AI Agents Skills

Skills for building and managing AI agents. This page lists all 2456 AI Agents skills indexed from 86 repositories (updated 2026-10-26). Every skill is free and open source — open one for the install command, or filter the interactive catalog to AI Agents.

1. find-me-skills luongnv89/asm · score 98/100 (grade A)
   Find Agent Skills for a goal the user cannot name yet, then export an installable bundle. Use when they ask which skills fit a project. Don't use for installing named skills, authoring skills, or catalog maintenance.
2. skill-install-improved luongnv89/asm · score 97/100 (grade A)
   Install an improved variant of one named skill: resolve it by local path, repo, or name, run skill-creator's retrofit on a throwaway copy, then install the improved result. Don't use for improving in place, upstream PRs, or plain asm install.
3. skill-index-updater luongnv89/asm · score 96/100 (grade A)
   Add GitHub skill repos to the ASM index: clone, audit, eval, regenerate index, rebuild catalog, open PR. Use when given GitHub URLs to onboard. Don't use for refreshing indexed repos (refresh-index), improving skills (skill-creator), or install.
4. auto-pilot luongnv89/idd · score 95/100 (grade A)
   Run an autonomous triage-resolve-review-merge loop to auto-pilot the GitHub issue backlog, resolving everything until done with zero prompts. Don't use for single-issue work (/issue-resolver), triage (/issue-triage), or PR review (/issue-pr-review).
5. seo-ai-optimizer luongnv89/skills · score 95/100 (grade A)
   Audit and optimize websites for technical SEO, content SEO, and AI bot accessibility. Fixes meta tags, sitemaps, robots.txt, structured data, llms.txt, and GPTBot/ClaudeBot directives. Don't use for App Store ASO, paid search, or blog writing.
6. agent-evals sickn33/antigravity-awesome-skills · score 94/100 (grade A)
   Build automated evaluation suites for AI agents using golden datasets,
7. openhook sickn33/antigravity-awesome-skills · score 94/100 (grade A)
   Creates private callback inboxes with Openhook. Use when an agent needs to wait for a webhook, inspect received HTTP/email/DNS events, or verify a test callback's contents.
8. skill-creator luongnv89/asm · score 94/100 (grade A)
   Create a skill or bring an existing one up to the same standard (validate + asm eval fix loop); run evals, tune triggering. Use when authoring, fixing, or retrofitting a skill. Don't use for invoking skills, writing prose, or Python scaffolds.
9. herdr-agent luongnv89/skills · score 93/100 (grade A)
   Manage AI agent fleets in Herdr: tile root + sub-agents in one tab, start/prompt/wait/read/monitor via the herdr agent CLI, steer any pane; `help` lists every operation. Use for Herdr fleets. Don't use for tmux, screen, or non-Herdr terminals.
10. ollama-optimizer luongnv89/skills · score 93/100 (grade A)
    Optimize Ollama configuration for the current machine's hardware. Use when asked to speed up Ollama, tune local LLM performance, or pick models that fit available GPU/RAM. Don't use for LM Studio, llama.cpp, vLLM, or hosted-API LLM providers.
11. opencode-runner luongnv89/skills · score 93/100 (grade A)
    Run coding tasks via opencode using free cloud models. Use when asked to offload work to opencode.ai or run a free model. Don't use for local models (Ollama, LM Studio), Claude/OpenAI calls, or when Claude should do the work itself.
12. skill-upstream-pr luongnv89/asm · score 93/100 (grade A)
    Improve an open-source GitHub skill and open a friendly suggestion PR upstream: fork, run skill-creator's retrofit, attach asm eval before/after metrics. Don't use for local-only skills, authoring from scratch, bulk repos, or registry publish.
13. tmux-agent-comms luongnv89/skills · score 93/100 (grade A)
    Manage AI agents in tmux: spawn sessions, send messages, wait, capture replies, inspect fleets, and tear down safely. Use for tmux-hosted CLI agents. Don't use for SSH, GNU screen, or GUI apps.
14. agent-config luongnv89/skills · score 92/100 (grade A)
    Create, update, or audit AGENTS.md (default) or CLAUDE.md agent instructions: set up, prune, add a rule, or merge CLAUDE.md or .cursorrules into one file Claude Code, Codex, and Cursor all read. Don't use for READMEs, skills, or subagents.
15. design-optimizer luongnv89/skills · score 92/100 (grade A)
    Optimize a website or app design in one run: capture the page once, audit usability, UX/AX, virality and agent readiness, merge overlaps into one prioritized report, apply fixes on opt-in. Don't use for one lens (dont-make-me-think, ux-ax-review).
16. doc-manager luongnv89/skills · score 92/100 (grade A)
    Generate or update docs to match the code, citing each claim to path:line and asking on ambiguity; runbook docs also get a check-only validation script. Don't use for API-reference autogen (JSDoc/Sphinx), landing pages, or CLAUDE.md/AGENTS.md.
17. outreachgenie-list-audit sickn33/antigravity-awesome-skills · score 92/100 (grade A)
    Audit saved OutreachGenie prospect lists against an outreach flow for missing template values, text limits and incomplete collection, using read-only MCP snapshots and local reports.
18. rex-agent luongnv89/skills · score 92/100 (grade A)
    Manage AI agent fleets in a Rex terminal: tile root + workers in one tab, start/prompt/wait/read them, check what they do, steer fleet panes; `help` lists all. Don't use for Herdr, tmux, or one-off Rex tabs, splits or commands.
19. website-agent-readiness luongnv89/skills · score 92/100 (grade A)
    Scan a site for agent readiness via isitagentready.com — for 'make this site agent-ready' or 'scan this site', incl. localhost. Plans the 0-5 gaps and files issues via /plan-to-issues. Not for SEO/llms.txt fixes or app-store ASO.
20. agy-powerline sickn33/antigravity-awesome-skills · score 91/100 (grade A)
    Install, check and restyle the agy-powerline statusline for Antigravity CLI (agy): quotas, model, context window and git on agy's status bar.
21. faber-language sickn33/antigravity-awesome-skills · score 90/100 (grade A)
    Write, check and run Faber programs, an experimental statically typed language for coding agents and human authors. Uses version-matched faberlang.dev language documentation.
22. goal-instruction-writer sickn33/antigravity-awesome-skills · score 90/100 (grade A)
    Preview, draft, refine, or audit durable agent Goals with acceptance evidence, drift controls, proportional verification, and bounded waiting. Use for multi-stage work, not one-shot prompts.
23. pixeltable sickn33/antigravity-awesome-skills · score 89/100 (grade B)
    Build Pixeltable apps in app.py with tables, computed columns, embedding search, and HTTP routes. Use for RAG, media pipelines, and tool-calling agents.
24. skill-skill sickn33/antigravity-awesome-skills · score 89/100 (grade B)
    Write, upgrade or audit a Claude skill so it changes what gets generated: forcing functions, triggerable descriptions, and a static audit script with a 0-100 health score. Use for 写 skill, 改 skill.
25. train-sentence-transformers sickn33/antigravity-awesome-skills · score 89/100 (grade B)
    Train or fine-tune SentenceTransformer, CrossEncoder, and SparseEncoder models for retrieval, similarity, clustering, classification, reranking, and related embedding tasks.
26. using-lwc sickn33/antigravity-awesome-skills · score 89/100 (grade B)
    Use when project decisions, code structure, research, incidents, or verified context must survive future coding-agent sessions through LWC memory and graph indexes.
27. agentic-test-audit sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Audit a pytest suite: surviving mutants and untested code, flaky, order-dependent and slow tests, and removal candidates checked on held-out mutants. Report-only.
28. agentic-verify sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Check that a Python change is caught by tests: run every mutant of the changed lines and write tests until they catch them. Reports evidence instead of a diff to read.
29. agents-generator sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, confidence scoring, and command validation.
30. context-engineering sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
31. datawebot sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Find products for sale across online shops, list returned sellers' prices with direct links, and run Amazon and Shopify extraction Jobs through the hosted datawebot MCP server.
32. dos-verify-done-claims sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Before accepting an agent's 'done / shipped / fixed' claim, verify it against ground truth (git ancestry + the commit's own diff) using the DOS kernel's `dos verify` and `dos commit-audit` — never the agent's own narration.
33. hypogenic K-Dense-AI/claude-scientific-skills · score 88/100 (grade B)
    Plans and audits use of ChicagoHAI HypoGeniC/HypoRefine for LLM-assisted hypothesis generation from labeled text datasets. Use for the `hypogenic` package, its task configs, hypothesis banks, or HypoBench datasets—not for manual hypothesis formulation or scientific validation.
34. idea-to-blueprint sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Turn a raw product, app, bot or feature idea into one evidence-backed build blueprint (researched stack, epics, Given/When/Then criteria, tests) that coding agents build one epic per session.
35. jenkins sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Create and manage Jenkins CI/CD pipelines, configure agents, manage plugins,
36. markitdown K-Dense-AI/claude-scientific-skills · score 88/100 (grade B)
    Converts heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.
37. monte-carlo-storage-cost-analysis sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Analyze a warehouse for stale, unused, or redundant tables via the analyze_storage_costs MCP tool. Classifies waste patterns and table categories, computes safety tiers, and handles category drill-downs and lineage follow-ups.
38. shipvela-publish sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Publish an explicitly selected website through the user's connected Shipvela MCP account, track the exact deployment, and return its live HTTPS URL after success.
39. skill-check sickn33/antigravity-awesome-skills · score 88/100 (grade B)
    Validate Claude Code skills against the agentskills specification. Catches structural, semantic, and naming issues before users do.
40. ecl-harness-engineer sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Create or audit ECL Agent Harness infrastructure: AGENTS.md, change tracking, repository guidance, lint checks, CI gates, and agent handoff docs.
41. folder-specific-claude-and-agents-md sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Create folder-scoped CLAUDE.md and AGENTS.md guidance for future agents working in that area.
42. gemini-deep-research sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Run autonomous multi-step research with Google's Gemini Deep Research Agent: kick off a query, poll progress, and collect a cited report for market analysis or literature reviews.
43. gemini-interactions-api sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Build with the Gemini Interactions API for text, chat, multimodal generation, streaming, managed or background agents, function calling, structured output, and generateContent migrations.
44. latchbio-integration K-Dense-AI/claude-scientific-skills · score 87/100 (grade B)
    Builds, registers, debugs, and operates bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP. Use when authoring or deploying Latch workflows, configuring resources or interfaces, moving data, integrating Registry, or launching and monitoring runs.
45. llmops-platform-engineering sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Build production LLMOps platforms with CI/CD, model promotion workflows,
46. mcd-secret-menu-lab sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Plan McDonald's China recipe combinations using an authorized MCP connection for current store menus, prices and nutrition. Use for recreating food hacks or exploring combinations within a budget.
47. mock-hunter sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Audit a live web page in five phases (catalog, click, trace, classify, report) to identify mock data, hardcoded values, LLM-generated metrics, and broken endpoints. Outputs a markdown report with REAL/MOCK/LLM/HARDCODED/BROKEN/UNKNOWN verdicts per visible value.
48. model-serving-kubernetes sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA
49. runapi-cli sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Generate AI images, videos, and music/audio from agents using the RunAPI CLI.
50. tree-ring-memory sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Use Tree Ring Memory for local-first AI-agent memory lifecycle work: recall, evidence, audit, forgetting, and consolidation without transcript dumping.
51. vllm-server sickn33/antigravity-awesome-skills · score 87/100 (grade B)
    Deploy and manage vLLM for high-throughput LLM inference. Configure continuous
52. agent-architecture github/awesome-copilot · score 86/100 (grade B)
    Design AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.
53. agent-memory sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
54. agents-v2-py sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Build container-based Foundry Agents with Azure AI Projects SDK (HostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.
55. assay sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Run assay on a web page you just wrote or changed. It opens the page in a real browser, drives every control, and reports where the page contradicts itself. Local browser checks without an LLM API key.
56. cohesivity sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Provision headless backend services for AI agents through Cohesivity: hosting, databases, storage, LLMs, and third-party APIs over one HTTP API. Use when a trusted .cohesivity file exists or the user approves a new backend.
57. effective-agent-skills sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Author and review high-quality agent skills with triggers, progressive disclosure, and safety notes.
58. ejentum-reasoning-harness sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    MCP server exposing four cognitive harness modes (reasoning, code, anti-deception, memory). Each call returns an engineered scaffold (failure pattern, procedure, suppression vectors, falsification test) the agent ingests before generating.
59. famulor-skill sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Operate Famulor assistants, communication history, campaigns, knowledge, automations, telephony, and workspace administration through its hosted MCP server.
60. find-complementary-founders sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Use when an owner explicitly asks for a cofounder or project partner, or explicitly says they need a complementary builder, operator, go-to-market partner, or scaling capability. Assess and publish only the agent's own owner, then rank only approved own-owner profiles.
61. goal-loop sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions.
62. grok-build sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Delegate well-specified implementation tasks to xAI's Grok Build CLI running headlessly while the orchestrating agent plans, writes task specs, reviews every diff, and owns the result.
63. hosted-agents-v2-py sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Build hosted agents using Azure AI Projects SDK with HostedAgentDefinition. Use when creating container-based agents in Azure AI Foundry.
64. hugging-face-community-evals sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate.
65. llm-gateway sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Deploy an API gateway for LLM traffic with load balancing, rate limiting,
66. mcp-dependency-drift-audit sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Statically audit MCP configs for mutable npm/npx package references before approval or CI, without executing discovered MCP servers.
67. ollama-stack sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Run local LLM workloads with Ollama, Open WebUI, and GPU-aware tuning
68. since-cutoff sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Find which APIs of a project's pinned Python dependencies changed after the model's training cutoff, where the code uses them, and write short AGENTS.md or CLAUDE.md notes.
69. spec-driven-loop sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Freeze PRD, technical design, and acceptance criteria before medium-to-large Codex work; coordinate agents with explicit ownership, then judge delivery from diffs, tests, and evidence.
70. system-prompt-lookup sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Checks what a shipped AI product's system prompt and tool schema actually say, by reading a dated archive of captured prompts instead of recalling them. Use before asserting or accepting any claim about an agent's instructions.
71. tokenleak sickn33/antigravity-awesome-skills · score 86/100 (grade B)
    Token-lean rules for coding agents: cut the context re-sent on every later call (big reads, noisy logs, re-reads, serial calls) without losing correctness.
72. agent-evaluation sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.
73. agent-memory-discipline sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.
74. agenttrace-session-audit sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.
75. ai-sre-incident-response sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Build AI-focused SRE incident response practices for LLM outages, degraded
76. api-sdk-generator sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Generates client SDK code, API wrapper libraries, request/response models, and language-specific usage patterns for any REST API.
77. ax-extract-workflow sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.
78. campaign-analytics alirezarezvani/claude-skills · score 85/100 (grade B)
    Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when analyzing marketing campaigns, ad performance, attribution models, conversion rates, or calculating marketing ROI, ROAS, CPA, and campaign metrics across channels.
79. claude-api sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Build apps with the Claude API or Anthropic SDK. TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`/`claude_agent_sdk`, or user asks to use Claude API, Anthropic SDKs, or Agent SDK. DO NOT TRIGGER when: code imports `openai`/other AI SDK, general programming, or ML/data-science tasks.
80. google-drive-automation sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Lightweight Google Drive integration with standalone OAuth authentication. No MCP server required. Full read/write access.
81. hugging-face-vision-trainer sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Train object detection, image classification, and SAM or SAM2 segmentation models locally or on Hugging Face Jobs, with bounded dataset pilots and explicit artifact persistence.
82. image-generator sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Generate and edit images using Gemini's Nano Banana Pro model (gemini-3-pro-image-preview). Use this skill when the user asks you to generate images, create visuals, edit photos, create logos, generate product mockups, or perform any image generation/editing task.
83. lambdatest-agent-skills sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Production-grade test automation skills for 46 frameworks across E2E, unit, mobile, BDD, visual, and cloud testing in 15+ languages.
84. llm-fine-tuning sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Set up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full
85. monte-carlo-monitoring-advisor sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.
86. skill-audit sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Pre-install review framework for AI agent skills: inspect complete content, permissions, dependencies and suspicious behavior before activation.
87. skill-security-audit sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Audit an Agent Skill, MCP server, connector, or desktop extension before installation by tracing code, dependencies, permissions, credentials, data flow, and irreversible actions.
88. speech-engine elevenlabs/skills · score 85/100 (grade B)
    Add real-time voice conversations to a custom agent runtime with ElevenLabs Speech Engine. Use when building Speech Engine servers, WebSocket handlers, WebRTC browser clients, conversation token endpoints, interruption-aware streaming responses, or voice-enabled chat agents that connect developer-owned server logic to ElevenLabs speech-to-text and text-to-speech.
89. webly sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Publish a website or share files at a live URL in seconds with no account, then let the person claim it, edit it over Webly's MCP server, and publish drafts they approve.
90. x-twitter-scraper sickn33/antigravity-awesome-skills · score 85/100 (grade B)
    Use Xquik for X data workflows: tweet search, user lookup, follower export, media downloads, monitors, webhooks, REST API, MCP, SDK setup, and approval-gated account actions.
91. your-skill-name Affitor/affiliate-skills · score 85/100 (grade B)
    Replace with when the AI should activate this skill. Be pushy — cover multiple phrasings so the AI activates for a wide range of user prompts.
92. acquire-codebase-knowledge github/awesome-copilot · score 84/100 (grade B)
    Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
93. agents elevenlabs/skills · score 84/100 (grade B)
    Build voice AI agents with ElevenLabs. Use when creating voice assistants, customer service bots, interactive voice characters, or any real-time voice conversation experience, and when configuring an agent's tools, workflows, or procedures, including creating, editing, and publishing free-form and structured procedure drafts on an agent branch over the SDKs or REST API.
94. ai-prompt-regression-testing sickn33/antigravity-awesome-skills · score 84/100 (grade B)
    Use when comparing prompt changes against a fixed evaluation set: record actual model settings, required checks, missing results, judge limitations and case-level regression evidence.
95. anti-ui-slop sickn33/antigravity-awesome-skills · score 84/100 (grade B)
    Stop coding agents from shipping generic UI. Extend the product's design system, use UIZZE evidence only when useful, cover required states, and inspect the rendered result.
96. aws-mcp-setup sickn33/antigravity-awesome-skills · score 84/100 (grade B)
    Configure AWS MCP servers for documentation search and API access. Use when setting up AWS MCP, configuring AWS documentation tools, troubleshooting MCP connectivity, or when user mentions aws-mcp, awsdocs, uvx setup, or MCP server configuration.
97. codex-fable5 sickn33/antigravity-awesome-skills · score 84/100 (grade B)
    Apply Fable-inspired discipline to Codex work: inspect first, track goals and findings, ground conclusions in evidence, verify before completion, and adapt Claude/Fable prompt guidance without identity or provider claims.
98. court sickn33/antigravity-awesome-skills · score 84/100 (grade B)
    Put an idea on trial: a prosecutor and a defense Claude argue, 12 juror sub-agents vote independently, and a judge reads the verdict and the changes that would flip it.
99. cursor-delegate sickn33/antigravity-awesome-skills · score 84/100 (grade B)
    Delegate coding tasks to the Cursor Agent CLI (`cursor-agent`) only when
100. doomsday-escrow sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Verify cryptographic Proof-of-Escrow collateral (L1 UTXO outpoint proofs and Base Mainnet wDOOM settlement receipts) on GitHub bounties before spending autonomous agent compute.
101. esl-price-sync sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Synchronizes retail prices between ERP/POS systems and Electronic Shelf Labels (SES-imagotag, ZKONG, Pricer, Hanshow, SOLUM) with delta watermarking, idempotency, and battery modeling. Trigger phrases: esl price sync, electronic shelf labels, zkong sync, ses imagotag price, ghost pricing audit.
102. generate-nanobanana sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Generate and edit images/video with Google's Gemini media models (Nano Banana 2/Pro, Gemini Omni Flash), with cost-approval gates, reference-image support, and a prompt/output log per call.
103. idea-autopsy sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Autopsy a business idea before you build it: kill-list check, five hard filters, a free-AI one-prompt test, live ad-market verification, and a verdict with a named kill-pattern.
104. lamindb K-Dense-AI/claude-scientific-skills · score 84/100 (grade B)
     Manages biological datasets and models with LaminDB, including artifact registration, lineage tracking, schema validation, Bionty ontology annotation, query/search, collections, branches, storage, and workflow integrations. Use for reproducible biological data curation or a LaminDB lakehouse.
105. loop-library sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Find, compare, adapt, and design bounded AI-agent feedback loops with explicit checks, stop rules, guardrails, and handoffs.
106. loopy sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication.
107. monte-carlo-remediation sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Investigate and remediate data quality alerts using Monte Carlo MCP tools. Runs root cause analysis, assesses blast radius, discovers available tools (MCP/CLI/API), proposes and executes fixes, or escalates with full context when uncertain.
108. n8n-multi-instance sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Select, verify, and safely switch n8n MCP instances across production, staging, teams, or clients, especially before credential writes.
109. neon-postgres sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Guides and best practices for working with Neon Serverless Postgres. Covers setup, connection methods, branching, autoscaling, scale-to-zero, read replicas, connection pooling, Neon Auth, and the Neon CLI, MCP server, REST API, TypeScript SDK, and Python SDK.
110. neverapply sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Find matching jobs, tailor resumes, prepare for interviews and apply to jobs with the user's approval through NeverApply's hosted MCP server (OAuth sign-in).
111. odw sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Dynamic multi-agent workflows — plan first, then orchestrate parallel agents with adversarial verification via the local odw daemon. Use when the user asks for a "workflow", says "ultracode", or hands you a task spanning many files/items that benefits from parallel agents.
112. omentir-linkedin-outreach sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Run LinkedIn prospecting and outreach through the Omentir MCP server: find people, score fit, draft messages, and check campaigns. Never signs into LinkedIn.
113. open-dynamic-workflows sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Plan, orchestrate, and adversarially verify parallel AI coding agents with a dynamic multi-agent workflow engine.
114. pymc K-Dense-AI/claude-scientific-skills · score 84/100 (grade B)
     Builds and checks Bayesian models with PyMC, including hierarchical models, NUTS MCMC, variational inference, mutable-data predictions, posterior predictive checks, diagnostics, and PSIS-LOO model comparison. Use for probabilistic modeling and uncertainty inference in PyMC.
115. routerbase-model-gateway sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.
116. sshepherd sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Zero-knowledge SSH ops CLI — server health checks, docker/systemd control, log tailing, Postgres introspection, and declarative deploys, without ever exposing credentials to the agent.
117. usage-engineer sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Cut wasted tokens in coding-agent sessions: compact long logs, stop identical retries, check stale project maps, and audit local Codex/OpenCode usage.
118. yao-meta-skill sickn33/antigravity-awesome-skills · score 84/100 (grade B)
     Create, refactor, evaluate, and package agent skills from workflows, prompts, transcripts, docs, or notes. Use for skill creation, reusable workflow packaging, skill improvement, evals, and team-ready distribution.
119. adversarial-reviewer alirezarezvani/claude-skills · score 83/100 (grade B)
     Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.
120. ai-pipeline-orchestration sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Orchestrate AI/ML pipelines for data ingestion, model training, batch
121. ai-security-hardening sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Harden AI/LLM deployments against prompt injection, data exfiltration,
122. browser-testing-with-devtools sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Test browser apps with Chrome DevTools MCP by inspecting live DOM, console logs, network traffic, screenshots, accessibility, and performance traces.
123. bug-hunt-swarm sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Parallel read-only multi-agent root-cause investigation for bugs, regressions, crashes, flaky behavior, or unexplained failures.
124. bumblebee sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Run Bumblebee supply-chain inventory and exposure scans on macOS/Linux to detect compromised packages, extensions, and MCP host configs.
125. cmux sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.
126. codex-delegate sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Delegate coding tasks to the OpenAI Codex CLI only when the user explicitly
127. cooper-email sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Give an AI agent its own email inbox with Cooper Email: send, receive, reply, and wait for replies or verification codes over MCP or HTTP.
128. documentation-and-adrs sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
129. esm K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
     Uses the Biohub esm Python SDK for ESM3 protein generation, ESMC embeddings, and ESMFold2 all-atom folding. Applies to local model inference and Biohub hosted clients, including former Forge workflows; distinguishes the separate legacy fair-esm distribution.
130. evaluation sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Build evaluation frameworks for agent systems. Use when testing agent performance systematically, validating context engineering choices, or measuring improvements over time.
131. gmail-automation sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Lightweight Gmail integration with standalone OAuth authentication. No MCP server required.
132. hf-mem sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub
133. modellix sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Integrate the Modellix API/CLI for async AI image, video, and speech generation or transcription (model run --wait, task download).
134. neon-postgres-branches sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Choose and create the right Neon branch type for testing and development. Use when users ask about Neon branching, migration testing with real data, isolated test environments, schema-only branch workflows for sensitive data, or branch creation via Neon CLI or Neon MCP.
135. neuropixels-analysis K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
     Analyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
136. ontoly-software-graph sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Use Ontoly's deterministic Software Graph, MCP server, and agent skills for architecture review, request tracing, impact analysis, and dependency analysis.
137. pennylane K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
     Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for open-system dynamics use qutip.
138. polis-protocol sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Coordinate multi-vendor AI agents as a self-improving team — a learning router assigns work by track record and citizens can amend the protocol's own rules.
139. prompt-engineer-toolkit alirezarezvani/claude-skills · score 83/100 (grade B)
     Turns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version history with diffs, ready-to-use marketing prompt templates (ad copy, email campaigns, social posts, landing pages, SEO meta), and an LLM-governance playbook for marketing teams (claim discipline, disclosure rules, human-review gates). Use when a marketing team relies on AI-generated content and needs prompt quality to be measurable and safe — or when the user mentions 'prompt engineering,' 'improve my prompts,' 'prompt templates,' 'prompt versioning,' 'AI content workflow,' or 'AI governance for marketing.'
140. serply-search-mcp sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Search Google, Bing, Google News and Google Scholar, and read public pages, with the Serply MCP server. Use when the user chooses Serply or its connected tools for current information and source verification.
141. shark sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Pitch a business idea to a Shark Tank-style panel of Claude sub-agent investors who grill it, hear a founder agent answer, and each go IN or OUT with a practice offer.
142. textme sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Text Claude from your phone — set up the njerschow/textme daemon so inbound iMessages drive a Claude Code session on your laptop, with voice notes, image input, code execution, and a phone-number whitelist.
143. ui-states sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Design and build the UI states agents forget: first use, empty, loading, error, offline, no results, long content, permission denied and success.
144. unship sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Compare AI agent-made UI variants locally in a real app, then keep one and clean up unused temporary code.
145. using-n8n-mcp-skills sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Route n8n MCP workflow design, editing, validation, testing, deployment, credential, execution, and debugging tasks to specialist guidance.
146. weaviate-cookbooks sickn33/antigravity-awesome-skills · score 83/100 (grade B)
     Build Weaviate AI apps from official cookbook blueprints for RAG, agentic RAG, data exploration, multimodal PDF search, async clients, and frontends.
147. agent-orchestration-multi-agent-optimize sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
148. agent-qa-debug-fix sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.
149. altorank sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Run AltoRank through its hosted MCP server: readiness audits, Search Console, keyword research, and SEO drafts into a review queue.
150. anywrite sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.
151. apple-notes-search sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
152. architecture-review sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Review repository architecture using Ontoly Software Graph and MCP capabilities.
153. aws-agentic-ai sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations.
154. cc-skill-strategic-compact sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Prepare a verified checkpoint before condensing an agent conversation at a phase boundary. Use during long tasks when context is repetitive; preserves constraints, evidence, decisions and the next action.
155. compile-knowledge sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Compile durable, non-obvious findings into an interlinked markdown knowledge store — atomic files, [[wiki-links]], a maintained index — so an agent gets smarter across sessions instead of relearning the same facts.
156. deepchem K-Dense-AI/claude-scientific-skills · score 82/100 (grade B)
     Builds molecular property prediction and MoleculeNet workflows with DeepChem, including SMILES featurization, scaffold or grouped holdouts, masked labels, graph models and explicit pretrained encoder transfer. Used for ADMET, toxicity, solubility and chemistry ML when DeepChem data/model contracts and scientific validation are needed.
157. dispatch sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Delegate tasks to OpenAI Codex CLI and Google Antigravity CLI from Claude Code with topic-aware sessions
158. dispatching-parallel-agents sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
159. ditto sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Use when a user asks to mine or update a private, evidence-backed work profile from local Claude Code, Codex, Copilot CLI, or OpenCode sessions.
160. falsify sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     The scientific thinking protocol for AI agents. Use when facing complex, ambiguous, or high-stakes questions where guessing is costly: hypothesis → attempt to break it → evidence → calibrated conclusion.
161. generate-image K-Dense-AI/claude-scientific-skills · score 82/100 (grade B)
     Generates or edits images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.
162. huggingface-local-models sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.
163. huggingface-spaces sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants.
164. krexa sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Turn a trading idea, post or video into fixed rules, backtest and paper-trade them, and request a user-approved live agent through Krexa's MCP server. Cannot move funds.
165. linkdigest-social-link-reader sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Read one public Xiaohongshu, Douyin, TikTok, YouTube, X or WeChat article link into text an agent can use (transcript, image text, key points) via the LinkDigest API or MCP server.
166. logic-fix-all sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Autonomous repository-wide audit-and-fix pipeline: health → review → locate/explain → fix → diff-verify → iterate until clean. Starts with a mandatory consent prompt (token-intensive); after consent runs hands-free.
167. looot sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Search, price and run 2,500+ data API endpoints (work emails, company search, SERP, web pages) from one prepaid balance via the looot MCP server.
168. mac-mini-llm-lab sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Configure a Mac mini as a reliable local LLM server with remote access,
169. n8n-binary-and-data sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Handle n8n files and binary data across uploads, downloads, transforms, multimodal inputs, agent tools, and chat surfaces.
170. pangolinfo-amazon-data-research sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Plan and run read-only Amazon product, review, category, seller, and market research through Pangolinfo's documented MCP bridge.
171. parallel-search-mcp sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Search the public web and verify sources with Parallel's free Search MCP. Use when the user chooses Parallel or its connected tools for current information and URL extraction.
172. pm-skills alirezarezvani/claude-skills · score 82/100 (grade B)
     Use when coordinating project-delivery work across the 8 project-management sub-skills — sprint/velocity analytics, portfolio health, Jira/JQL, Confluence, Atlassian admin, templates, meeting analysis, team comms. Triggers on 'our sprints feel off', 'project health report', 'audit our Jira permissions', 'when will it be done', 'run the delivery loop'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a full goal→plan→execute→verify→close delivery loop through the repo-wide agent-harness with Jira MCP data bridged into the domain's analytics tools. Distinct from product-team (what to build vs how to deliver it), business-operations (internal ops), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).
173. skill-creator bytedance/deer-flow · score 82/100 (grade B)
     Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
174. skill-scanner sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Scan agent skills for security issues before adoption. Detects prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks.
175. solidping sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Run SolidPing uptime monitoring through its hosted MCP server: list and diagnose checks, read results and incidents, create checks across 40+ types, and manage status pages.
176. talivia-agent-kit sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Set up and verify Talivia revenue analytics through MCP, with explicit confirmation for website changes and payment attribution.
177. terraform-patterns alirezarezvani/claude-skills · score 82/100 (grade B)
     Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state management strategies, provider configuration, security hardening, policy-as-code with Sentinel/OPA, and CI/CD plan/apply workflows. Use when: user wants to design Terraform modules, manage state backends, review Terraform security, implement multi-region deployments, or follow IaC best practices.
178. triage sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.
179. unslop-file sickn33/antigravity-awesome-skills · score 82/100 (grade B)
     Humanize natural-language memory files (CLAUDE.md, todos, preferences, docs) by removing AI-isms and adding burstiness while preserving every code block, URL, path, command, and heading exactly.
180. web-performance-audit warpdotdev/oz-skills · score 82/100 (grade B)
     Audit web performance using Chrome DevTools MCP. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed.
181. write-a-skill alirezarezvani/claude-skills · score 82/100 (grade B)
     Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author a new skill.
182. agent-reels sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Find animation and video references on 1human, consult a human-agent shared library, and contribute public creations only with prior owner permission.
183. agentmail sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and inspect billing balance via the AgentMail API.
184. antigravity-maintainer-batch-release sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Run protected AAS maintainer sweeps, PR merge batches, resumable review, immutable distribution, Core checks, and scripted releases. Use for repository maintenance, main alignment, CLI/MCP/Workbench changes, or release work; not ordinary contribution tasks.
185. aomi-transact sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Build natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.
186. azure-ai-document-intelligence-dotnet sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models.
187. buddy-sings MiniMax-AI/skills · score 81/100 (grade B)
     Use when user wants their Claude Code pet (/buddy) to sing a song. Triggers on any request that combines the concept of their Claude Code buddy, pet, or companion with singing or music. Supports multilingual triggers — match equivalent phrases in any language.
188. clarvia-aeo-check sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Score any MCP server, API, or CLI for agent-readiness using Clarvia AEO (Agent Experience Optimization). Use current provider evidence as advisory input when evaluating a tool.
189. clinical-decision-support K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
     Prepares and validates research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Supports aggregate or synthetic research documentation and traceability, excluding patient care and live clinical operation.
190. conductor-setup sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Configure a Rails project to work with Conductor (parallel coding agents)
191. constraint-driven-development sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Write the project quality bar as enforced CONSTRAINTS.md so agents stop
192. context-engineering addyosmani/agent-skills · score 81/100 (grade B)
     Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
193. context-kit sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Evaluate, adapt, and safely install Context Kit personal context artifacts for Claude Code or adjacent agent workflows.
194. devcontainer-setup sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Creates devcontainers with Claude Code, language-specific tooling (Python/Node/Rust/Go), and persistent volumes. Use when adding devcontainer support to a project, setting up isolated development environments, or configuring sandboxed Claude Code workspaces.
195. domain-modeling sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
196. email-marketing-bible sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Data-backed email marketing for AI agents: automation flows, deliverability triage, copy de-slopping, AI email design, ESP control via MCP with send gates and compliance.
197. eval-driven-dev github/awesome-copilot · score 81/100 (grade B)
     Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.
198. expo-examples sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Expo's official example projects — the expo/examples repo of ~70 `with-*` integrations (Stripe, Clerk, Supabase, OpenAI, maps, Reanimated, SQLite, Skia, NativeWind, and more).
199. free-tier-strategy sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Design free tiers that convert to paid without creating resentment or abuse. Trigger phrases: free tier design, freemium model, free trial strategy, free tier limits, developer free plan, open source commercial, feature gating, upgrade triggers, free tier conversion
200. gtars K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
     Supports Gtars for local genomic interval models and set algebra, overlaps and counts, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and the CLI.
201. hugging-face-model-trainer sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment.
202. hunt-dispatch sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Skill-set loader for /hunt orchestrator.
203. invokely-statistics sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Use Invokely MCP to find official statistics, retrieve values and series, compare or rank places, and report each figure with its period, unit, and source citation.
204. keenable-search-mcp sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Search the public web with site and date filters, and read pages with an extraction prompt, through Keenable's keyless MCP server. Use when the user chooses Keenable or its connected tools.
205. klaviyo-automation sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Automate Klaviyo tasks via Rube MCP (Composio): manage email/SMS campaigns, inspect campaign messages, track tags, and monitor send jobs. Always search tools first for current schemas.
206. llm-council sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Run Fireworks-hosted open-weight model councils that compare responses and synthesize a final answer.
207. mcp-server-security sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Secure Model Context Protocol (MCP) servers with transport encryption,
208. model-registry-governance sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Establish model registry standards, governance controls, metadata schemas,
209. model-supply-chain-security sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Secure the AI model supply chain with artifact signing, provenance attestation,
210. orca-replay sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Answers questions about a past agent run from its recording rather than from memory, and replays or forks that run. Use when asked why an earlier run did something, or to reproduce a failure.
211. pathml K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
     Supports local computational pathology research with PathML: slide loading and tiling, preprocessing and QC, h5path storage, multiplex quantification, spatial graphs, and bounded model inference. Use for whole-slide H&E, CODEX, Vectra, Mesmer, HoVer-Net, and HACTNet workflows.
212. pi-delegate sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Delegate coding tasks to the Pi coding agent CLI (`pi`) only when the
213. power-platform-mcp-connector-suite github/awesome-copilot · score 81/100 (grade B)
     Generate complete Power Platform custom connector with MCP integration for Copilot Studio - includes schema generation, troubleshooting, and validation
214. pro-motion sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Make a motion-graphics launch, brand or promo film audio first: plan the music, then render the film in code (canvas to MP4) cut to the track. Use for 发布视频, 宣传片, TVC, BGM, Suno prompts.
215. prompt-caching-strategy affaan-m/ECC · score 81/100 (grade B)
     Optimize LLM prompt caching hit rate to reduce API costs and improve latency. Analyzes prompt structure, identifies cacheable vs non-cacheable content, and recommends restructuring to maximize cache reuse. TRIGGER when: user says "prompt cache", "cache hit rate", "reduce LLM cost", "optimize token usage", "cheaper LLM calls", or asks about prompt caching strategies for OpenAI/Anthropic/other providers. DO NOT TRIGGER when: user just wants to optimize a single prompt's quality (use prompt-optimizer instead), or asks about general caching infrastructure.
216. prompt-caching-strategy affaan-m/everything-claude-code · score 81/100 (grade B)
     Optimize LLM prompt caching hit rate to reduce API costs and improve latency. Analyzes prompt structure, identifies cacheable vs non-cacheable content, and recommends restructuring to maximize cache reuse. TRIGGER when: user says "prompt cache", "cache hit rate", "reduce LLM cost", "optimize token usage", "cheaper LLM calls", or asks about prompt caching strategies for OpenAI/Anthropic/other providers. DO NOT TRIGGER when: user just wants to optimize a single prompt's quality (use prompt-optimizer instead), or asks about general caching infrastructure.
217. prompt-optimizer affaan-m/ECC · score 81/100 (grade B)
     Analyze draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis and rationale — advisory only, never executes the task. Use when the user says 'optimize prompt', 'improve my prompt', 'rewrite this prompt', 'help me prompt', 优化prompt, 改进prompt, 怎么写prompt, or 帮我优化这个指令; not for requests to optimize code or performance.
218. prompt-optimizer affaan-m/everything-claude-code · score 81/100 (grade B)
     Analyze draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis and rationale — advisory only, never executes the task. Use when the user says 'optimize prompt', 'improve my prompt', 'rewrite this prompt', 'help me prompt', 优化prompt, 改进prompt, 怎么写prompt, or 帮我优化这个指令; not for requests to optimize code or performance.
219. protect-mcp-governance sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Agent governance skill for MCP tool calls — Cedar policy authoring, shadow-to-enforce rollout, and Ed25519 receipt verification.
220. rayden-use sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Build and maintain Rayden UI components and screens in Figma via Figma MCP with full design token enforcement
221. run-deep-swe sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Run reproducible DeepSWE coding-agent benchmark evaluations through OpenRouter and mini-swe-agent.
222. scvelo K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
     Performs RNA velocity analysis with scVelo from spliced and unspliced single-cell RNA counts. Fits deterministic or dynamical models, examines gene phase portraits, builds velocity graphs, estimates relative latent time, and ranks velocity-associated genes. Use for directional trajectory hypotheses and kinetic-model diagnostics alongside Scanpy; velocity alone does not establish cell fate or causal drivers.
223. senior-prompt-engineer alirezarezvani/claude-skills · score 81/100 (grade B)
     Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.
224. skill-issue sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Find out why a coding-agent skill won't fire — grade each SKILL.md A–F on activation, simulate which skill a prompt triggers, and flag collisions where one silently shadows another.
225. taisly-social-media-posting sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Use Taisly Agent Kit to prepare and publish approved short-form video posts across TikTok, Instagram Reels, YouTube Shorts, X, and Facebook.
226. transformers K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
     Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with AutoModel, pipelines, tokenizers, generation configs, or TrainingArguments within Transformers.
227. url-to-markdown sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Fetch a public webpage as clean Markdown for an agent: read, summarize, quote, or cite the page while preserving its source URL.
228. warp-delegate sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Delegate coding tasks to the Warp Agent CLI (`oz`) only when the user
229. write-design-md sickn33/antigravity-awesome-skills · score 81/100 (grade B)
     Write or update a project's DESIGN.md from the colors, type, spacing and components it really uses, with rules agents follow so new screens match.
230. xlsx ComposioHQ/awesome-claude-skills · score 81/100 (grade B)
     Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
231. agent-identifier Galaxy-Dawn/claude-scholar · score 80/100 (grade B)
     Use when creating or configuring Claude Code agents and their frontmatter.
232. agent-observability sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Instrument AI agents with tracing, token metrics, latency, and cost visibility.
233. agent-self-evaluation affaan-m/ECC · score 80/100 (grade B)
     Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.
234. agent-self-evaluation affaan-m/everything-claude-code · score 80/100 (grade B)
     Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.
235. agent-self-scheduling sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
236. agentphone sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Build AI phone agents with AgentPhone API. Use when the user wants to make phone calls, send/receive SMS, manage phone numbers, create voice agents, set up webhooks, or check usage — anything related to telephony, phone numbers, or voice AI.
237. amplitude-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. Always search tools first for current schemas.
238. automated-triage sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
239. autoskill K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Analyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose skills.
240. azure-ai-agents-persistent-dotnet sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
241. azure-ai-projects-dotnet sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.
242. backend-development-feature-development sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.
243. brand-guidelines-anthropic sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     To access Anthropic's official brand identity and style resources, use this skill.
244. brand-guidelines-community sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     To access Anthropic's official brand identity and style resources, use this skill.
245. brave-man sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Runs a structured clarifying interview for new project requests before building. Instead of writing code, it outputs a fully specified prompt.md for a fresh agent session to execute, preventing expensive mistakes.
246. brooks-harness sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Maintenance orchestrator for the brooks-lint plugin itself.
247. byagent sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Publish agent-written Markdown or HTML as a shareable link with the byagent CLI, then read readers' line comments back, edit, republish to the same link and resolve them.
248. claude-settings-audit sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Analyze a repository to generate recommended Claude Code settings.json permissions. Use when setting up a new project, auditing existing settings, or determining which read-only bash commands to allow. Detects tech stack, build tools, and monorepo structure.
249. coda-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Coda tasks via Rube MCP (Composio): manage docs, pages, tables, rows, formulas, permissions, and publishing. Always search tools first for current schemas.
250. codex-subagent sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Launch Codex CLI as an isolated subagent for bounded coding, review, or verification tasks.
251. convertkit-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate ConvertKit (Kit) tasks via Rube MCP (Composio): manage subscribers, tags, broadcasts, and broadcast stats. Always search tools first for current schemas.
252. darkmoon-pentest sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Start, follow and triage authorized autonomous AI pentest runs on a self-hosted Darkmoon Pro instance through its MCP server.
253. depmap K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Retrieves and analyzes Cancer Dependency Map (DepMap) release data, including CRISPR Chronos gene effects, cancer model annotations, omics biomarkers, and PRISM drug sensitivity. Supports cancer-selective dependency, co-essentiality, and candidate synthetic-lethality analyses with release-aware identifiers and statistical checks.
254. discord-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Discord tasks via Rube MCP (Composio): messages, channels, roles, webhooks, reactions. Always search tools first for current schemas.
255. effective-agent-skills davidondrej/skills · score 80/100 (grade B)
     Write, review, and debug agent skills. Use when creating or editing SKILL.md files, improving skill structure, or diagnosing invocation and execution problems.
256. enhance-prompt sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
257. faf-go sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Guided interview to Gold Code (100% AI-Readiness). Use when helping users improve their .faf file through questions. Leverages Claude Code's AskUserQuestion for seamless integration. Just type /faf-go and answer questions till done.
258. fal-workflow sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Generate workflow JSON files for chaining AI models
259. gdb-cli sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     GDB debugging assistant for AI agents - analyze core dumps, debug live processes, investigate crashes and deadlocks with source code correlation
260. google-analytics-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Google Analytics tasks via Rube MCP (Composio): run reports, list accounts/properties, funnels, pivots, key events. Always search tools first for current schemas.
261. gtm-ai-gtm github/awesome-copilot · score 80/100 (grade B)
     Go-to-market strategy for AI products. Use when positioning AI products, handling "who is responsible when it breaks" objections, pricing variable-cost AI, choosing between copilot/agent/teammate framing, or selling autonomous tools into enterprises.
262. helium-mcp sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Connect to Helium's MCP server for news research, media bias analysis, balanced perspectives, stock/options data, and semantic meme search across 3.2M+ articles and 5,000+ sources
263. intercom-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Intercom tasks via Rube MCP (Composio): conversations, contacts, companies, segments, admins. Always search tools first for current schemas.
264. jev-use sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Route enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jev_judge and jev_gate MCP tools, batched into one call per state.
265. kernel-prompt sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Use when composing or improving an LLM prompt or agent instruction. Asks one round of questions, then returns only the prompt; never performs the task.
266. kubestellar-console sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Multi-cluster Kubernetes dashboard with AI-powered operations via MCP server and 10+ built-in agent skills
267. langchain-architecture sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.
268. lognorm sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Work a site's SEO and AI-visibility (GEO) backlog through the hosted LogNorm MCP server: audits, fixes, content, AI-answer tracking.
269. mcp-builder sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
270. mcp-copilot-studio-server-generator github/awesome-copilot · score 80/100 (grade B)
     Generate a complete MCP server implementation optimized for Copilot Studio integration with proper schema constraints and streamable HTTP support
271. open-notebook K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Organizes research with the self-hosted Open Notebook alternative to NotebookLM. Supports source ingestion (PDFs, web pages, audio, video, and Office documents), cited document chat, text and vector search, notes, custom transformations, and multi-speaker podcasts. Use when automating Open Notebook through its REST API or configuring its local or cloud AI providers, including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral.
272. optim-agent sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Guide agent-driven parameter optimization for configurable systems with measurable objectives. Use for HPO, inference tuning, simulations, or RL/control experiments.
273. performance-testing-review-multi-agent-review sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Review a defined code diff from relevant correctness, authorization and performance perspectives; delegate only when authorized and reproduce findings centrally.
274. prompt-engineer sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)
275. prompt-engineering sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
276. pybamm K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Simulates lithium-ion battery charge, discharge and rest experiments with PyBaMM, records parameter-set provenance, checks mesh and solver sensitivity, and compares predicted voltage curves with measured cycling data. Use for SPM or DFN electrochemical battery modeling, C-rate protocols, voltage cutoffs, parameter studies and numerical validation of battery simulations.
277. pydantic-ai sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
278. quality-playbook github/awesome-copilot · score 80/100 (grade B)
     Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.
279. review-swarm sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps.
280. scikit-learn sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.
281. scikit-survival K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Builds, evaluates, and audits right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.
282. setup-gbrain garrytan/gstack · score 80/100 (grade B)
     Set up gbrain for this coding agent: install the CLI, initialize a local PGLite or Supabase brain, register MCP, capture per-remote trust policy. (gstack)
283. skill-creator anthropics/skills · score 80/100 (grade B)
     Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
284. socialclaw sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Agent-first social media publishing skill — schedule and publish posts across the listed platforms (X, LinkedIn, Instagram, Facebook Pages, TikTok, Discord, Telegram, YouTube, Reddit, WordPress, Pinterest) via a single workspace API key.
285. statsmodels K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Fits and diagnoses Python statistical models including OLS, GLM, discrete and mixed models, ARIMA and SARIMAX. Supports coefficient inference, marginal effects, model comparison and time series forecasting with explicit design and uncertainty checks. Used for econometrics and statistical modeling; for guided test selection with APA reporting, see statistical-analysis.
286. taasky sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Negotiate terms with another person or their agent through the hosted Taasky MCP server: meeting times, prices, dates. The human confirms every accept, reject or withdraw.
287. tellurium K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
     Simulates biochemical kinetic models from SBML or Antimony with Tellurium and libRoadRunner, checks model units, compares deterministic parameter perturbations, and exports and replays SBML plus SED-ML COMBINE archives. Use for reaction-network time courses, kinetic parameters, concentration dynamics and reproducible simulation experiments; steady-state constraint-based metabolic flux analysis belongs to cobrapy.
288. twitter-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Twitter/X tasks via Rube MCP (Composio): posts, search, users, bookmarks, lists, media. Always search tools first for current schemas.
289. typesafe-ai typesafe-ai/skills · score 80/100 (grade B)
     TypeSafe integration craft for System One models (sometimes called Decision Models) such as Jev, which answer typed questions about text, images, and application state with calibrated probabilities. Use when building, reviewing, or debugging code that calls TypeSafe; when writing its questions or state; when replacing an LLM prompt-and-parse step, keyword matching, or a brittle heuristic with a typed question; or when brainstorming where programmable common sense fits in an app.
290. unified-ai-gateway sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Operate and evaluate Unified AI System through fifteen governed MCP tools, including provider-free prompt enhancement, while preserving fake-provider, authorization, and evidence boundaries.
291. using-agent-skills sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Meta-skill for discovering and invoking the right agent skill for the
292. vercel-automation sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Automate Vercel tasks via Rube MCP (Composio): manage deployments, domains, DNS, env vars, projects, and teams. Always search tools first for current schemas.
293. vps-server-management sickn33/antigravity-awesome-skills · score 80/100 (grade B)
     Manage authorized VPS hosts and server-side agents through cautious SSH and operations workflows.
294. a4a sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Connect your AI agent to the A4A end-to-end encrypted agent-to-agent messaging network via local MCP tools or Python SDK.
295. activecampaign-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
296. agent-platform-prompt-management google/skills · score 79/100 (grade C)
     Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.
297. agent-qa-authoring sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.
298. ai-agent-security sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Secure AI agents against prompt injection, tool abuse, and data exfiltration
299. ai-agent-tool-routing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use when designing or reviewing an AI agent tool registry or MCP router: document parameter schemas, caller authorization, execution limits, replay-safe retries and verification evidence.
300. ai-coding-agent-guardrails sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission
301. ai-engineer sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
302. airtable-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
303. anti-ui-slop github/awesome-copilot · score 79/100 (grade C)
     Stop coding agents from shipping generic UI. Use UIZZE''s 800,000+ real web and iOS screens to build product-specific interfaces, define a design contract, cover required states, and run a hard finish gate. Use when designing, implementing, redesigning, critiquing, or pre-ship reviewing a web or iOS interface in Codex, Claude Code, Cursor, Copilot, or another coding agent. Trigger with "anti-ui-slop", "stop UI slop", "ground this UI in real screens", or "run the UI finish gate".
304. antigravity-skill-orchestrator sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
305. antigravity-workflows sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use when asked to ship a SaaS MVP, audit application security, build an AI agent, run browser QA, or design a domain model with multiple skills and verified checkpoints.
306. arize-instrumentation github/awesome-copilot · score 79/100 (grade C)
     Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.
307. axonx sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Develop AxonX research plugins and operate quantitative research tasks through CLI or MCP, inspecting execution status, logs, artifacts, and lineage.
308. azure-ai-openai-dotnet sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Azure OpenAI SDK for .NET. Client library for Azure OpenAI and OpenAI services. Use for chat completions, embeddings, image generation, audio transcription, and assistants.
309. bilig-workpaper sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use formula-backed WorkPaper JSON and MCP tools for agent spreadsheet tasks without driving Excel or a browser UI.
310. boat davidondrej/skills · score 79/100 (grade C)
     Manage Boat (boat.dev, formerly Box by Ascii) cloud sandboxes via API, CLI, and SSH. Use for provisioning, environments, secrets, templates, snapshots, stop/resume/fork, or running BB and coding agents on Boat.
311. buywhere-product-catalog sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use BuyWhere's MCP and API surfaces to add product search, price comparison, and deal discovery to AI shopping agents.
312. caio-review alirezarezvani/claude-skills · score 79/100 (grade C)
     /c-level-agents:caio-review [plan] — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring. Use when shipping an AI feature without an eval set, choosing between API, fine-tune, and self-hosted, or classifying a use case under the EU AI Act.
313. cal-com-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Cal.com tasks via Rube MCP (Composio): manage bookings, check availability, configure webhooks, and handle teams. Always search tools first for current schemas.
314. canva-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Canva tasks via Rube MCP (Composio): designs, exports, folders, brand templates, autofill. Always search tools first for current schemas.
315. career-ops santifer/career-ops · score 79/100 (grade C)
     Open-source AI job search agent -- evaluate offers, generate CVs, scan portals, track applications. Use when the user pastes a job URL or JD, asks to scan portals, generate a CV/PDF, track applications, prepare for interviews, draft outreach/emails, or run any career-ops mode.
316. circleci-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate CircleCI tasks via Rube MCP (Composio): trigger pipelines, monitor workflows/jobs, retrieve artifacts and test metadata. Always search tools first for current schemas.
317. close-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Close CRM tasks via Rube MCP (Composio): create leads, manage calls/SMS, handle tasks, and track notes. Always search tools first for current schemas.
318. create-agentsmd github/awesome-copilot · score 79/100 (grade C)
     Prompt for generating an AGENTS.md file for a repository
319. cs-agile-product-owner alirezarezvani/claude-skills · score 79/100 (grade C)
     Agile product owner agent for epic breakdown, sprint planning, backlog refinement, and INVEST-compliant user story generation. Use when preparing work for a development team — e.g., decomposing a large epic into INVEST-compliant stories with acceptance criteria, or refining a messy backlog ahead of sprint planning.
320. datadog-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Always search tools first for current schemas.
321. gemini-api-dev sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use this skill when building applications with Gemini API hosted models, including Gemini and Gemma 4, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications.
322. github-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Operate GitHub issues, pull requests, branches, checks, workflows, and permissions through Rube MCP. Use when GitHub work must be queried or changed programmatically with repository-policy safeguards.
323. gpt-taste sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use when generating elite GSAP-heavy frontend pages with strict AIDA structure, wide hero typography, and gapless bento grids.
324. hf-mcp sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.
325. hugging-face-paper-publisher sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
326. hugging-face-papers sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page.
327. jira-integration affaan-m/ECC · score 79/100 (grade C)
     Use this skill when retrieving Jira tickets, analyzing requirements, updating ticket status, adding comments, or transitioning issues. Provides Jira API patterns via MCP or direct REST calls.
328. jira-integration affaan-m/everything-claude-code · score 79/100 (grade C)
     Use this skill when retrieving Jira tickets, analyzing requirements, updating ticket status, adding comments, or transitioning issues. Provides Jira API patterns via MCP or direct REST calls.
329. linkedin-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate LinkedIn tasks via Rube MCP (Composio): create posts, manage profile, company info, comments, and image uploads. Always search tools first for current schemas.
330. lintlang-audit sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Audit named agent instructions, tool definitions, and supported Python prompts with local LintLang checks; return finding codes and locations without changing files.
331. llm-app-security sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Secure LLM-powered applications with input validation, output controls,
332. llm-inference-scaling sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU
333. lore sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Markdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.
334. m365-agents-dotnet sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Microsoft 365 Agents SDK for .NET. Build multichannel agents for Teams/M365/Copilot Studio with ASP.NET Core hosting, AgentApplication routing, and MSAL-based auth.
335. make-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Make (Integromat) tasks via Rube MCP (Composio): operations, enums, language and timezone lookups. Always search tools first for current schemas.
336. mcp-builder warpdotdev/oz-skills · score 79/100 (grade C)
     Build high-quality MCP (Model Context Protocol) servers that let LLMs interact with external services through well-designed tools. Use when creating MCP servers to integrate APIs or services in Python (FastMCP) or Node/TypeScript (MCP SDK).
337. mixpanel-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Mixpanel tasks via Rube MCP (Composio): events, segmentation, funnels, cohorts, user profiles, JQL queries. Always search tools first for current schemas.
338. modal K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
     Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.
339. multi-agent-architect sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.
340. multi-tenant-llm-hosting sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Design secure, multi-tenant LLM hosting platforms with tenant isolation,
341. n8n-agents sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Design n8n AI agents, chains, classifiers, extractors, tool calling, memory, RAG, structured output, and human-review flows.
342. notion-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Notion tasks via Rube MCP (Composio): pages, databases, blocks, comments, users. Always search tools first for current schemas.
343. orchestrate sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Coordinate focused subagents on substantial work, keep their ownership non-overlapping, and integrate verified results. Use for large-scope Codex tasks; keep trivial work with the coordinator.
344. orchestrate-batch-refactor Dimillian/Skills · score 79/100 (grade C)
     Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.
345. outlook-calendar-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Outlook Calendar tasks via Rube MCP (Composio): create events, manage attendees, find meeting times, and handle invitations. Always search tools first for current schemas.
346. outreachagent sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Operate reply-aware cold outbound email workflows for AI agents with inboxes, contacts, templates, pacing, approvals, webhooks, and delivery metrics.
347. pagerduty-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate PagerDuty tasks via Rube MCP (Composio): manage incidents, services, schedules, escalation policies, and on-call rotations. Always search tools first for current schemas.
348. postmark-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Postmark email delivery tasks via Rube MCP (Composio): send templated emails, manage templates, monitor delivery stats and bounces. Always search tools first for current schemas.
349. protocolsio-integration K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
     Reads, validates, and safely exports protocols.io data with current official REST/MCP contracts, or creates non-executing mutation plans. The bundled client makes bounded official-host GET requests only with explicit --execute. Use only for tasks explicitly targeting protocols.io or an exact protocols.io protocol version.
350. qrx sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Make branded, print-ready art QR codes to validate before use with QRX (qrx.codes). Use when a link needs a QR code that looks like artwork or matches a brand for print, packaging, signs, slides or event badges, and to list or re-point QRX codes. Not for plain QR codes the agent makes locally.
351. realtime elevenlabs/skills · score 79/100 (grade C)
     Use ElevenLabs Realtime models (`eleven_realtime_v1_mini`, `eleven_realtime_v1_max`), the low-latency models built for voice conversation. Use when the user wants to create an ElevenAgents agent on a Realtime model or switch an existing agent's Voice mode to Realtime, set `conversation_config.realtime_model`, choose between Realtime Mini and Max, or debug a Realtime agent that won't publish or transfer. Also use when migrating a voice app built on OpenAI's Realtime API and SDK (`@openai/agents-realtime`, `gpt-realtime`) to the OpenAI-compatible ElevenLabs Realtime API, including the `client_secrets` mint, the WebSocket transport, and audio after leaving WebRTC (closes with 4001/4003, no audio). Not for choosing an agent's LLM or TTS model in Custom mode, Scribe realtime speech-to-text, or migrating Chat Completions or Responses API text calls.
352. scanpy K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
     Performs Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or SingleCellExperiment RDS conversion to h5ad. Applies to established exploratory scRNA-seq workflows with explicit count and expression provenance; complementary skills cover scvi-tools models and AnnData format details.
353. scikit-learn K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
     Supports machine learning in Python with scikit-learn. Applies when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
354. scvi-tools K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
     Fits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.
355. secops-cases google/skills · score 79/100 (grade C)
     Manage Google Security Operations (SecOps) SOAR cases throughout their lifecycle. Use when listing, creating, inspecting, updating, or closing SOAR cases; adding investigative comments and notes; updating case priority or description; or linking and grouping security alerts within cases. Supports both remote Google SecOps MCP tools and local fallback tools. Don't use for SIEM UDM searches or detection rule authoring.
356. segment-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Segment tasks via Rube MCP (Composio): track events, identify users, manage groups, page views, aliases, batch operations. Always search tools first for current schemas.
357. sentry-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Sentry tasks via Rube MCP (Composio): manage issues/events, configure alerts, track releases, monitor projects and teams. Always search tools first for current schemas.
358. skill-writer sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Create and improve agent skills following the Agent Skills specification. Use when asked to create, write, or update skills.
359. threat-modeling sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Conduct threat modeling using STRIDE methodology. Identify threats, assess
360. tokenwise sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Measurement-driven model router for Claude Code. Routes Haiku/Sonnet/Opus per task class, logs every routed task with real $ numbers, and A/B tests cheaper tiers before you trust the savings.
361. tool-design sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Build tools that agents can use effectively, including architectural reduction patterns. Use when creating new tools for agent systems, debugging tool-related failures or misuse, or optimizing existing tool sets for better agent performance.
362. torchdrug K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
     Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.
363. uiverify-triage-visual-changes sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Triage a UI Verify visual regression build from your coding agent over MCP: sort changed screenshots into regressions, intended changes and noise, then accept baselines.
364. unity-ai-game-creator sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Transform raw game ideas into complete Unity projects with AI-powered asset generation, scene blueprints, music/SFX prompts, and step-by-step development procedures using Unity 6+ and modern AI tools.
365. usage-based-pricing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Design pricing models that developers understand, accept, and can predict. Trigger phrases: usage-based pricing, API pricing, metered billing, developer pricing, pricing page, cost calculator, pay as you go, pricing transparency, competitive pricing, developer billing
366. verification-loop affaan-m/ECC · score 79/100 (grade C)
     Run a six-phase verification of a Claude Code session's work — build, type check, lint, tests with coverage, security grep, and diff review — then produce a PASS/FAIL verification report. Use when verifying work after completing a feature or refactor, before creating a PR, or when quality gates must pass.
367. verification-loop affaan-m/everything-claude-code · score 79/100 (grade C)
     Run a six-phase verification of a Claude Code session's work — build, type check, lint, tests with coverage, security grep, and diff review — then produce a PASS/FAIL verification report. Use when verifying work after completing a feature or refactor, before creating a PR, or when quality gates must pass.
368. wrike-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Wrike project management via Rube MCP (Composio): create tasks/folders, manage projects, assign work, and track progress. Always search tools first for current schemas.
369. youtube-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate YouTube tasks via Rube MCP (Composio): upload videos, manage playlists, search content, get analytics, and handle comments. Always search tools first for current schemas.
370. zendesk-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
     Automate Zendesk tasks via Rube MCP (Composio): tickets, users, organizations, replies. Always search tools first for current schemas.
371. advanced-evaluation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Design LLM-as-judge rubrics, direct scores and pairwise comparisons. Use for judge models, evals, position bias and calibration against human labels.
372. agent-memory-mcp sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
373. agent-platform-tuning-management google/skills · score 78/100 (grade C)
     Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use `agent-platform-tuning`), deploying models to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).
374. agent-protocol alirezarezvani/claude-skills · score 78/100 (grade C)
     Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.
375. ai-seo sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
376. airflow-dag-patterns sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
377. andrej-karpathy sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
378. anndata K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Handles annotated matrices in single-cell analysis, .h5ad and Zarr files, and integration with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
379. asana-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.
380. asc-aso-audit rudrankriyam/app-store-connect-cli-skills · score 78/100 (grade C)
     Run an offline ASO audit on canonical App Store metadata under `./metadata` and surface keyword gaps using Astro MCP. Use after pulling metadata with `asc metadata pull`.
381. atlas-cloud-media sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
382. attack-chain sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Authorized multi-stage attack-path planning and orchestration spanning reconnaissance, initial access, privilege escalation, lateral movement, and reporting. Entry point for full engagements and cross-phase operations.
383. audit-agent-run-evidence sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Use when an agent, harness, gateway, MCP workflow, or multi-step automation claims completion and the available traces, checkpoints, approvals, tool calls, or deployment records must be judged without trusting self-reported success.
384. bamboohr-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate BambooHR tasks via Rube MCP (Composio): employees, time-off, benefits, dependents, employee updates. Always search tools first for current schemas.
385. bdistill-knowledge-extraction sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
386. book-to-skill alirezarezvani/claude-skills · score 78/100 (grade C)
     Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills — extracting named frameworks, principles, techniques, and anti-patterns into a master SKILL.md plus on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Use when the user wants to study a document with an agent, apply an author's frameworks while working, turn internal docs or standards into a reusable knowledge base, or package a compiled book skill as a claude-skills plugin.
387. calendly-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Calendly scheduling, event management, invitee tracking, availability checks, and organization administration via Rube MCP (Composio). Always search tools first for current schemas.
388. claude-code-guide sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     To provide a comprehensive reference for configuring and using Claude Code (the agentic coding tool) to its full potential. This skill synthesizes best practices, configuration templates, and advanced usage patterns.
389. code-review-and-quality sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
390. context-compression sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     When agent sessions generate millions of tokens of conversation history, compression becomes mandatory. The naive approach is aggressive compression to minimize tokens per request.
391. context-degradation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems.
392. create-skill Affitor/affiliate-skills · score 78/100 (grade C)
     Turn a repeatable AI prompt or workflow into a structured, shareable skill for the affiliate-skills GitHub repository. Use this skill when the user wants to create a new skill, write a SKILL.md, convert a prompt to a skill, share a skill via the GitHub repo, or document an AI workflow. Also trigger for: "create a skill", "write a skill", "make this a skill", "turn this into a skill", "publish skill", "add skill to list", "write SKILL.md", "skill from prompt", "document this workflow", "package this as a skill".
393. crypto-bd-agent sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Reference patterns (upstream reports, not independently verified here) for building AI agents that autonomously discover, evaluate, and acquire token listings for cryptocurrency exchanges.
394. customer-success-manager alirezarezvani/claude-skills · score 78/100 (grade C)
     Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.
395. data-scientist sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence.
396. delegating-to-agents sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Delegate bounded work to other AI agents while preserving context, ownership, and progress checks.
397. dispatching-parallel-agents obra/superpowers · score 78/100 (grade C)
     Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
398. distribute-skill-to-all-agents sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Distribute a skill across configured agent skill folders while respecting local symlink layouts.
399. dmux-workflows affaan-m/ECC · score 78/100 (grade C)
     Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
400. dmux-workflows affaan-m/everything-claude-code · score 78/100 (grade C)
     Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
401. emblemai-crypto-wallet sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Crypto wallet management across 7 blockchains via EmblemAI Agent Hustle API. Balance checks, token swaps, portfolio analysis, and transaction execution for Solana, Ethereum, Base, BSC, Polygon, Hedera, and Bitcoin.
402. error-debugging-multi-agent-review sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Review a defined code diff from relevant correctness, authorization and performance perspectives; delegate only when authorized and reproduce findings centrally.
403. eval-harness affaan-m/ECC · score 78/100 (grade C)
     Eval-driven development (EDD) framework for AI coding sessions — define capability and regression evals before coding, grade with code-based, model-based, rule, or human graders, and track pass@k and pass^k reliability. Use when defining pass/fail criteria for agent tasks, measuring agent reliability, building regression suites for prompt or agent changes, or benchmarking across model versions.
404. eval-harness affaan-m/everything-claude-code · score 78/100 (grade C)
     Eval-driven development (EDD) framework for AI coding sessions — define capability and regression evals before coding, grade with code-based, model-based, rule, or human graders, and track pass@k and pass^k reliability. Use when defining pass/fail criteria for agent tasks, measuring agent reliability, building regression suites for prompt or agent changes, or benchmarking across model versions.
405. event-staffing-compliance sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Assess worker-classification and compliance risk for temporary event staffing in the US and Canada — W-2 vs 1099, misclassification penalties, joint-employer liability, COI, and wage/hour rules. Includes live state-by-state lookups via MCP.
406. figma-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Figma tasks via Rube MCP (Composio): files, components, design tokens, comments, exports. Always search tools first for current schemas.
407. freshservice-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Freshservice ITSM tasks via Rube MCP (Composio): create/update tickets, bulk operations, service requests, and outbound emails. Always search tools first for current schemas.
408. geniml K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Supports audited local Geniml genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.
409. git-worktree-manager alirezarezvani/claude-skills · score 78/100 (grade C)
     Run parallel feature work safely with Git worktrees. Standardizes branch isolation, port allocation, environment sync, and cleanup so each worktree behaves like an independent local app. Optimized for multi-agent workflows where each agent or terminal session owns one worktree. Use when running multiple feature branches simultaneously, isolating experimental work, or coordinating multi-agent development across the same repo.
410. goal-loop davidondrej/skills · score 78/100 (grade C)
     Draft /goal prompts and explain persistent agent loops. Use for goal or Ralph loops, autonomous run setup, monitoring, and troubleshooting.
411. google-cloud-storage-basics google/skills · score 78/100 (grade C)
     Stores, retrieves, and manages data as objects in Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Use when you need to interact with Cloud Storage — set up a Storage MCP server (remote or local Toolbox), create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set storage classes (Standard, Nearline, Coldline, Archive), manage lifecycle and cost, protect data (versioning, CMEK, retention, Bucket Lock, holds, soft delete), host static websites, trigger Pub/Sub notifications, mount buckets (gcsfuse), or optimize performance. Covers gcloud storage / gsutil, JSON/XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for generic MCP setup that doesn't mention Cloud Storage, other MCP servers, block storage (Persistent Disk), BigQuery, or databases (Cloud SQL, Spanner, Bigtable, Firestore).
412. helpdesk-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate HelpDesk tasks via Rube MCP (Composio): list tickets, manage views, use canned responses, and configure custom fields. Always search tools first for current schemas.
413. hosted-agents sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Build background agents in sandboxed environments. Use for hosted coding agents, sandboxed VMs, Modal sandboxes, and remote coding environments.
414. hugging-face-datasets sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
415. huggingface-best sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores.
416. impediment-prioritization github/awesome-copilot · score 78/100 (grade C)
     Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula. Use when someone asks to prioritize, rank, sequence, or triage impediments, countermeasures, remediation items, risks, findings, gaps, action items, or backlog entries; or mentions value-stream prioritization, A3 / lean countermeasure ranking, ROI vs. effort scoring, or building a remediation / improvement backlog. Works with GHQR findings, audit results, retrospective action items, risk registers, architecture review gaps, or any free-form `{impediment, countermeasure}` list.
417. instagram-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Instagram tasks via Rube MCP (Composio): create posts, carousels, manage media, get insights, and publishing limits. Always search tools first for current schemas.
418. internal-comms-anthropic sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Compatibility alias for internal-comms: draft status updates, newsletters and FAQs from approved sources.
419. jira-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Jira tasks via Rube MCP (Composio): issues, projects, sprints, boards, comments, users. Always search tools first for current schemas.
420. kubernetes-deployment sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Kubernetes deployment workflow for container orchestration, Helm charts, service mesh, and production-ready K8s configurations.
421. last30days sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Research a topic from the last 30 days on Reddit + X + Web, summarize evidence, and write copy-paste-ready prompts for the user's target tool.
422. linear-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Linear tasks via Rube MCP (Composio): issues, projects, cycles, teams, labels. Always search tools first for current schemas.
423. liteparse K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Local document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.
424. llm-caching sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Implement multi-layer LLM caching with exact match, semantic similarity,
425. logic-lens sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     AI-powered Claude Code skill that performs deep code review using formal logic and reasoning frameworks to detect bugs, anti-patterns, and security risks beyond what linters catch.
426. loki-mode sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Historical 2.35.x multi-agent workflow for turning a scoped PRD into reviewed implementation; includes experimental runner and benchmark artifacts.
427. mcp-tool-developer sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Build Model Context Protocol (MCP) servers and tools from scratch. Full-stack MCP development with TypeScript/Python, testing, deployment, and registry publishing.
428. microsoft-teams-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Microsoft Teams tasks via Rube MCP (Composio): send messages, manage channels, create meetings, handle chats, and search messages. Always search tools first for current schemas.
429. moyu sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Anti-over-engineering guardrail that activates when an AI coding agent expands scope, adds abstractions, or changes files the user did not request.
430. multi-agent-patterns sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.
431. n8n-subworkflows sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Build reusable n8n sub-workflows with typed inputs, all-vs-each execution, discoverable naming, and agent-tool exposure.
432. one-drive-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate OneDrive file management, search, uploads, downloads, sharing, permissions, and folder operations via Rube MCP (Composio). Always search tools first for current schemas.
433. orchestrate-batch-refactor sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Plan and execute large refactors with dependency-aware work packets and parallel analysis.
434. outlook-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Outlook tasks via Rube MCP (Composio): emails, calendar, contacts, folders, attachments. Always search tools first for current schemas.
435. parallel-agents sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
436. pi-web-search sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Give Pi Agents a safe web-search and fetch workflow using the installed pi-web-access package.
437. playwright-java sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Scaffold, write, debug, and enhance enterprise-grade Playwright E2E tests in Java using Page Object Model, JUnit 5, Allure reporting, and parallel execution.
438. posthog-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate PostHog tasks via Rube MCP (Composio): events, feature flags, projects, user profiles, annotations. Always search tools first for current schemas.
439. ppt-orchestra-skill MiniMax-AI/skills · score 78/100 (grade C)
     Plan and orchestrate multi-slide PowerPoint creation from scratch. Use before generating a full deck with subagents: classify each slide type, enforce visual variety, set typography/spacing rules, and run text-based QA to catch content issues.
440. pyhealth K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Builds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.
441. qutip K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Simulate and audit closed and open quantum-system models with QuTiP 5, including deterministic, trajectory, steady-state, spectral, and phase-space workflows. Use for local quantum-dynamics work where physical assumptions, dimensions, and numerical convergence must be explicit.
442. reddit-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Reddit tasks via Rube MCP (Composio): search subreddits, create posts, manage comments, and browse top content. Always search tools first for current schemas.
443. render-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Render tasks via Rube MCP (Composio): services, deployments, projects. Always search tools first for current schemas.
444. salesforce-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Salesforce tasks via Rube MCP (Composio): leads, contacts, accounts, opportunities, SOQL queries. Always search tools first for current schemas.
445. sandbase-mcp sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Discover, inspect, and invoke 2,000+ AI models and APIs through SandBase's local MCP bridge with explicit schema and cost checks.
446. shader-dev MiniMax-AI/skills · score 78/100 (grade C)
     Comprehensive GLSL shader techniques for creating stunning visual effects — ray marching, SDF modeling, fluid simulation, particle systems, procedural generation, lighting, post-processing, and more.
447. shopify-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Shopify tasks via Rube MCP (Composio): products, orders, customers, inventory, collections. Always search tools first for current schemas.
448. skill-creator sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Create and review reusable skill drafts with bundled Python scaffolding, basic frontmatter validation and ZIP packaging helpers. Use for skill authoring and packaging; verify target-host requirements separately.
449. skill-improver sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Iteratively improve a Claude Code skill using the skill-reviewer agent until it meets quality standards. Use when improving a skill with multiple quality issues, iterating on a new skill until it meets standards, or automated fix-review cycles instead of manual editing.
450. skill-suggester sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Scan prompt history for recurring patterns and unmet needs, then propose new skills or command templates
451. square-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Square tasks via Rube MCP (Composio): payments, orders, invoices, locations. Always search tools first for current schemas.
452. startup-financial-modeling sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups.
453. statistical-analysis K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.
454. stitch-ui-design sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Expert guidance for crafting effective prompts in Google Stitch, the AI-powered UI design tool by Google Labs. This skill helps create precise, actionable prompts that generate high-quality UI designs for web and mobile applications.
455. subagent-orchestrator sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Coordinate quota-aware parallel subagents for large, multi-file Antigravity tasks.
456. supabase-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.
457. telegram-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Telegram tasks via Rube MCP (Composio): send messages, manage chats, share photos/documents, and handle bot commands. Always search tools first for current schemas.
458. tiktok-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate TikTok tasks via Rube MCP (Composio): upload/publish videos, post photos, manage content, and view user profiles/stats. Always search tools first for current schemas.
459. torch-geometric K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
     Supports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch_geometric, not for general NetworkX analytics or non-graph PyTorch models.
460. value-ladder-architect Affitor/affiliate-skills · score 78/100 (grade C)
     Design the complete free-to-premium value ladder for affiliate promotions. Triggers on: "value ladder", "customer journey", "upsell path", "ascension model", "free to paid funnel", "tripwire offer", "upsell strategy", "downsell", "product ladder", "price ladder", "customer ascension", "funnel architecture", "map my funnel", "design my funnel stages", "monetization path".
461. whatsapp-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate WhatsApp Business tasks via Rube MCP (Composio): send messages, manage templates, upload media, and handle contacts. Always search tools first for current schemas.
462. zoom-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
     Automate Zoom meeting creation, management, recordings, webinars, and participant tracking via Rube MCP (Composio). Always search tools first for current schemas.
463. adhx sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.
464. agent-creator sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Create custom AI subagents with proper plugin structure, persona generation, and companion routing skills.
465. agent-evaluation-reporting sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when summarizing agent evaluations where autonomous, assisted, failed, timed-out, or invalid outcomes must remain distinct and comparable.
466. agent-harness-fault-injection sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
467. agent-squad sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Main agent orchestrator that coordinates a specialized squad of agents
468. agents-md sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Create, revise, or audit AGENTS.md files from repository evidence, verified commands, and correctly scoped instructions without overwriting maintainer intent.
469. ai-agent-evaluation-benchmarking sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Autonomous AI agent benchmark evaluation register: task completion rates, planning accuracy, tool invocation precision, and cost benchmarks.
470. ai-native-cli sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.
471. alphagenome K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
     Looks up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), scores variants or scans windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and builds Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.
472. api-gateway-mcp-server google/skills · score 77/100 (grade C)
     Configures Google Cloud API Gateway to act as a remote Model Context Protocol (MCP) server (Public Preview) that exposes REST APIs as agent tools over HTTP (POST /mcp). Use when migrating OpenAPI 2.0 specs to OpenAPI 3.x for MCP, annotating specs with x-google-api-management.mcp and x-google-mcp-tool, securing tools/list with JWTs or API keys, connecting Google ADK (McpToolset) or Apigee API hub and Agent Registry, or troubleshooting MCP JSON-RPC errors (-32601, -32602, -32000). Do not use for Apigee X proxy bundles, outbound LLM model routing, or GKE Gateway API.
473. autoresearch-agent alirezarezvani/claude-skills · score 77/100 (grade C)
     Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.
474. azure-mgmt-weightsandbiases-dotnet sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability.
475. basecamp-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Basecamp project management, to-dos, messages, people, and to-do list organization via Rube MCP (Composio). Always search tools first for current schemas.
476. bigquery-migration-sql-translator google/skills · score 77/100 (grade C)
     Translates SQL queries, DDL schemas, and stored procedures from legacy database dialects (Teradata, Oracle, Redshift, Snowflake, SparkSQL, HiveQL) to BigQuery GoogleSQL using the BigQuery Migration Service (BQMS) MCP server. Use when translating legacy SQL queries, migrating schemas or metadata zip archives, or configuring BigQuery Migration Service (BQMS) YAML translation settings. Don't use for executing BigQuery queries or managing datasets and tables (use bigquery-basics), diagnosing runtime job errors (use bigquery-troubleshooting), or tuning slot reservations (use bigquery-optimization).
477. bitbucket-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Bitbucket repositories, pull requests, branches, issues, and workspace management via Rube MCP (Composio). Always search tools first for current schemas.
478. breakdown-test github/awesome-copilot · score 77/100 (grade C)
     Test Planning and Quality Assurance prompt that generates comprehensive test strategies, task breakdowns, and quality validation plans for GitHub projects.
479. claude-delegate sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Delegate coding tasks to a separate Claude Code CLI process or Claude
480. claude-in-chrome-troubleshooting sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Diagnose and fix Claude in Chrome MCP extension connectivity issues. Use when mcp__claude-in-chrome__* tools fail, return "Browser extension is not connected", or behave erratically.
481. clean-code-guard sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Review generated or changed production code with Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks.
482. clickup-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate ClickUp project management including tasks, spaces, folders, lists, comments, and team operations via Rube MCP (Composio). Always search tools first for current schemas.
483. codebase-onboarding affaan-m/ECC · score 77/100 (grade C)
     Analyze an unfamiliar codebase and generate a structured onboarding guide with architecture map, key entry points, conventions, and a starter CLAUDE.md. Use when joining a new project or setting up Claude Code for the first time in a repo.
484. codebase-onboarding affaan-m/everything-claude-code · score 77/100 (grade C)
     Analyze an unfamiliar codebase and generate a structured onboarding guide with architecture map, key entry points, conventions, and a starter CLAUDE.md. Use when joining a new project or setting up Claude Code for the first time in a repo.
485. codehealth-mcp affaan-m/ECC · score 77/100 (grade C)
     Real-time structural Code Health via CodeScene MCP — review before edits, verify score deltas after changes, gate commits and PRs. Use when reviewing code quality, refactoring, checking if AI changes degraded a file, or before commit/PR.
486. codehealth-mcp affaan-m/everything-claude-code · score 77/100 (grade C)
     Real-time structural Code Health via CodeScene MCP — review before edits, verify score deltas after changes, gate commits and PRs. Use when reviewing code quality, refactoring, checking if AI changes degraded a file, or before commit/PR.
487. confluence-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Confluence page creation, content search, space management, labels, and hierarchy navigation via Rube MCP (Composio). Always search tools first for current schemas.
488. copilot-sdk sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Build applications that programmatically interact with GitHub Copilot. The SDK wraps the Copilot CLI via JSON-RPC, providing session management, custom tools, hooks, MCP server integration, and streaming across Node.js, Python, Go, and .NET.
489. counterparty-channel-discipline affaan-m/ECC · score 77/100 (grade C)
     Per-channel strict prompts, mention gating, silent observation, and a communication autonomy policy for agents that sit in shared channels with external counterparties. Use when an agent joins group chats, shared channels, or DMs where outsiders can read every message and you need it to speak only when addressed, never leak internal context, and route risky content to draft-only approval.
490. counterparty-channel-discipline affaan-m/everything-claude-code · score 77/100 (grade C)
     Per-channel strict prompts, mention gating, silent observation, and a communication autonomy policy for agents that sit in shared channels with external counterparties. Use when an agent joins group chats, shared channels, or DMs where outsiders can read every message and you need it to speak only when addressed, never leak internal context, and route risky content to draft-only approval.
491. crewai sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Design role-based agents, tasks, crews, and flows with CrewAI.
492. cs-ux-researcher alirezarezvani/claude-skills · score 77/100 (grade C)
     UX research agent for research planning, persona generation, journey mapping, and usability test analysis. Use when product decisions need user evidence — e.g., planning interview scripts and recruiting criteria for a discovery study, or synthesizing usability-test sessions into prioritized findings and updated personas.
493. developing-genkit-dart google/skills · score 77/100 (grade C)
     Generates code and provides documentation for the Genkit Dart SDK. Use when the user asks to build AI agents in Dart, use Genkit flows, or integrate LLMs into Dart/Flutter applications.
494. docker-development alirezarezvani/claude-skills · score 77/100 (grade C)
     Docker and container development agent skill and plugin for Dockerfile optimization, docker-compose orchestration, multi-stage builds, and container security hardening. Use when: user wants to optimize a Dockerfile, create or improve docker-compose configurations, implement multi-stage builds, audit container security, reduce image size, or follow container best practices. Covers build performance, layer caching, secret management, and production-ready container patterns.
495. docusign-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate DocuSign tasks via Rube MCP (Composio): templates, envelopes, signatures, document management. Always search tools first for current schemas.
496. dropbox-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Dropbox file management, sharing, search, uploads, downloads, and folder operations via Rube MCP (Composio). Always search tools first for current schemas.
497. earllm-build sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Build, maintain, and extend the EarLLM One Android project — a Kotlin/Compose app that connects Bluetooth earbuds to an LLM via voice pipeline.
498. etsy-search-listings sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Fetch live Etsy search listing rows for a keyword, market phrase, or category via Apify Actor publicrecords/etsy-search-scraper (MCP). Needs an Apify token; Actor run is billed.
499. event-staffing-ordering sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Order W-2 compliant temporary event staff for conventions, trade shows, festivals, concerts, sporting events, and brand activations across 300+ US and Canadian markets via TempGuru. Covers city coverage, role pricing, availability, state compliance lookups via MCP, and request submission.
500. figma-create-design-system-rules openai/skills · score 77/100 (grade C)
     Generates custom design system rules for the user's codebase. Use when user says "create design system rules", "generate rules for my project", "set up design rules", "customize design system guidelines", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.
501. film-crew sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Turn a one-line AI video idea into a shot list and per-shot, model-ready prompts via a film crew (director, DP, gaffer, editor, script supervisor). Also fixes failing video prompts and diagnoses bad clips before a reroll. Works with Wan, LTX, Kling, Veo, Seedance, Hailuo, Runway.
502. full-stack-orchestration-full-stack-feature sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when working with full stack orchestration full stack feature
503. gemini-api-integration sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when integrating Google Gemini API into projects. Covers model selection, multimodal inputs, streaming, function calling, and production best practices.
504. git-pr-workflows-git-workflow sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Orchestrate review, tests, commits, branch pushes, and pull-request creation with parallel agents. Use when completed changes must move through validation into a PR or guarded merge.
505. gitlab-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate GitLab project management, issues, merge requests, pipelines, branches, and user operations via Rube MCP (Composio). Always search tools first for current schemas.
506. global-agent-guardrails davidondrej/skills · score 77/100 (grade C)
     Configure the shared guard against catastrophic shell commands in local AI agents. Use when changing block patterns, adding an agent or machine, or investigating why a command was or wasn't blocked.
507. hunt-llm-ai sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Hunt LLM/AI feature bugs
508. instructree sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Map, explain, and lint repository-scoped coding-agent instructions before changing code.
509. karpathy-coder alirezarezvani/claude-skills · score 77/100 (grade C)
     Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
510. langsmith-fetch ComposioHQ/awesome-claude-skills · score 77/100 (grade C)
     Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
511. lightning-architecture-review sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Review Bitcoin Lightning Network protocol designs, compare channel factory approaches, and analyze Layer 2 scaling tradeoffs. Covers trust models, on-chain footprint, consensus requirements, HTLC/PTLC compatibility, liveness, and watchtower support.
512. llm-app-patterns sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Architecture and integration sketches for LLM applications, with explicit retrieval, tool, privacy and verification boundaries.
513. llm-prompt-optimizer sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage.
514. m365-agents-py sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Microsoft 365 Agents SDK for Python. Build multichannel agents for Teams/M365/Copilot Studio with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based auth.
515. memory-systems sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Design short-term, long-term, and graph-based memory architectures. Use when building agents that must persist across sessions, needing to maintain entity consistency across conversations, or implementing reasoning over accumulated knowledge.
516. miro-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Miro tasks via Rube MCP (Composio): boards, items, sticky notes, frames, sharing, connectors. Always search tools first for current schemas.
517. monday-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Monday.com work management including boards, items, columns, groups, subitems, and updates via Rube MCP (Composio). Always search tools first for current schemas.
518. monte-carlo-monitor-creation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.
519. multi-agent-brainstorming sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.
520. n8n-mcp-tools-expert sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns.
521. pipedrive-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Pipedrive CRM operations including deals, contacts, organizations, activities, notes, and pipeline management via Rube MCP (Composio). Always search tools first for current schemas.
522. plan-orchestrate affaan-m/ECC · score 77/100 (grade C)
     Read a plan document, decompose it into steps, classify each step, and emit the ready-to-paste ECC slash command for that step, carrying the step identifier and scope in the command's own documented argument form. Generative only — never invokes commands itself and never claims to control what a command runs internally. Steps whose command cannot carry plan scope fail closed instead of being emitted. Use when the user has a multi-step plan and wants the right command for each step without picking it by hand.
523. plan-orchestrate affaan-m/everything-claude-code · score 77/100 (grade C)
     Read a plan document, decompose it into steps, classify each step, and emit the ready-to-paste ECC slash command for that step, carrying the step identifier and scope in the command's own documented argument form. Generative only — never invokes commands itself and never claims to control what a command runs internally. Steps whose command cannot carry plan scope fail closed instead of being emitted. Use when the user has a multi-step plan and wants the right command for each step without picking it by hand.
524. plugin-audit alirezarezvani/claude-skills · score 77/100 (grade C)
     Comprehensive audit pipeline for skills, plugins, agents, and commands. Validates structure, quality, security, marketplace compliance, cross-platform compatibility, and ecosystem integration. Runs all built-in validation tools, invokes domain-appropriate agents for code review, and produces a pass/fail gate report. Usage: /plugin-audit <skill-path>
525. power-bi-dax-optimization github/awesome-copilot · score 77/100 (grade C)
     Comprehensive Power BI DAX formula optimization prompt for improving performance, readability, and maintainability of DAX calculations.
526. pricing-strategist alirezarezvani/claude-skills · score 77/100 (grade C)
     Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.
527. projection-patterns sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
528. prompt-for-others davidondrej/skills · score 77/100 (grade C)
     Write a prompt teammates can give their AI agents to apply a fix, upgrade, or setup change. Use only when the user explicitly invokes /prompt-for-others.
529. prompt-injection-defense sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Defend AI systems against prompt injection and indirect prompt attacks
530. pydantic-models-py sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Create Pydantic models following the multi-model pattern for clean API contracts.
531. research-summarizer alirezarezvani/claude-skills · score 77/100 (grade C)
     Structured research summarization agent skill for non-dev users. Handles academic papers, web articles, reports, and documentation. Extracts key findings, generates comparative analyses, and produces properly formatted citations. Use when: user wants to summarize a research paper, compare multiple sources, extract citations from documents, or create structured research briefs. Plugin for Claude Code, Codex, Gemini CLI, and OpenClaw.
532. review-multi-agent-orchestration sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when a supervisor, swarm, graph, planner-worker system, or parallel agent workflow needs review for task boundaries, shared state, branch joins, retries, cancellation, context handoffs, budgets, deadlocks, or human escalation before implementation or production rollout.
533. seo-aeo-orchestrator sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Runs an audit-first SEO/AEO growth workflow from project discovery through implementation, foundational content, measurement setup, deployment verification, and optional weekly monitoring.
534. session-to-skill entireio/skills · score 77/100 (grade C)
     Use when the user wants to turn one or more Entire-tracked sessions, checkpoints, or repeated agent workflows into a reusable agent skill.
535. ship-gate alirezarezvani/claude-skills · score 77/100 (grade C)
     Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Intercepts deploy commands and blocks until critical items pass. Stack-agnostic. Use for "run ship gate", "am I ready to ship", "pre-launch audit", "can I deploy", "push to production", "go live checklist", "preflight check". Not for CI/CD setup or infra provisioning.
536. skeleton-first sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Prove a data/AI/agent workflow end to end on a tiny sample, find cheap wins, then scale in cost-gated steps within budget.
537. skill-installer sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Validate and install explicitly selected local skill trees into a workspace, with full-tree Claude registration, backups and ZIP packaging.
538. sound-effects elevenlabs/skills · score 77/100 (grade C)
     Generate sound effects from text descriptions using ElevenLabs. Use when creating sound effects, generating audio textures, producing ambient sounds, cinematic impacts, UI sounds, or any audio that isn't speech. Supports looping, duration control, and prompt influence tuning.
539. tamarind K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
     Provides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.
540. todoist-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Todoist task management, projects, sections, filtering, and bulk operations via Rube MCP (Composio). Always search tools first for current schemas.
541. trl-training sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.
542. update-skills-from-changelog elevenlabs/skills · score 77/100 (grade C)
     Update ElevenLabs agent skills from a merged weekly changelog in elevenlabs-dx, then open a pull request in elevenlabs/skills. Trigger after a changelog merges to main on elevenlabs-dx, or when asked to update skills from changelog YYYY-MM-DD.
543. waypoint-bio K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
     Supports work with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretraining corpus, the Compass eight-task benchmark, or the `waypoint` CLI from the `waypoint-bio` package. Covers embedding microbiome samples, fine-tuning on taxonomic abundance data, benchmarking a checkpoint on Compass, pretraining a GPT-2 model on taxonomic abundance profiles, and converting MetaPhlAn, Kraken2, QIIME 2, or MGnify abundance tables into waypoint format.
544. webflow-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Webflow CMS collections, site publishing, page management, asset uploads, and ecommerce orders via Rube MCP (Composio). Always search tools first for current schemas.
545. workflow-builder alirezarezvani/claude-skills · score 77/100 (grade C)
     Design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool. Use when a user wants to build, create, author, scaffold, or run a custom Claude Code workflow, orchestrate sub-agents (fan-out, pipeline, loop, judge-panel), or automate a repeatable multi-step task across fresh-context agents.
546. writing-skills sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Use when creating, updating, or improving agent skills.
547. x-twitter-scraper github/awesome-copilot · score 77/100 (grade C)
     Build GitHub Copilot workflows with Xquik X API SDKs, REST endpoints, hosted Apify Actor runs, MCP tools, TweetClaw OpenClaw plugin installs, signed webhooks, tweet search, user lookup, follower exports, media actions, and agent automation.
548. zoho-crm-automation sickn33/antigravity-awesome-skills · score 77/100 (grade C)
     Automate Zoho CRM tasks via Rube MCP (Composio): create/update records, search contacts, manage leads, and convert leads. Always search tools first for current schemas.
549. agent-manager-skill sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) in an explicitly authorized workspace.
550. agent-memory-systems sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Design tenant-scoped memory, retrieval and retention for agents. Use when planning RAG, conversation history, vector stores or remembering across sessions.
551. ai-dev-jobs-mcp sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Search indexed AI and ML jobs, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP
552. ai-engineering-toolkit sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Overview of six AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
553. ai-md sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Convert human-written CLAUDE.md into AI-native structured-label format. Propose and evaluate structured-label rewrites while preserving rule meaning; benefits require measured evidence.
554. asc-app-create-ui rudrankriyam/app-store-connect-cli-skills · score 76/100 (grade C)
     Create a new App Store Connect app record via browser automation. Use when there is no public API for app creation and you need an agent to drive the New App form.
555. asc-revenuecat-catalog-sync rudrankriyam/app-store-connect-cli-skills · score 76/100 (grade C)
     Reconcile App Store Connect subscriptions and in-app purchases with RevenueCat products, entitlements, offerings, and packages using asc and RevenueCat MCP. Use when setting up or syncing subscription catalogs across ASC and RevenueCat.
556. autonomous-agent-patterns sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Design patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
557. azure-ai-document-intelligence-ts sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Extract text, tables, and structured data from documents using prebuilt and custom models.
558. azure-ai-projects-ts sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.
559. behavioral-modes sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
560. brevo-automation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Automate Brevo (formerly Sendinblue) email marketing operations through Composio's Brevo toolkit via Rube MCP.
561. chrome-devtools github/awesome-copilot · score 76/100 (grade C)
     Expert-level browser automation, debugging, and performance analysis using Chrome DevTools MCP. Use for interacting with web pages, capturing screenshots, analyzing network traffic, and profiling performance.
562. claude-devfleet affaan-m/ECC · score 76/100 (grade C)
     Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports. Use when dispatching parallel coding agents across isolated worktrees and tracking their reports.
563. claude-devfleet affaan-m/everything-claude-code · score 76/100 (grade C)
     Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports. Use when dispatching parallel coding agents across isolated worktrees and tracking their reports.
564. cmo-advisor alirezarezvani/claude-skills · score 76/100 (grade C)
     Marketing leadership for scaling companies. Brand positioning, growth model design, marketing budget allocation, and marketing org design. Use when designing brand strategy, selecting growth models (PLG vs sales-led vs community-led), allocating marketing budgets, building marketing teams, or when user mentions CMO, brand strategy, growth model, CAC, LTV, channel mix, or marketing ROI.
565. context-fundamentals sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Context is the complete state available to a language model at inference time. It includes everything the model can attend to when generating responses: system instructions, tool definitions, retrieved documents, message history, and tool outputs.
566. cs-workspace-admin alirezarezvani/claude-skills · score 76/100 (grade C)
     Google Workspace administration agent using the gws CLI. Orchestrates workspace setup, Gmail/Drive/Sheets/Calendar automation, security audits, and recipe execution. Spawn when users need Google Workspace automation, gws CLI help, or workspace administration.
567. data-structure-protocol sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Give agents persistent structural memory of a codebase — navigate dependencies, track public APIs, and understand why connections exist without re-reading the whole repo.
568. developing-genkit-js google/skills · score 76/100 (grade C)
     Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.
569. diagram-design cathrynlavery/diagram-design · score 76/100 (grade C)
     Create branded architecture, architecture delta, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, exploded axonometric, axonometric plan, Venn, pyramid/funnel, treemap and marimekko, heatmap, bar and dumbbell, waterfall, line (slopegraph, ridgeline, streamgraph, bump), Gantt and scatter charts (bubble, beeswarm), high-level, process, medallion, data flow, DP integration, DP security matrix, Sankey, fishbone, Wardley map, kanban, user journey, service blueprint, deployment, dependency graph, UML class, story map, or database schema diagrams as HTML/SVG/PNG, with .drawio, Mermaid, and .excalidraw import, plus lifecycle phase maps, block decomposition trees, and onboarding guidance.
570. docx ComposioHQ/awesome-claude-skills · score 76/100 (grade C)
     Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
571. engineering-advanced-skills alirezarezvani/claude-skills · score 76/100 (grade C)
     Index of 37 advanced engineering agent skills for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Use when browsing or choosing among the POWERFUL-tier engineering skills: agent design, RAG, MCP servers, CI/CD, database design, observability, security auditing, changelog/release automation, reliability (SLO/chaos/flags/operators), platform ops.
572. engineering-skills alirezarezvani/claude-skills · score 76/100 (grade C)
     Index of the engineering-team skills bundle for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. Architecture, frontend, backend, QA, DevOps, security, AI/ML, data engineering, Playwright, Stripe, AWS, MS365 (stdlib-only Python tools). Use when browsing or choosing among engineering-team role skills — load only the one specialist SKILL.md you need, never bulk-load the bundle.
573. flowstudio-power-automate-build github/awesome-copilot · score 76/100 (grade C)
     Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Your agent constructs flow definitions, wires connections, deploys, and tests — all via MCP without opening the portal. Load this skill when asked to: create a flow, build a new flow, deploy a flow definition, scaffold a Power Automate workflow, construct a flow JSON, update an existing flow's actions, patch a flow definition, add actions to a flow, wire up connections, or generate a workflow definition from scratch. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app
574. folklore-variant-evidence K-Dense-AI/claude-scientific-skills · score 76/100 (grade C)
     Retrieves ClinGen gene-disease validity assertions for a public gene or disease, and reviews source-linked public evidence and literature for one supported GRCh38 germline nuclear SNV or simple indel through Folklore Clinical Variant Interpretation MCP. Used when a scientific agent must branch deterministically on resolved, ambiguous, not-found, invalid, unsupported, or unavailable variant outcomes; chain a resolved public variant into related literature or publication details; or preserve evidence provenance without accepting patient, phenotype, family, segregation, or private case data.
575. framework-migration-legacy-modernize sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Orchestrate a comprehensive legacy system modernization using the strangler fig pattern, enabling gradual replacement of outdated components while maintaining continuous business operations through ex
576. freshdesk-automation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Automate Freshdesk helpdesk operations including tickets, contacts, companies, notes, and replies via Rube MCP (Composio). Always search tools first for current schemas.
577. geo-audit sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Full website GEO+SEO audit with parallel subagent delegation.
578. google-admin-automation ComposioHQ/awesome-claude-skills · score 76/100 (grade C)
     Automate Google Workspace Admin tasks via Rube MCP (Composio): manage users, groups, memberships, suspend accounts, create users, add aliases. Always search tools first for current schemas.
579. googletasks-automation ComposioHQ/awesome-claude-skills · score 76/100 (grade C)
     Automate Google Tasks via Rube MCP (Composio): create, list, update, delete, move, and bulk-insert tasks and task lists. Always search tools first for current schemas.
580. handoff sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Compact the current conversation into a handoff document for another agent to pick up.
581. harness-engineering github/awesome-copilot · score 76/100 (grade C)
     Adopt repository-level harness engineering for coding agents. Use when a user wants to prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.
582. hugging-face-evaluation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
583. hugging-science K-Dense-AI/claude-scientific-skills · score 76/100 (grade C)
     Discovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.
584. litreview alirezarezvani/claude-skills · score 76/100 (grade C)
     Searches academic literature through free, keyless PubMed and OpenAlex APIs, optionally augments results with Consensus MCP when connected, builds a PICO, SPIDER, decomposition, or hybrid search plan, and produces a formatted Word research-orientation guide. Uses brief intake and post-reconnaissance checkpoints to confirm the framework, sub-areas, and depth (5, 10, or 20 queries) before spending the search budget. The output is a launching pad, not a finished review. Use when the user requests a literature review, starts a paper or literature-oriented research project, or needs structured research on a topic. Do NOT use for a single paper lookup or a quick paper list; use a plain PubMed, OpenAlex, or Consensus query instead.
585. llm-cost-optimization sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Reduce LLM API and infrastructure costs through model selection, prompt
586. llm-structured-output sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
587. m365-agents-ts sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Microsoft 365 Agents SDK for TypeScript/Node.js.
588. mailchimp-automation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Automate Mailchimp email marketing including campaigns, audiences, subscribers, segments, and analytics via Rube MCP (Composio). Always search tools first for current schemas.
589. mantis-architecture google/mantis · score 76/100 (grade C)
     Synthesizes raw learnings and codebase analysis into an interlinked Markdown Knowledge Base (KB). Use at the beginning of a loop to build or update architecture.md, entities, and vulnerabilities. Don't use for generating threat models or formulating execution plans.
590. mcp-builder anthropics/skills · score 76/100 (grade C)
     Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
591. mcp-release-qa github/awesome-copilot · score 76/100 (grade C)
     Verify an MCP server before release by exercising a real protocol session, comparing runtime capabilities with source and documentation, testing failure paths, and recording reproducible evidence. Use when shipping or reviewing an MCP server, tool, resource, prompt, catalog, or install path.
592. mesh-memory sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.
593. microsoft-skill-creator github/awesome-copilot · score 76/100 (grade C)
     Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.
594. ml-pipeline-workflow sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Complete end-to-end MLOps pipeline orchestration from data preparation through model deployment.
595. mle-workflow affaan-m/ECC · score 76/100 (grade C)
     Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
596. mle-workflow affaan-m/everything-claude-code · score 76/100 (grade C)
     Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
597. mmx-cli sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Use mmx to generate text, images, video, speech, and music via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, perform web search, or manage MiniMax API resources from the terminal.
598. molykit sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     CRITICAL: Use for MolyKit AI chat toolkit. Triggers on: BotClient, OpenAI, SSE streaming, AI chat, molykit, PlatformSend, spawn(), ThreadToken, cross-platform async, Chat widget, Messages, PromptInput, Avatar, LLM
599. phoenix-tracing github/awesome-copilot · score 76/100 (grade C)
     OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
600. pilot-protocol sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Give an AI agent a permanent network address, encrypted P2P messaging, and an installable app store via Pilot Protocol
601. pipecat-friday-agent sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Build a low-latency, Iron Man-inspired tactical voice assistant (F.R.I.D.A.Y.) using Pipecat, Gemini, and OpenAI.
602. podcast-generation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Generate real audio narratives from text content using Azure OpenAI's Realtime API.
603. project-development sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     This skill covers the principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development.
604. promote alirezarezvani/claude-skills · score 76/100 (grade C)
     Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.
605. prompt-governance alirezarezvani/claude-skills · score 76/100 (grade C)
     Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production AI features. Triggers: 'manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline'. NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design (use rag-architect). NOT for LLM cost reduction (use llm-cost-optimizer).
606. quit-sponsor sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Helps an AI agent provide non-judgmental, evidence-informed quit-smoking support with user-consented tracking, craving check-ins, and escalation to human or clinical help. Not medical care.
607. rowan K-Dense-AI/claude-scientific-skills · score 76/100 (grade C)
     Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
608. scenario-war-room alirezarezvani/claude-skills · score 76/100 (grade C)
     Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all business functions simultaneously. Use when facing complex risk scenarios, strategic decisions with major downside, or when the user asks 'what if X AND Y both happen?'
609. scheduler warpdotdev/oz-skills · score 76/100 (grade C)
     Schedule on-device reminders and local actions only. Use this skill to set personal reminders or run lightweight, local tasks at a specific time or interval (e.g., notifications, local scripts), on the user's computer or with platforms like Slack. Do NOT use for scheduling cloud agents, background agentic jobs, or Oz-managed workflows.
610. sendblue-notify sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Text the user's phone when a long-running task, agent turn, or scheduled job finishes — via @sendblue/cli for outbound, optionally wired to a Claude Code Stop hook for automatic fire.
611. skill-developer sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Comprehensive guide for creating and managing skills in Claude Code with auto-activation system, using an illustrative custom hook architecture and concise progressive disclosure and progressive disclosure pattern.
612. skill-doctor alirezarezvani/claude-skills · score 76/100 (grade C)
     Use when the user wants their agent setup graded from real conversation history, asks which installed skills are actually working, or wants evidence-backed skill edits — scores recent local Claude Code / Codex sessions against efficiency and code-quality rubrics, then drafts skill changes gated by a deterministic aggregator and renders one local shareable report.
613. skill-tester alirezarezvani/claude-skills · score 76/100 (grade C)
     Validate, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script testing (syntax + imports + runtime + output format), multi-dimensional quality scoring with letter grades and tier classification (BASIC/STANDARD/POWERFUL). Use when authoring a new skill, auditing existing skills for tier promotion, setting up pre-commit hooks for skill quality, or integrating skill QA into CI.
614. statistical-power K-Dense-AI/claude-scientific-skills · score 76/100 (grade C)
     Calculates sample sizes and statistical power for study planning. Applies when someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for complex designs — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Also handles requests that only mention an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.
615. statsmodels sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.
616. stripe-automation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Automate Stripe tasks via Rube MCP (Composio): customers, charges, subscriptions, invoices, products, refunds. Always search tools first for current schemas.
617. transformers-js sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript.
618. trello-automation sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Automate Trello boards, cards, and workflows via Rube MCP (Composio). Create cards, manage lists, assign members, and search across boards programmatically.
619. varlock sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Secure-by-default environment variable management for Claude Code sessions.
620. voice-ai-engine-development sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support
621. weather-model-data-fetching sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Retrieve numerical weather prediction data from public AWS S3 and HTTP archives using GRIB2 inventories, byte ranges, Herbie, provider fallbacks, and verified caching.
622. workflow-orchestration-patterns sickn33/antigravity-awesome-skills · score 76/100 (grade C)
     Master workflow orchestration architecture with Temporal, covering fundamental design decisions, resilience patterns, and best practices for building reliable distributed systems.
623. accesslint-audit sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Find and fix WCAG 2.2 accessibility issues. Two modes — report (sweep a codebase or page, produce a prioritized written report, no edits) and fix (audit→edit→verify loop on a target). Prefers direct-CDP live-DOM auditing; falls back to a browser-MCP composition or HTML-string audits.
624. agent-qa-result-triage sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.
625. agent-skill-stack github/awesome-copilot · score 75/100 (grade C)
     Find, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.
626. agentfolio sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.
627. ai-security alirezarezvani/claude-skills · score 75/100 (grade C)
     Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.
628. andreessen alirezarezvani/claude-skills · score 75/100 (grade C)
     Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit; bias to build over deliberate. Use when the user says 'andreessen', 'pmarca mode', 'should I build this', 'is there a market', 'are we at product/market fit', 'pmf check', 'pressure-test this idea', 'be brutal about this venture', 'market-first take', or wants a no-disclaimers, no-hedging, confidence-leveled verdict on whether something is worth pursuing. Also provides the 3x5-card + Anti-Todo personal productivity routine. Runs on a fixed anti-sycophancy operating prompt: leads with the strongest counterargument, never validates premises, uses explicit confidence levels, never apologizes for disagreeing. Not for polite brainstorming — this skill exists to tell you the market is dead when it is.
629. archify-tuning tt-a1i/archify · score 75/100 (grade C)
     Improve Archify diagram accuracy, visual quality and complete authoring speed with fewer repairs. Use for generation experiments or evaluating changes to layout, routing, diagnostics, authoring instructions and acceptance rules against actual diagrams and agent traces.
630. avalonia-viewmodels-zafiro sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Optimal ViewModel and Wizard creation patterns for Avalonia using Zafiro and ReactiveUI.
631. azure-ai-agents-persistent-java sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
632. azure-cosmos-java sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive patterns.
633. bigquery-udfs google/skills · score 75/100 (grade C)
     Creates, deploys, and troubleshoots BigQuery User-Defined Functions (UDFs) and Remote Functions across SQL, JavaScript, Python, and Cloud Run endpoints. Use when writing custom scalar or aggregate functions in BigQuery, installing PyPI packages or Cloud Storage libraries in a Python or JavaScript UDF, or calling Google Cloud and external APIs from a Python UDF (WITH CONNECTION) or Remote Function. Don't use for standard BigQuery table/dataset CRUD (use bigquery-basics), DataFrames client workflows (use bigquery-bigframes), or BigQuery ML models (use bigquery-ai-ml).
634. bio-workflows-riboseq-pipeline GPTomics/bioSkills · score 75/100 (grade C)
     End-to-end Ribo-seq analysis from FASTQ through periodicity QC, P-site calibration, ORF detection, translation efficiency, and stalling. Use when orchestrating a full ribosome profiling pipeline and deciding harvest/dedup/alignment options and which downstream analyses the library can support.
635. browser-testing-with-devtools addyosmani/agent-skills · score 75/100 (grade C)
     Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
636. claude-api anthropics/skills · score 75/100 (grade C)
     Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
637. claude-win11-speckit-update-skill sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Review updates to GitHub SpecKit on Windows 11 with PowerShell, preserving local templates and customizations
638. cobrapy K-Dense-AI/claude-scientific-skills · score 75/100 (grade C)
     Performs constraint-based metabolic modeling with COBRApy, including FBA, pFBA, FVA, gene knockouts, flux sampling, growth media, production envelopes, gap filling, and SBML model validation for systems biology and metabolic engineering.
639. commercial-skills alirezarezvani/claude-skills · score 75/100 (grade C)
     Use when reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on "review this deal", "should we discount", "pricing model", "partner economics", "RFP response", "bookings forecast", "channel mix". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth (sales execution) and c-level-advisor/cro-advisor (strategic CRO judgment).
640. competitor-ad-intelligence github/awesome-copilot · score 75/100 (grade C)
     Use this skill when the user asks to analyze, tear down, or reverse-engineer a competitor''s paid ads. Trigger for prompts like "what ads is [competitor] running", "tear down their ad strategy", "competitor ad analysis", "find ad angles we haven''t tried", or "reverse-engineer their paid funnel". Do not trigger for organic/SEO competitor research or website positioning analysis.
641. context-window-management sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Strategies for managing LLM context windows including
642. council-multi-model affaan-m/ECC · score 75/100 (grade C)
     Add one optional external Codex critique after the existing council has produced a decision draft. Use when an ambiguous, high-consequence decision would benefit from a separate model invocation's attempt to break the synthesis. Requires explicit consent before sending the compact draft and disagreement to OpenAI, labels same-provider reviews honestly, and marks the review absent when the adapter is unavailable.
643. council-multi-model affaan-m/everything-claude-code · score 75/100 (grade C)
     Add one optional external Codex critique after the existing council has produced a decision draft. Use when an ambiguous, high-consequence decision would benefit from a separate model invocation's attempt to break the synthesis. Requires explicit consent before sending the compact draft and disagreement to OpenAI, labels same-provider reviews honestly, and marks the review absent when the adapter is unavailable.
644. cs-product-strategist alirezarezvani/claude-skills · score 75/100 (grade C)
     Product strategy agent for quarterly OKR planning, competitive landscape analysis, product vision development, and strategy pivot evaluation. Use when the question is direction rather than delivery — e.g., cascading company OKRs into product-team objectives for next quarter, or running a competitive teardown to decide whether to enter an adjacent market.
645. cs-project-manager alirezarezvani/claude-skills · score 75/100 (grade C)
     Project Manager agent for sprint planning, Jira/Confluence workflows, Scrum ceremonies, and stakeholder reporting. Orchestrates project-management skills. Use when running delivery operations — e.g., planning a sprint with capacity and carry-over math in Jira, or assembling a portfolio health report for stakeholders from ticket and velocity data.
646. debate-review sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Two-model debate review of a GitHub PR, GitLab MR, Azure DevOps PR, or
647. dynamic-workflow-mode affaan-m/ECC · score 75/100 (grade C)
     Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses. Use when building a task-local harness, adding eval gates, or extracting a reusable skill from ad-hoc work.
648. dynamic-workflow-mode affaan-m/everything-claude-code · score 75/100 (grade C)
     Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses. Use when building a task-local harness, adding eval gates, or extracting a reusable skill from ad-hoc work.
649. ecc-tools-cost-audit affaan-m/ECC · score 75/100 (grade C)
     Evidence-first ECC Tools burn and billing audit workflow. Use when investigating runaway PR creation, quota bypass, premium-model leakage, duplicate jobs, or GitHub App cost spikes in the ECC Tools repo.
650. ecc-tools-cost-audit affaan-m/everything-claude-code · score 75/100 (grade C)
     Evidence-first ECC Tools burn and billing audit workflow. Use when investigating runaway PR creation, quota bypass, premium-model leakage, duplicate jobs, or GitHub App cost spikes in the ECC Tools repo.
651. efcore-d2-db-diagram github/awesome-copilot · score 75/100 (grade C)
     Generate D2 database diagrams from Entity Framework Core models. USE FOR: EF Core database diagram, Entity Framework Core ERD, DbContext diagram, C# entity relationship diagram, PostgreSQL schema visualization, generate .d2 file from EF Core entities, Fluent API mapping diagram, migrations-based database diagram, table relationships, owned types, many-to-many join tables, indexes and constraints. DO NOT USE FOR: runtime debugging, database migration execution, schema deployment, SQL performance tuning, or draw.io diagrams.
652. fal-generate sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Generate images and videos using fal.ai AI models
653. flowstudio-power-automate-debug github/awesome-copilot · score 75/100 (grade C)
     Debug failing Power Automate cloud flows using the FlowStudio MCP server. The Graph API only shows top-level status codes. This skill gives your agent action-level inputs and outputs to find the actual root cause. Load this skill when asked to: debug a flow, investigate a failed run, why is this flow failing, inspect action outputs, find the root cause of a flow error, fix a broken Power Automate flow, diagnose a timeout, trace a DynamicOperationRequestFailure, check connector auth errors, read error details from a run, or troubleshoot expression failures. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app
654. foundry-agent-sync github/awesome-copilot · score 75/100 (grade C)
     Create and synchronize prompt-based AI agents directly within Azure AI Foundry via REST API, from a local JSON manifest. Unlike scaffolding skills that only generate local code, this skill registers agents in the Foundry service itself — making them immediately available for invocation. Use when the user asks to create agents in Foundry, sync, deploy, register, or push agents to Foundry, update agent instructions, or scaffold the manifest and sync script for a new repository. Triggers: 'create agent in foundry', 'sync foundry agents', 'deploy agents to foundry', 'register agents in foundry', 'push agents', 'create foundry agent manifest', 'scaffold agent sync'.
655. github-issues github/awesome-copilot · score 75/100 (grade C)
     Create, update, and manage GitHub issues using MCP tools. Use this skill when users want to create bug reports, feature requests, or task issues, update existing issues, add labels/assignees/milestones, manage repository labels, set issue fields (dates, priority, custom fields), set issue types, manage issue workflows, link issues, add dependencies, or track blocked-by/blocking relationships. Triggers on requests like "create an issue", "file a bug", "request a feature", "update issue X", "set the priority", "set the start date", "create a label", "rename a label", "list repo labels", "link issues", "add dependency", "blocked by", "blocking", or any GitHub issue management task.
656. global-chat-agent-discovery sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Discover and compare MCP servers and AI agents using Global Chat's cross-protocol directory and MCP server.
657. go-mcp-server-generator github/awesome-copilot · score 75/100 (grade C)
     Generate a complete Go MCP server project with proper structure, dependencies, and implementation using the official github.com/modelcontextprotocol/go-sdk.
658. google-search-console-automation ComposioHQ/awesome-claude-skills · score 75/100 (grade C)
     Automate Google Search Console tasks via Rube MCP (Composio): query search analytics, list sites, inspect URLs, submit sitemaps, monitor search performance. Always search tools first for current schemas.
659. googleads-automation ComposioHQ/awesome-claude-skills · score 75/100 (grade C)
     Automate Google Ads analytics tasks via Rube MCP (Composio): list Google Ads links, run GA4 reports, check compatibility, list properties and accounts. Always search tools first for current schemas.
660. googledocs-automation ComposioHQ/awesome-claude-skills · score 75/100 (grade C)
     Automate Google Docs tasks via Rube MCP (Composio): create, edit, search, export, copy, and update documents. Always search tools first for current schemas.
661. googlephotos-automation ComposioHQ/awesome-claude-skills · score 75/100 (grade C)
     Automate Google Photos tasks via Rube MCP (Composio): upload media, manage albums, search photos, batch add items, create and update albums. Always search tools first for current schemas.
662. handoff davidondrej/skills · score 75/100 (grade C)
     Capture session context for a fresh agent. Use for handoffs, context limits, switching focus, ending sessions, or splitting work across sessions.
663. hubspot-automation sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Automate HubSpot CRM operations (contacts, companies, deals, tickets, properties) via Rube MCP using Composio integration.
664. infinite-gratitude sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Plan and synthesize multi-perspective research; use parallel agents only when authorized and verify findings against sources.
665. lambda-lang sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Native agent-to-agent language for compact multi-agent messaging. A shared tongue agents speak directly, not a translation layer. 340+ atoms across 7 domains; 3x smaller than natural language.
666. macos-menubar-tuist-app Dimillian/Skills · score 75/100 (grade C)
     Build, refactor, or review macOS menubar apps that use Tuist and SwiftUI. Use when creating or maintaining LSUIElement menubar utilities, defining Tuist targets/manifests, implementing model-client-store-view architecture, adding script-based launch flows, or validating reliable local build/run behavior without Xcode-first workflows.
667. mailtrap-email-integration affaan-m/ECC · score 75/100 (grade C)
     Guides agents through integrating transactional email sending via Mailtrap's Email API, including sandbox testing, domain verification, and API authentication. Use when implementing email-sending features, debugging delivery issues, or setting up safe dev/staging email testing.
668. mailtrap-email-integration affaan-m/everything-claude-code · score 75/100 (grade C)
     Guides agents through integrating transactional email sending via Mailtrap's Email API, including sandbox testing, domain verification, and API authentication. Use when implementing email-sending features, debugging delivery issues, or setting up safe dev/staging email testing.
669. manifest sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Install and configure the Manifest observability plugin for your agents. Use when setting up telemetry, configuring API keys, or troubleshooting the plugin.
670. mcp-builder ComposioHQ/awesome-claude-skills · score 75/100 (grade C)
     Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
671. mcp-builder-ms sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Use this skill when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
672. mcp-dependency-review affaan-m/ECC · score 75/100 (grade C)
     Statically review MCP configuration for mutable package references before approval or CI, without executing discovered MCP servers. Use when reviewing .mcp.json, Cursor, VS Code, Claude, Windsurf, or other repo-scoped MCP config.
673. mcp-dependency-review affaan-m/everything-claude-code · score 75/100 (grade C)
     Statically review MCP configuration for mutable package references before approval or CI, without executing discovered MCP servers. Use when reviewing .mcp.json, Cursor, VS Code, Claude, Windsurf, or other repo-scoped MCP config.
674. ml-engineer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.
675. mlops-engineer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools.
676. not-a-vibe-coder sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Turns vague prompts into 8 structured planning files for brand new projects. DO NOT use on existing codebases.
677. openrouter davidondrej/skills · score 75/100 (grade C)
     Design, build, debug, and optimize OpenRouter API integrations. Use for any OpenRouter API work, including models, reasoning, routing, media, tools, structured output, cost, or performance.
678. phylogenetics K-Dense-AI/claude-scientific-skills · score 75/100 (grade C)
     Builds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein families, and cautiously interpreted dated phylogenies.
679. polis-protocol-a-self-optimizing-city-of-agents sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Polis Protocol: A Self-Optimizing City of Agents
680. prompt-caching sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Caching strategies for LLM prompts including Anthropic prompt
681. prompt-engineering-patterns sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
682. santa-method affaan-m/ECC · score 75/100 (grade C)
     Multi-agent adversarial verification: two independent reviewers with the same rubric must both pass before output ships, with a fix-and-re-review convergence loop and human escalation cap. Use when gating publishing, production deploys, compliance or brand-sensitive content, or hallucination-prone claims before they ship.
683. santa-method affaan-m/everything-claude-code · score 75/100 (grade C)
     Multi-agent adversarial verification: two independent reviewers with the same rubric must both pass before output ships, with a fix-and-re-review convergence loop and human escalation cap. Use when gating publishing, production deploys, compliance or brand-sensitive content, or hallucination-prone claims before they ship.
684. skill-creator anthropics/financial-services · score 75/100 (grade C)
     Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
685. skill-optimizer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Diagnose and optimize Agent Skills (SKILL.md) with real session data and research-backed static analysis. Works with Claude Code, Codex, and any Agent Skills-compatible agent.
686. snowflake-development sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks, Snowpipe), Cortex AI functions, Cortex Agents, Snowpark Python, dbt integration, performance tuning, and security hardening.
687. subagent-driven-development sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Use when executing implementation plans with independent tasks in the current session
688. superpowers-lab sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Evaluate experimental Claude workflow skills in an isolated lab with reproducible tasks, observed results, and explicit adoption criteria.
689. team-agent-orchestration affaan-m/ECC · score 75/100 (grade C)
     Run team-based orchestration for agent squads: work items with owners and scope, agent Kanban state, branch isolation, control pane visibility, and merge gates. Use when coordinating multiple agents in parallel across branches or worktrees — multi-agent fan-out, agent Kanban, squad coordination, or merging agent output into one product.
690. team-agent-orchestration affaan-m/everything-claude-code · score 75/100 (grade C)
     Run team-based orchestration for agent squads: work items with owners and scope, agent Kanban state, branch isolation, control pane visibility, and merge gates. Use when coordinating multiple agents in parallel across branches or worktrees — multi-agent fan-out, agent Kanban, squad coordination, or merging agent output into one product.
691. temporal-python-pro sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment.
692. unified-memory affaan-m/ECC · score 75/100 (grade C)
     Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.
693. unified-memory affaan-m/everything-claude-code · score 75/100 (grade C)
     Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.
694. vision-analysis MiniMax-AI/skills · score 75/100 (grade C)
     Analyze, describe, and extract information from images using the MiniMax vision MCP tool. Use when: user shares an image file path or URL (any message containing .jpg, .jpeg, .png, .gif, .webp, .bmp, or .svg file extension) or uses any of these words/phrases near an image: "analyze", "analyse", "describe", "explain", "understand", "look at", "review", "extract text", "OCR", "what is in", "what's in", "read this image", "see this image", "tell me about", "explain this", "interpret this", in connection with an image, screenshot, diagram, chart, mockup, wireframe, or photo. Also triggers for: UI mockup review, wireframe analysis, design critique, data extraction from charts, object detection, person/animal/activity identification. Triggers: any message with an image file extension (jpg, jpeg, png, gif, webp, bmp, svg), or any request to analyze/describ/understand/review/extract text from an image, screenshot, diagram, chart, photo, mockup, or wireframe.
695. xvary-stock-research sickn33/antigravity-awesome-skills · score 75/100 (grade C)
     Thesis-driven equity analysis from public SEC EDGAR and market data; /analyze, /score, /compare workflows with bundled Python tools (Claude Code, Cursor, Codex).
696. agent-framework-azure-ai-py sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.
697. agent-owasp-compliance github/awesome-copilot · score 74/100 (grade C)
     Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
698. agent-platform-alert-configuration google/skills · score 74/100 (grade C)
     Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.
699. agent-platform-deploy google/skills · score 74/100 (grade C)
     Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for running model evaluations (use `agent-platform-eval-flywheel` skill).
700. agent-platform-endpoint-management google/skills · score 74/100 (grade C)
     Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.
701. agent-runtime-gateway-smoke-test affaan-m/ECC · score 74/100 (grade C)
     Verify a local agent API, temporary gateway tunnel, and remote sandbox callback with a tool-free task, then restore the original app connection.
702. agent-runtime-gateway-smoke-test affaan-m/everything-claude-code · score 74/100 (grade C)
     Verify a local agent API, temporary gateway tunnel, and remote sandbox callback with a tool-free task, then restore the original app connection.
703. agentflow sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and recoverable pipeline design.
704. agentic-actions-auditor sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines.
705. ai-ml sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
706. analyze-project sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and recommends prompt and workflow improvements.
707. anthropic_administrator-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Anthropic Admin tasks via Rube MCP (Composio): API keys, usage, workspaces, and organization management. Always search tools first for current schemas.
708. app-builder sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.
709. arbor K-Dense-AI/claude-scientific-skills · score 74/100 (grade C)
     Applies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization. Uses persistent hypotheses, isolated experiments, evidence propagation and held-out candidate comparison for multi-experiment research runs. Includes a standard-library state manager and guidance for the RUC-NLPIR Arbor CLI.
710. arize-ai-provider-integration github/awesome-copilot · score 74/100 (grade C)
     Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
711. arize-prompt-optimization github/awesome-copilot · score 74/100 (grade C)
     Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.
712. auri-core sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Auri: assistente de voz inteligente (Alexa + modelo Claude configurado e verificado). Visao do produto, persona Vitoria Neural, stack AWS, modelo Free/Pro/Business/Enterprise, roadmap 4 fases, GTM, north star WAC e analise competitiva.
713. autonomous-agent-harness affaan-m/ECC · score 74/100 (grade C)
     Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
714. autonomous-agent-harness affaan-m/everything-claude-code · score 74/100 (grade C)
     Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
715. autonomous-agents sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Autonomous agents are AI systems that can independently decompose
716. azure-ai-ml-py sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
717. bio-outlier-splicing-detection GPTomics/bioSkills · score 74/100 (grade C)
     Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-multinomial outlier mode of LeafCutter for annotation-free junctions), and DROP (Snakemake pipeline integrating FRASER2 + OUTRIDER + monoallelic expression for clinical diagnostics). The statistical model is fundamentally different from differential splicing — single-sample-vs-cohort outlier detection rather than two-group comparison. Standard tool in EU rare-disease (Solve-RD) and NIH UDN programs. Use when applying RNA-seq to undiagnosed Mendelian disease, validating predicted splice variants in clinical samples, or detecting cryptic splicing in disease tissue.
718. bio-phylo-distance-calculations GPTomics/bioSkills · score 74/100 (grade C)
     Build model-corrected evolutionary distance matrices and distance trees (NJ, BIONJ, FastME, UPGMA) with Biopython Bio.Phylo plus R ape/phangorn/FastME. Covers why a distance is a model-corrected estimate of substitutions per site that undercounts raw because of multiple/back/parallel hits (saturation); why the matrix discards the per-site information ML keeps; the LogDet/paralinear fix for compositional heterogeneity; the UPGMA molecular-clock trap; and the Bio.Phylo landmine that DistanceCalculator offers only identity/matrix distances, not JC/K80/TN93. Use when computing a distance matrix, building a fast NJ/FastME tree, seeding an ML search, barcoding, or testing substitution saturation before a deep tree. Routes ML and starting-tree work to modern-tree-inference, alignment quality to alignment/alignment-io, and tree I/O to tree-io.
719. blender-motion-state-inspection affaan-m/ECC · score 74/100 (grade C)
     Use this skill when inspecting Blender characters, rigs, poses, animation retargeting, ground contact, facing direction, or model-vs-motion alignment where screenshots alone are not enough.
720. blender-motion-state-inspection affaan-m/everything-claude-code · score 74/100 (grade C)
     Use this skill when inspecting Blender characters, rigs, poses, animation retargeting, ground contact, facing direction, or model-vs-motion alignment where screenshots alone are not enough.
721. blueprint sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Turn a one-line objective into a step-by-step construction plan any coding agent can execute cold. Each step has a self-contained context brief — a fresh agent in a new session can pick up any step without reading prior steps.
722. board-meeting alirezarezvani/claude-skills · score 74/100 (grade C)
     Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes /c-level-agents:boardroom, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.
723. capsule_crm-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Capsule CRM tasks via Rube MCP (Composio): contacts, opportunities, cases, tasks, and pipeline management. Always search tools first for current schemas.
724. chatgpt-apps openai/skills · score 74/100 (grade C)
     Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.
725. chief-data-officer-advisor alirezarezvani/claude-skills · score 74/100 (grade C)
     Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy), B2B customer-data-as-asset valuation and M&A readiness, data team org evolution. Use when deciding whether to train models on customer data, choosing data architecture, valuing data for fundraising or M&A, sequencing data hires, or when user mentions CDO, chief data officer, data strategy, data mesh, lakehouse, training data, data product, data monetization, or customer data asset. NOT a tactical data engineering skill — strategic decisions only.
726. codebase-memory-mcp github/awesome-copilot · score 74/100 (grade C)
     Use when exploring unfamiliar code, mapping architecture, finding symbols or relationships, tracing callers, callees, data flow or dependencies, assessing impact, auditing dead or complex code, or handling explicit Codebase Memory requests. Otherwise skip tasks confined to a supplied known file, tiny one-file check, exact literal, configuration value, error string, or non-code text.
727. codex garrytan/gstack · score 74/100 (grade C)
     OpenAI Codex CLI wrapper — three modes. (gstack)
728. collab-proof alirezarezvani/claude-skills · score 74/100 (grade C)
     Use when you want to understand what Claude contributed vs what you drove in a session. Triggers on: /collab-proof, session retrospective, ai contribution analysis, collaboration evidence, what did claude do.
729. comps-analysis anthropics/financial-services · score 74/100 (grade C)
     Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
730. configure-ecc affaan-m/ECC · score 74/100 (grade C)
     Run the conversational ECC setup wizard inside the current harness: inventory the install, collect scope (user/project/local) and hook mode (off/minimal/standard/strict) in Claude Code, use Codex's native plugin lifecycle, or install the project surface under ./.kimi-code, then preview, apply, and verify. Use when installing, updating, reconfiguring, or repairing an ECC installation, changing hook profiles, or moving ECC between install scopes.
731. configure-ecc affaan-m/everything-claude-code · score 74/100 (grade C)
     Run the conversational ECC setup wizard inside the current harness: inventory the install, collect scope (user/project/local) and hook mode (off/minimal/standard/strict) in Claude Code, use Codex's native plugin lifecycle, or install the project surface under ./.kimi-code, then preview, apply, and verify. Use when installing, updating, reconfiguring, or repairing an ECC installation, changing hook profiles, or moving ECC between install scopes.
732. conversion-tracking coreyhaines31/marketingskills · score 74/100 (grade C)
     Set up, audit, verify, or fix website conversion tracking. Use when the conversion is a form submission, booked meeting, chat, phone call, signup, or purchase; when conversions must reach Google Ads, Meta, GA4, LinkedIn, TikTok, or Microsoft Ads; when the work involves GTM tags and dataLayer events, pixels, the Conversions API (CAPI), Enhanced Conversions, server-side tagging, or gclid and fbclid capture; or when the user reports conversion problems like "conversions stopped", "double counting", "spend but no conversions", "GA4 and Google Ads don't match", or an Unverified or Inactive status. Covers lead gen and ecommerce. Always fire on confirmed success, never the submit click; verify a test conversion arrives; diagnose before changing anything; offer free and native paths alongside paid ones and disclose partner tools. For tracking plans and UTMs, see analytics. For attribution models, see attribution. For campaigns and bidding, see ads. For CRM lead-stage design, see revops.
733. cosmosdb-datamodeling github/awesome-copilot · score 74/100 (grade C)
     Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
734. data-engineering-data-driven-feature sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.
735. database-architect sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures.
736. database-designer alirezarezvani/claude-skills · score 74/100 (grade C)
     Use when the user asks to design database schemas, plan data migrations, optimize queries, choose between SQL and NoSQL, or model data relationships.
737. dev-team affaan-m/ECC · score 74/100 (grade C)
     Simulate a collaborative dev team session where multiple role-based personas (PM, Architect, Developer, QA) respond to the same problem together in one session. Use when designing a feature, reviewing a proposal, or onboarding a new initiative and you want multi-role perspective without switching agents manually.
738. dev-team affaan-m/everything-claude-code · score 74/100 (grade C)
     Simulate a collaborative dev team session where multiple role-based personas (PM, Architect, Developer, QA) respond to the same problem together in one session. Use when designing a feature, reviewing a proposal, or onboarding a new initiative and you want multi-role perspective without switching agents manually.
739. docker_hub-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Docker Hub tasks via Rube MCP (Composio): repositories, images, tags, and container registry management. Always search tools first for current schemas.
740. fillout_forms-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Fillout tasks via Rube MCP (Composio): forms, submissions, workflows, and form builder. Always search tools first for current schemas.
741. genomic-intelligence K-Dense-AI/claude-scientific-skills · score 74/100 (grade C)
     Predicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.
742. google_admin-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Admin tasks via Rube MCP (Composio): user management, org units, groups, and domain administration. Always search tools first for current schemas.
743. google_classroom-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Classroom tasks via Rube MCP (Composio): course management, assignments, student rosters, and announcements. Always search tools first for current schemas.
744. google_maps-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Maps tasks via Rube MCP (Composio): geocoding, directions, place search, and distance calculations. Always search tools first for current schemas.
745. google_search_console-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Search Console tasks via Rube MCP (Composio): search performance, URL inspection, sitemaps, and indexing status. Always search tools first for current schemas.
746. google-maps-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Maps tasks via Rube MCP (Composio): geocode addresses, search places, get directions, compute route matrices, reverse geocode, autocomplete, get place details. Always search tools first for current schemas.
747. googlemeet-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Meet tasks via Rube MCP (Composio): create Meet spaces, schedule video conferences via Calendar events, manage meeting access. Always search tools first for current schemas.
748. googlesheets-automation sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Automate Google Sheets operations (read, write, format, filter, manage spreadsheets) via Rube MCP (Composio). Read/write data, manage tabs, apply formatting, and search rows programmatically.
749. googleslides-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Google Slides tasks via Rube MCP (Composio): create presentations, add slides from Markdown, batch update, copy from templates, get thumbnails. Always search tools first for current schemas.
750. healthcare-job-search sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Find open US healthcare jobs (nursing, CNA, allied health, therapy, imaging, pharmacy, physicians) and the hourly pay employers post, via CareJobs.Now's free MCP server or JSON endpoints.
751. helm-chart-builder alirezarezvani/claude-skills · score 74/100 (grade C)
     Helm chart development agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw — chart scaffolding, values design, template patterns, dependency management, security hardening, and chart testing. Use when: user wants to create or improve Helm charts, design values.yaml files, implement template helpers, audit chart security (RBAC, network policies, pod security), manage subcharts, or run helm lint/test.
752. hookify-rules affaan-m/ECC · score 74/100 (grade C)
     Create and configure hookify rules — markdown files with YAML frontmatter that match bash, file, prompt, or stop events by regex or conditions and show warn/block messages to the agent. Use when creating a hookify rule, writing hook rule syntax, configuring hookify, or adding pattern guardrails such as blocking dangerous commands, .env edits, or debug code.
753. hookify-rules affaan-m/everything-claude-code · score 74/100 (grade C)
     Create and configure hookify rules — markdown files with YAML frontmatter that match bash, file, prompt, or stop events by regex or conditions and show warn/block messages to the agent. Use when creating a hookify rule, writing hook rule syntax, configuring hookify, or adding pattern guardrails such as blocking dangerous commands, .env edits, or debug code.
754. ida-reverse sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Reverse engineer binaries with IDA Pro: decompilation, disassembly, data-flow tracking, cross-references, and IDA MCP automation for deep static analysis of PE/ELF/Mach-O targets.
755. laravel-tdd affaan-m/ECC · score 74/100 (grade C)
     Laravel testing strategies with PHPUnit, Pest, model factories, HTTP tests, Sanctum authentication testing, mocking, and coverage. Use when writing Laravel tests with PHPUnit or Pest, or driving a Laravel feature test-first.
756. laravel-tdd affaan-m/everything-claude-code · score 74/100 (grade C)
     Laravel testing strategies with PHPUnit, Pest, model factories, HTTP tests, Sanctum authentication testing, mocking, and coverage. Use when writing Laravel tests with PHPUnit or Pest, or driving a Laravel feature test-first.
757. launch_darkly-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate LaunchDarkly tasks via Rube MCP (Composio): feature flags, environments, segments, and rollout management. Always search tools first for current schemas.
758. lemon_squeezy-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Lemon Squeezy tasks via Rube MCP (Composio): products, orders, subscriptions, checkouts, and digital sales. Always search tools first for current schemas.
759. llm-application-dev-langchain-agent sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
760. llm-evaluation sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
761. llm-security sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Authorized security assessment of LLM applications and AI agents: prompt injection, tool abuse, RAG exposure, memory poisoning, system-prompt extraction, and agent-compliance engineering per OWASP LLM/ASI Top 10.
762. loop-library alirezarezvani/claude-skills · score 74/100 (grade C)
     Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring agent workflow or automation cadence, turn an outcome into a bounded copy-ready loop, or review an existing loop for weak checks, unsafe authority, unbounded repetition, stale state, or unclear stopping behavior.
763. manage-skills sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Discover, list, create, edit, toggle, copy, move, and delete AI agent skills across 11 tools (Cursor, Claude, Agents, Windsurf, Copilot, Codex, Cline, Aider, Continue, Roo Code, Augment)
764. mantis-configure google/mantis · score 74/100 (grade C)
     Configures and validates Mantis pipeline environments, sandbox mechanisms, and AI models. Use to set up workflow.json, auto-detect host capabilities, switch between sandboxes (static-only, gvisor, microsandbox, gce), select AI models, and run fast 1-2s preflight tests. Don't use for scanning source code or running attack campaigns.
765. many_chat-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate ManyChat tasks via Rube MCP (Composio): chatbot flows, subscribers, broadcasts, and messenger automation. Always search tools first for current schemas.
766. marketing-loops coreyhaines31/marketingskills · score 74/100 (grade C)
     When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'weekly ads check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'run my SEO,' 'SEO operator,' 'daily SEO agent,' 'run my outbound,' 'AI SDR,' 'reply triage,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.
767. mcp-implementation-security-review github/awesome-copilot · score 74/100 (grade C)
     Review the implementation source code of MCP (Model Context Protocol) servers, clients, and tool handlers against a security baseline — authentication, sessions, rate limiting, input-schema validation, official-SDK usage, RCE vectors, and the OWASP MCP Top 10 — producing a report with file/line evidence. Use this skill when: - Reviewing an MCP server implementation for security before release - Checking a server against the baseline controls (MCP-01 to MCP-05) and the OWASP MCP Top 10 - Auditing tools for RCE vectors (command/code injection, unsafe deserialization, path traversal, SSTI, dependency hijacking, SSRF) - Verifying auth, session, rate-limiting, and input-validation controls on a network-exposed server - Reviewing MCP client code that handles untrusted server responses and session IDs - Requests like "review this MCP server for security" or "is my MCP server implementation secure?"
768. mcp-server-builder alirezarezvani/claude-skills · score 74/100 (grade C)
     Design and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and TypeScript support, schema validation, safe evolution. Use when exposing an existing API as an MCP server, building tool integrations for Claude or Codex or Cursor, or scaffolding an MCP project from scratch.
769. microsoft_clarity-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Microsoft Clarity tasks via Rube MCP (Composio): session recordings, heatmaps, and user behavior analytics. Always search tools first for current schemas.
770. microsoft-agent-framework github/awesome-copilot · score 74/100 (grade C)
     Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.
771. mistral_ai-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Mistral AI tasks via Rube MCP (Composio): completions, embeddings, fine-tuning, and model management. Always search tools first for current schemas.
772. music elevenlabs/skills · score 74/100 (grade C)
     Generate music using ElevenLabs Music API. Use when creating instrumental tracks, songs with lyrics, background music, jingles, or any AI-generated music composition. Supports prompt-based generation, composition plans for granular control, and detailed output with metadata.
773. nagent davidondrej/skills · score 74/100 (grade C)
     Launch a new bb worker thread with the right project, model, worktree, and task brief. Use for nagent, launching a bb session, or a standalone bb agent. Covers thread creation; use bb-cli for managing existing threads.
774. new_relic-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate New Relic tasks via Rube MCP (Composio): APM, alerts, dashboards, NRQL queries, and infrastructure monitoring. Always search tools first for current schemas.
775. onesignal_rest_api-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate OneSignal tasks via Rube MCP (Composio): push notifications, segments, templates, and messaging. Always search tools first for current schemas.
776. pair-agent garrytan/gstack · score 74/100 (grade C)
     Pair a remote AI agent with your browser. (gstack)
777. partnerships-architect alirezarezvani/claude-skills · score 74/100 (grade C)
     Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic alliance review — not technical sale enablement, not channel cost economics, not M&A.
778. paywall-upgrade-cro alirezarezvani/claude-skills · score 74/100 (grade C)
     When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.
779. pdf-conversion-router sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Use when converting a PDF into another format such as Markdown, HTML, text, JSON, DOCX, or structured notes and the agent must choose the best extraction route, settings, and cleanup strategy for maximum fidelity and readability.
780. phoenix-evals github/awesome-copilot · score 74/100 (grade C)
     Build and run evaluators for AI/LLM applications using Phoenix.
781. php-mcp-server-generator github/awesome-copilot · score 74/100 (grade C)
     Generate a complete PHP Model Context Protocol server project with tools, resources, prompts, and tests using the official PHP SDK
782. pi-agent K-Dense-AI/claude-scientific-skills · score 74/100 (grade C)
     Builds with and operates Pi, the minimal terminal coding harness. Use for installing Pi, configuring providers/models/settings/environment variables, creating Pi skills/extensions/packages/themes/prompt templates, embedding Pi through the SDK, integrating over RPC or JSON event streams, parsing sessions, running local models through the llama.cpp router, developing custom Pi providers and TUI components, or using ecosystem packages such as pi-subagents (delegation/orchestration), pi-mcp-adapter (MCP servers), pi-interview (interactive forms), and pi-web-access (web search, fetching, video understanding).
783. pinecone-rag github/awesome-copilot · score 74/100 (grade C)
     Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend. ALWAYS USE THIS SKILL when the user mentions Pinecone, wants to index documents for semantic search, build a retrieval-augmented generation system, store agent memory across sessions, implement hybrid search, or connect an LLM to a searchable knowledge base — even if they don't say "Pinecone" explicitly. Also use when the user asks about vector databases for RAG, namespace isolation for multi-tenant agents, embedding pipelines, or scaling a knowledge base beyond what local storage can handle. DO NOT use for local-only vector stores (Chroma, FAISS, pgvector) or pure keyword search with no semantic component.
784. plugin-structure Galaxy-Dawn/claude-scholar · score 74/100 (grade C)
     This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.
785. product-skills alirezarezvani/claude-skills · score 74/100 (grade C)
     Use when coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a continuous-discovery loop (Torres cadence tracker + OST linter as machine gates) or a full goal→plan→execute→verify→close run through the repo-wide agent-harness. Distinct from project-management (how to deliver vs what to build), marketing/landing (from-scratch pages), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).
786. prompt-library sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     A comprehensive collection of battle-tested prompts inspired by [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) and community best practices.
787. release-skills JimLiu/baoyu-skills · score 74/100 (grade C)
     Universal release workflow. Auto-detects version files and changelogs. Supports Node.js, Python, Rust, Claude Plugin, GitHub Releases, annotated tags, historical release backfill, and generic projects. Use when user says "release", "发布", "new version", "bump version", "push", "推送", "release notes", "GitHub Release", or "回填 Release".
788. research-prompt sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Turn vague research needs into one precise deep-research prompt with context and output criteria.
789. results-analysis Galaxy-Dawn/claude-scholar · score 74/100 (grade C)
     This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.
790. ring_central-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate RingCentral tasks via Rube MCP (Composio): calls, messages, meetings, and unified communications. Always search tools first for current schemas.
791. saga-orchestration sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Patterns for managing distributed transactions and long-running business processes.
792. secret-scanning github/awesome-copilot · score 74/100 (grade C)
     Guide for configuring and managing GitHub secret scanning, push protection, custom patterns, and secret alert remediation. For pre-commit secret scanning in AI coding agents via the GitHub MCP Server, this skill references the Advanced Security plugin (`advanced-security@copilot-plugins`). Use this skill when enabling secret scanning, setting up push protection, defining custom patterns, triaging alerts, resolving blocked pushes, or when an agent needs to scan code for secrets before committing.
793. seek-and-analyze-video sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Seek and analyze video content using Memories.ai Large Visual Memory Model for persistent video intelligence
794. share_point-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate SharePoint tasks via Rube MCP (Composio): document libraries, sites, lists, and content management. Always search tools first for current schemas.
795. similarweb_digitalrank_api-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate SimilarWeb tasks via Rube MCP (Composio): website traffic, rankings, and digital market intelligence. Always search tools first for current schemas.
796. skill-creator ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
797. skill-creator openai/skills · score 74/100 (grade C)
     Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
798. skill-creator-ms sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.
799. skill-share ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     A skill that creates new Claude skills and automatically shares them on Slack using Rube for seamless team collaboration and skill discovery.
800. speech openai/skills · score 74/100 (grade C)
     Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
801. startup-analyst sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies.
802. startup-business-analyst-financial-projections sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Create detailed 3-5 year financial model with revenue, costs, cash
803. stride-analysis-patterns sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Apply STRIDE methodology to systematically identify threats. Use when analyzing system security, conducting threat modeling sessions, or creating security documentation.
804. survey_monkey-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate SurveyMonkey tasks via Rube MCP (Composio): surveys, responses, collectors, and survey analytics. Always search tools first for current schemas.
805. test-app-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Test App tasks via Rube MCP (Composio). Always search tools first for current schemas.
806. tldr-prompt github/awesome-copilot · score 74/100 (grade C)
     Create tldr summaries for GitHub Copilot files (prompts, agents, instructions, collections), MCP servers, or documentation from URLs and queries.
807. ui-skills sickn33/antigravity-awesome-skills · score 74/100 (grade C)
     Opinionated, evolving constraints to guide agents when building interfaces
808. wave_accounting-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Wave Accounting tasks via Rube MCP (Composio): invoices, customers, payments, and small business accounting. Always search tools first for current schemas.
809. xcode-build-orchestrator AvdLee/Xcode-Build-Optimization-Agent-Skill · score 74/100 (grade C)
     Orchestrate Xcode build optimization by benchmarking first, running the specialist analysis skills, prioritizing findings, requesting explicit approval, delegating approved fixes to xcode-build-fixer, and re-benchmarking after changes. Use when a developer wants an end-to-end build optimization workflow, asks to speed up Xcode builds, wants a full build audit, or needs a recommend-first optimization pass covering compilation, project settings, and packages.
810. zoho_bigin-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Zoho Bigin tasks via Rube MCP (Composio): pipelines, contacts, companies, products, and small business CRM. Always search tools first for current schemas.
811. zoho_books-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Zoho Books tasks via Rube MCP (Composio): invoices, expenses, contacts, payments, and accounting. Always search tools first for current schemas.
812. zoho_desk-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Zoho Desk tasks via Rube MCP (Composio): tickets, contacts, agents, departments, and help desk operations. Always search tools first for current schemas.
813. zoho_inventory-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Zoho Inventory tasks via Rube MCP (Composio): items, orders, warehouses, shipments, and stock management. Always search tools first for current schemas.
814. zoho_invoice-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Zoho Invoice tasks via Rube MCP (Composio): invoices, estimates, expenses, clients, and payment tracking. Always search tools first for current schemas.
815. zoho_mail-automation ComposioHQ/awesome-claude-skills · score 74/100 (grade C)
     Automate Zoho Mail tasks via Rube MCP (Composio): email sending, folders, labels, and mailbox management. Always search tools first for current schemas.
816. acceptance-orchestrator sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
817. add-educational-comments github/awesome-copilot · score 73/100 (grade C)
     Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.
818. agent-eval affaan-m/ECC · score 73/100 (grade C)
     Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.
819. agent-eval affaan-m/everything-claude-code · score 73/100 (grade C)
     Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.
820. agent-orchestration-improve-agent sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
821. agent-platform-rag-engine-management google/skills · score 73/100 (grade C)
     Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google Workspace RAG, or other RAG products like gRAG.
822. agent-tool-builder sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Tools are how AI agents interact with the world. A well-designed
823. ai-agent-development sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
824. ai-team-orchestration github/awesome-copilot · score 73/100 (grade C)
     Bootstrap and run a lightweight multi-agent development team. Use when starting or adopting a project, planning work, coordinating implementation and optional QA, brainstorming with distinct perspectives, or preserving context across sessions.
825. alloydb-basics google/skills · score 73/100 (grade C)
     Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.
826. artifacts-builder ComposioHQ/awesome-claude-skills · score 73/100 (grade C)
     Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
827. asset-it-management sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Asset and IT register: serial, model, condition, assignee, location, purchase value, warranty expiry and return date, as CSV, SQL, JSON Schema or Notion on request. Use for asset audits.
828. audio-transcriber sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
829. autonomous-loops affaan-m/ECC · score 73/100 (grade C)
     Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems. Retained for compatibility only: when new autonomous loop guidance is needed, use continuous-agent-loop instead.
830. autonomous-loops affaan-m/everything-claude-code · score 73/100 (grade C)
     Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems. Retained for compatibility only: when new autonomous loop guidance is needed, use continuous-agent-loop instead.
831. benchmark-models garrytan/gstack · score 73/100 (grade C)
     Cross-model benchmark for gstack skills. (gstack)
832. blockrun sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     BlockRun works with Claude Code and Google Antigravity.
833. caveman-compress JuliusBrussee/caveman · score 73/100 (grade C)
     Compress a memory file such as CLAUDE.md or a todo list into caveman format to save input tokens, keeping a readable backup. Sends the file's text to the configured model provider. Trigger: /caveman-compress.
834. chief-ai-officer-advisor alirezarezvani/claude-skills · score 73/100 (grade C)
     Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
835. cirq K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
     Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
836. claude-code-expert sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Especialista profundo em Claude Code - CLI da Anthropic. Maximiza produtividade com atalhos, hooks, MCPs, configuracoes avancadas, workflows, CLAUDE.md, memoria, sub-agentes, permissoes e integracao com ecossistemas.
837. claude-monitor sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Monitor de performance do Claude Code e sistema local. Diagnostica lentidao, mede CPU/RAM/disco, verifica API latency e gera relatorios de saude do sistema.
838. code-to-prd alirezarezvani/claude-skills · score 73/100 (grade C)
     Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Use when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document page logic, analyze page fields and interactions, create a functional inventory, write requirements from an existing codebase, document API endpoints, or analyze backend routes.
839. commercial-policy alirezarezvani/claude-skills · score 73/100 (grade C)
     Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under. Covers discount matrix design (ARR band x term length x payment terms x strategic value), commercial policy design, exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces). For Head of Commercial, Head of Deal Desk, VP Sales, or RevOps at the policy-design moment — NOT per-deal application (that is deal-desk) and NOT pricing model selection (that is pricing-strategist).
840. compliance-os alirezarezvani/claude-skills · score 73/100 (grade C)
     Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE internal audits, and CONSOLIDATE evidence across multiple frameworks. Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario library? (4) Across selected frameworks, what's the unified evidence checklist with reuse map? Use when standing up a multi-framework program, planning the annual audit calendar, or preparing for certification stage 1. Does NOT replace per-framework skills (it orchestrates them).
841. computer-use-agents sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Build AI agents that interact with computers like humans do -
842. container-audit briiirussell/cybersecurity-skills · score 73/100 (grade C)
     Audit container images, Dockerfiles, and Kubernetes manifests for misconfigurations, excessive privileges, exposed secrets, and runtime risks. Use when the user mentions 'container security,' 'Docker security,' 'Dockerfile audit,' 'Kubernetes security,' 'K8s security,' 'pod security,' 'container hardening,' 'kubectl audit,' 'image scanning,' 'distroless,' 'rootless containers,' 'pod security policy,' 'pod security standards,' 'PSS,' 'network policy,' 'OPA Gatekeeper,' 'Kyverno,' 'runtime security,' or needs to review container or orchestration security.
843. context7-auto-research sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Automatically fetch latest library/framework documentation for Claude Code via Context7 API. Use when you need up-to-date documentation for libraries and frameworks or asking about React, Next.js, Prisma, or any other popular library.
844. cqrs-implementation sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
845. cs-demand-gen-specialist alirezarezvani/claude-skills · score 73/100 (grade C)
     Demand generation and acquisition-funnel specialist orchestrating the marketing-demand-acquisition, paid-ads, and email-sequence skills. Use when building or fixing the acquisition engine — e.g., comparing channel CAC against B2B SaaS benchmarks before reallocating a $40k/month budget, scoring paid-ads account health with ad_health_scorer.py before scaling spend, or designing a nurture sequence that must score 70+ on sequence_analyzer.py before launch. Covers channel mix, CAC/ROAS math, MQL→SQL workflows, attribution, and nurture design.
846. cs-product-manager alirezarezvani/claude-skills · score 73/100 (grade C)
     Product management agent for feature prioritization, customer discovery, PRD development, and roadmap planning using RICE framework. Use when a product decision needs structure and evidence — e.g., RICE-scoring a backlog of 20 feature requests before quarterly planning, or drafting a PRD from raw customer-interview notes.
847. dcf-model anthropics/financial-services · score 73/100 (grade C)
     Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.
848. deep-research alirezarezvani/claude-skills · score 73/100 (grade C)
     Run a disciplined, multi-source research investigation for a high-stakes question or decision — fan-out web search across many channels, parallel sub-agents, source triangulation (each claim backed by ≥3 independent sources), an adversarial review pass, and every source saved to its own file with verbatim quotes for reuse. Use when a low-quality answer is expensive: strategy work, comparing N products/methods/markets, validating a hypothesis with external data, or mapping how a field works. NOT for quick fact-checks (answer directly), structured 12-dimension competitor scoring (use competitive-teardown), or fast topic overviews where the decision risk is low (use the research router instead).
849. docker-expert sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     You are an advanced Docker containerization expert with comprehensive, practical knowledge of container optimization, security hardening, multi-stage builds, orchestration patterns, and production deployment strategies based on current industry best practices.
850. documentation-and-adrs addyosmani/agent-skills · score 73/100 (grade C)
     Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
851. dotnet-upgrade github/awesome-copilot · score 73/100 (grade C)
     Ready-to-use prompts for comprehensive .NET framework upgrade analysis and execution
852. e2e-testing affaan-m/ECC · score 73/100 (grade C)
     Playwright E2E testing patterns, Page Object Model, configuration, CI/CD integration, artifact management, and flaky test strategies. Use when writing Playwright tests, structuring page objects, or fixing flaky E2E runs in CI.
853. e2e-testing affaan-m/everything-claude-code · score 73/100 (grade C)
     Playwright E2E testing patterns, Page Object Model, configuration, CI/CD integration, artifact management, and flaky test strategies. Use when writing Playwright tests, structuring page objects, or fixing flaky E2E runs in CI.
854. embedding-strategies sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Guide to selecting and optimizing embedding models for vector search applications.
855. event-sourcing-architect sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use PROACTIVELY for event-sourced systems, audit trail requirements, or complex domain modeling with temporal queries.
856. fable-safe-prompt sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Rewrite allowed prompts to reduce false-positive safety triggers without bypassing policy or changing intent.
857. faf-expert sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Advanced .faf (Foundational AI-context Format) specialist. IANA-registered format, MCP server config, championship scoring, bi-directional sync.
858. fastapi-router-py sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Create FastAPI routers following established patterns with proper authentication, response models, and HTTP status codes.
859. foundation-models-on-device affaan-m/ECC · score 73/100 (grade C)
     Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+. Use when adding on-device LLM features with Apple FoundationModels on iOS 26+.
860. foundation-models-on-device affaan-m/everything-claude-code · score 73/100 (grade C)
     Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+. Use when adding on-device LLM features with Apple FoundationModels on iOS 26+.
861. game-development sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Game development orchestrator. Routes by platform, dimension, and engine fit (web 2D/3D, hybrid DOM+canvas, narrative tools). Use when starting or structuring a game project, choosing frameworks, or picking among Phaser, PixiJS, Kaplay, Canvas/WebGL, Three.js, Babylon.js, Godot, Unity, or Ink/Twine.
862. gan-style-harness affaan-m/ECC · score 73/100 (grade C)
     GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper. Use when a feature should be built autonomously through generator and evaluator iteration until it clears a quality bar.
863. gan-style-harness affaan-m/everything-claude-code · score 73/100 (grade C)
     GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper. Use when a feature should be built autonomously through generator and evaluator iteration until it clears a quality bar.
864. geo-fundamentals sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
865. git-flow-branch-creator github/awesome-copilot · score 73/100 (grade C)
     Intelligent Git Flow branch creator that analyzes git status/diff and creates appropriate branches following the nvie Git Flow branching model.
866. gke-inference google/skills · score 73/100 (grade C)
     Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers. Use when deploying GKE inference servers, configuring GKE GPU resources for inference, or deploying LLMs on GKE. Don't use for migrating existing AI workloads to GKE (use google-cloud-solution-guided-gke-ai-migration), GKE RAG with Cloud SQL/AlloyDB (use google-cloud-solution-rag-enterprise-search-gke-sqldb), or batch/HPC (use gke-batch-hpc).
867. gtm-board-and-investor-communication github/awesome-copilot · score 73/100 (grade C)
     Board meeting preparation, investor updates, and executive communication. Use when preparing board decks, writing investor updates, handling bad news with the board, structuring QBRs, or building board-level metric discipline. Includes the "Three Things" narrative model, the 4-tier metric hierarchy, and the pre-brief pattern that prevents board surprises.
868. hexagonal-architecture affaan-m/ECC · score 73/100 (grade C)
     Design, implement, and refactor Ports & Adapters systems with clear domain boundaries, dependency inversion, and testable use-case orchestration across TypeScript, Java, Kotlin, and Go services. Use when introducing or refactoring toward Ports and Adapters, or when domain logic has become entangled with I/O.
869. hexagonal-architecture affaan-m/everything-claude-code · score 73/100 (grade C)
     Design, implement, and refactor Ports & Adapters systems with clear domain boundaries, dependency inversion, and testable use-case orchestration across TypeScript, Java, Kotlin, and Go services. Use when introducing or refactoring toward Ports and Adapters, or when domain logic has become entangled with I/O.
870. initiating-coverage anthropics/financial-services · score 73/100 (grade C)
     Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
871. internal-comms alirezarezvani/claude-skills · score 73/100 (grade C)
     Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management communication — a re-org announcement, a tool rollout, a policy change, a leadership transition, a layoff, an acquisition close, or an internal product launch — and the audience is employees (not customers). Pairs Prosci ADKAR and Kotter's 8-step change model with deterministic stdlib-only Python tools to produce a sequenced touchpoint calendar, a Kotter-compliant primary announcement, an audience-segmented FAQ, and manager cascade talking points; industry-tuned via --profile {tech-startup, scaleup, enterprise, public-company, non-profit}. Triggers on "all-hands announcement", "change comms", "rollout comms", "re-org announcement", "manager talking points", "layoff comms".
872. ios-debugger-agent sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Debug the current iOS project on a booted simulator with XcodeBuildMCP.
873. ito-inference affaan-m/ECC · score 73/100 (grade C)
     Inspect the availability of model serving on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed serving manifest. Use after ito-compute has booked GPU nodes and the user asks for an OpenAI-compatible endpoint, ito-serve, hosted Kimi, or self-hosted open-weights inference. ECC implements no serving stack of its own.
874. ito-inference affaan-m/everything-claude-code · score 73/100 (grade C)
     Inspect the availability of model serving on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed serving manifest. Use after ito-compute has booked GPU nodes and the user asks for an OpenAI-compatible endpoint, ito-serve, hosted Kimi, or self-hosted open-weights inference. ECC implements no serving stack of its own.
875. karpathy-guidelines multica-ai/andrej-karpathy-skills · score 73/100 (grade C)
     Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
876. kotler-macro-analyzer sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Professional PESTEL/SWOT analysis agent based on Kotler's methodology for strategic market audits.
877. kotlin-mcp-server-generator github/awesome-copilot · score 73/100 (grade C)
     Generate a complete Kotlin MCP server project with proper structure, dependencies, and implementation using the official io.modelcontextprotocol:kotlin-sdk library.
878. lab-hardware-cad K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
     Designs custom laboratory hardware as parametric build123d models and exports fabrication artifacts as STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.
879. langfuse sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Expert in Langfuse - the open-source LLM observability platform.
880. linear-claude-skill sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Manage Linear issues, projects, and teams
881. llm-application-dev-prompt-optimize sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Improve LLM prompts using task-specific evaluation, structured instructions, and regression checks.
882. llm-ops sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.
883. malware-analysis sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Analyze suspected malware through static, dynamic, and behavioral techniques: IOC extraction, YARA/Sigma rule authoring, sandbox orchestration, and anti-analysis detection.
884. mantis-advise google/mantis · score 73/100 (grade C)
     Proactive security advisor and architectural remediation assistant for secure code development. Use to query threat models, historical vulnerability lineages, verified patch patterns, triaged false positives, and learned trajectory invariants before code edits or to generate architectural remediation plans for confirmed findings. Don't use for automated multi-pass red-team exploitation or fuzzing.
885. mantis-meta-agent google/mantis · score 73/100 (grade C)
     Acts as the persistent supervisor, launching and monitoring the automated review campaign. Use when running a long-running, continuous security review campaign that needs autonomous coordination. Don't use for executing individual review stages directly.
886. maxia sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Connect to MAXIA AI-to-AI marketplace on Solana. Discover, buy, sell AI services. Earn USDC. 13 MCP tools, A2A protocol, DeFi yields, sentiment analysis, rug detection.
887. mcp-integration Galaxy-Dawn/claude-scholar · score 73/100 (grade C)
     This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
888. migrate-to-codex openai/skills · score 73/100 (grade C)
     Migrate supported instruction files, skills, agents, and MCP config into Codex project and global files.
889. minimax-xlsx MiniMax-AI/skills · score 73/100 (grade C)
     Open, create, read, analyze, edit, or validate Excel/spreadsheet files (.xlsx, .xlsm, .csv, .tsv). Use when the user asks to create, build, modify, analyze, read, validate, or format any Excel spreadsheet, financial model, pivot table, or tabular data file. Covers: creating new xlsx from scratch, reading and analyzing existing files, editing existing xlsx with zero format loss, formula recalculation and validation, and applying professional financial formatting standards. Triggers on 'spreadsheet', 'Excel', '.xlsx', '.csv', 'pivot table', 'financial model', 'formula', or any request to produce tabular data in Excel format.
890. multi-agent-task-orchestrator sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Route tasks to specialized AI agents with anti-duplication, quality gates, and 30-minute heartbeat monitoring
891. not-human-search-mcp sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Search AI-ready websites, inspect indexed site details, verify MCP endpoints, and discover tools and APIs using the Not Human Search MCP server
892. odoo-module-developer sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Expert guide for creating custom Odoo modules. Covers __manifest__.py, model inheritance, ORM patterns, and module structure best practices.
893. phoenix-cli github/awesome-copilot · score 73/100 (grade C)
     Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique.
894. pi-custom-model sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Register custom Pi Agent model slugs so saved OpenRouter variants resolve correctly.
895. pkpd-modeling K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
     Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".
896. prisma-expert sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     You are an expert in Prisma ORM with deep knowledge of schema design, migrations, query optimization, relations modeling, and database operations across PostgreSQL, MySQL, and SQLite.
897. progressive-estimation sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Estimate AI-assisted and hybrid human+agent development work with explicit PERT assumptions and calibration feedback loops
898. quant-analyst sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage.
899. recursive-context-pruning-token-budgeting sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Optimizes AI agent performance by pruning redundant context, managing token usage, and enforcing ultra-concise, direct-to-value responses.
900. remove-bg-automation ComposioHQ/awesome-claude-skills · score 73/100 (grade C)
     Automate Remove Bg tasks via Rube MCP (Composio). Always search tools first for current schemas.
901. security-requirement-extraction sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Derive security requirements from threat models and business context. Use when translating threats into actionable requirements, creating security user stories, or building security test cases.
902. skill-creator himself65/finance-skills · score 73/100 (grade C)
     Create, improve, and evaluate agent skills (SKILL.md plus reference files). Use this skill whenever the user wants to build, scaffold, or design a new skill, improve or fix an existing skill that isn't working well, score or benchmark a skill's quality or run evals on it, or turn a repeated manual workflow into a skill ("I keep doing X manually", "can you remember how to do X", "turn this into a skill").
903. snowflake-development alirezarezvani/claude-skills · score 73/100 (grade C)
     Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowflake, or troubleshooting Snowflake errors.
904. social-orchestrator sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Orquestrador unificado de canais sociais — coordena Instagram, Telegram e WhatsApp em um unico fluxo de trabalho. Publicacao cross-channel, metricas unificadas, reutilizacao de conteudo por formato, agendamento sincronizado e gestao centralizada de campanhas em todos os canais simultaneamente.
905. sql-pro sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.
906. subagent-driven-development obra/superpowers · score 73/100 (grade C)
     Use when executing implementation plans with independent tasks in the current session
907. super-code sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Standing house style to enforce dense, correct, and idiomatic code on all coding tasks. Minimizes code bloat and agent operation overhead.
908. sync-gbrain garrytan/gstack · score 73/100 (grade C)
     Keep gbrain current with this repo's code and refresh agent search guidance in CLAUDE.md. (gstack)
909. tdd-orchestrator sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Master TDD orchestrator specializing in red-green-refactor discipline, multi-agent workflow coordination, and comprehensive test-driven development practices.
910. threejs-loaders sickn33/antigravity-awesome-skills · score 73/100 (grade C)
     Three.js asset loading - GLTF, textures, images, models, async patterns. Use when loading 3D models, textures, HDR environments, or managing loading progress.
911. token-metrics-automation ComposioHQ/awesome-claude-skills · score 73/100 (grade C)
     Automate Token Metrics tasks via Rube MCP (Composio). Always search tools first for current schemas.
912. typescript-mcp-server-generator github/awesome-copilot · score 73/100 (grade C)
     Generate a complete MCP server project in TypeScript using the MCP TypeScript SDK v2 (@modelcontextprotocol/server) with tools, resources, and proper configuration
913. typespec-create-agent github/awesome-copilot · score 73/100 (grade C)
     Generate a complete TypeSpec declarative agent with instructions, capabilities, and conversation starters for Microsoft 365 Copilot
914. verify anthropics/financial-services · score 73/100 (grade C)
     Verify changes to the claude-for-msft-365-install admin scripts and commands by driving them against an isolated fake $HOME.
915. web-artifacts-builder anthropics/skills · score 73/100 (grade C)
     Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
916. webmcpify github/awesome-copilot · score 73/100 (grade C)
     WebMCP agent skill for curated core coverage or route-by-route parity — inventory an existing web app, integrate approved tools, then inspect, verify and heal them in a real browser. Use for "webmcpify", "add WebMCP", or "expose app actions to AI agents".
917. workiq-copilot github/awesome-copilot · score 73/100 (grade C)
     Guides the Copilot CLI on how to use the WorkIQ CLI/MCP server to query Microsoft 365 Copilot data (emails, meetings, docs, Teams, people) for live context, summaries, and recommendations.
918. 007 sickn33/antigravity-awesome-skills · score 72/100 (grade C)
     Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.
919. ably-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Ably tasks via Rube MCP (Composio). Always search tools first for current schemas.
920. abstract-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Abstract tasks via Rube MCP (Composio). Always search tools first for current schemas.
921. abuselpdb-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.
922. abyssale-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Abyssale tasks via Rube MCP (Composio). Always search tools first for current schemas.
923. academic-pipeline Imbad0202/academic-research-skills · score 72/100 (grade C)
     Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로, flujo de trabajo académico, investigación a artículo, flujo completo de artículo, pipeline de investigación completa, publicación de investigación, flujo de trabajo completo del artículo.
924. accelo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Accelo tasks via Rube MCP (Composio). Always search tools first for current schemas.
925. accredible-certificates-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Accredible Certificates tasks via Rube MCP (Composio). Always search tools first for current schemas.
926. acculynx-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Acculynx tasks via Rube MCP (Composio). Always search tools first for current schemas.
927. active-campaign-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate ActiveCampaign tasks via Rube MCP (Composio). Always search tools first for current schemas.
928. addresszen-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Addresszen tasks via Rube MCP (Composio). Always search tools first for current schemas.
929. adobe-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Adobe tasks via Rube MCP (Composio). Always search tools first for current schemas.
930. adobe-illustrator-scripting github/awesome-copilot · score 72/100 (grade C)
     Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
931. adrapid-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Adrapid tasks via Rube MCP (Composio). Always search tools first for current schemas.
932. adyntel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Adyntel tasks via Rube MCP (Composio). Always search tools first for current schemas.
933. aero-workflow-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Aero Workflow tasks via Rube MCP (Composio). Always search tools first for current schemas.
934. aeroleads-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Aeroleads tasks via Rube MCP (Composio). Always search tools first for current schemas.
935. affinda-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Affinda tasks via Rube MCP (Composio). Always search tools first for current schemas.
936. affinity-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Affinity tasks via Rube MCP (Composio). Always search tools first for current schemas.
937. agencyzoom-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Agencyzoom tasks via Rube MCP (Composio). Always search tools first for current schemas.
938. agent-introspection-debugging affaan-m/ECC · score 72/100 (grade C)
     Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
939. agent-introspection-debugging affaan-m/everything-claude-code · score 72/100 (grade C)
     Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
940. agent-mail-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Agent Mail tasks via Rube MCP (Composio). Always search tools first for current schemas.
941. agent-platform-model-registry google/skills · score 72/100 (grade C)
     Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
942. agent-platform-troubleshooting google/skills · score 72/100 (grade C)
     Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP logs show permission errors. Don't use for general Google Cloud Identity and Access Management (IAM) debugging or networking issues unrelated to the Agent Platform stack.
943. agent-regression-evals alirezarezvani/claude-skills · score 72/100 (grade C)
     Use when an agent, prompt, model or tool change needs proof it did not make the agent worse — setting up a regression eval suite, deciding whether a pass-rate drop is real or noise, grading tool-call trajectories, finding flaky eval cases, or wiring an eval gate into CI that blocks the merge. Runs repeated trials, reports pass@k and pass^k, compares candidate to baseline with paired statistics, and refuses to pass a dropped case, a critical-case regression, or a forbidden tool call.
944. agenthub alirezarezvani/claude-skills · score 72/100 (grade C)
     Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.
945. agentic-os affaan-m/ECC · score 72/100 (grade C)
     Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.
946. agentic-os affaan-m/everything-claude-code · score 72/100 (grade C)
     Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.
947. agentql-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Agentql tasks via Rube MCP (Composio). Always search tools first for current schemas.
948. agenty-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Agenty tasks via Rube MCP (Composio). Always search tools first for current schemas.
949. agiled-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Agiled tasks via Rube MCP (Composio). Always search tools first for current schemas.
950. agility-cms-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Agility CMS tasks via Rube MCP (Composio). Always search tools first for current schemas.
951. ai-agents-architect sickn33/antigravity-awesome-skills · score 72/100 (grade C)
     Expert in designing and building autonomous AI agents. Masters tool
952. ai-ml-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate AI ML API tasks via Rube MCP (Composio). Always search tools first for current schemas.
953. ai-prompt-engineering-safety-review github/awesome-copilot · score 72/100 (grade C)
     Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.
954. aivoov-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Aivoov tasks via Rube MCP (Composio). Always search tools first for current schemas.
955. alchemy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Alchemy tasks via Rube MCP (Composio). Always search tools first for current schemas.
956. algodocs-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Algodocs tasks via Rube MCP (Composio). Always search tools first for current schemas.
957. algolia-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Algolia tasks via Rube MCP (Composio). Always search tools first for current schemas.
958. all-images-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate All Images AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
959. alpha-vantage-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Alpha Vantage tasks via Rube MCP (Composio). Always search tools first for current schemas.
960. altoviz-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Altoviz tasks via Rube MCP (Composio). Always search tools first for current schemas.
961. alttext-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Alttext AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
962. amara-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Amara tasks via Rube MCP (Composio). Always search tools first for current schemas.
963. amazon-alexa sickn33/antigravity-awesome-skills · score 72/100 (grade C)
     Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
964. amazon-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Amazon tasks via Rube MCP (Composio). Always search tools first for current schemas.
965. ambee-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Ambee tasks via Rube MCP (Composio). Always search tools first for current schemas.
966. ambient-weather-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Ambient Weather tasks via Rube MCP (Composio). Always search tools first for current schemas.
967. amcards-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Amcards tasks via Rube MCP (Composio). Always search tools first for current schemas.
968. anchor-browser-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Anchor Browser tasks via Rube MCP (Composio). Always search tools first for current schemas.
969. anonyflow-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Anonyflow tasks via Rube MCP (Composio). Always search tools first for current schemas.
970. anthropic-administrator-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Anthropic Admin tasks via Rube MCP (Composio). Always search tools first for current schemas.
971. apaleo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apaleo tasks via Rube MCP (Composio). Always search tools first for current schemas.
972. apex27-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apex27 tasks via Rube MCP (Composio). Always search tools first for current schemas.
973. api-bible-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate API Bible tasks via Rube MCP (Composio). Always search tools first for current schemas.
974. api-labz-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate API Labz tasks via Rube MCP (Composio). Always search tools first for current schemas.
975. api-ninjas-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate API Ninjas tasks via Rube MCP (Composio). Always search tools first for current schemas.
976. api-sports-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate API Sports tasks via Rube MCP (Composio). Always search tools first for current schemas.
977. api2pdf-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Api2pdf tasks via Rube MCP (Composio). Always search tools first for current schemas.
978. apiflash-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apiflash tasks via Rube MCP (Composio). Always search tools first for current schemas.
979. apilio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apilio tasks via Rube MCP (Composio). Always search tools first for current schemas.
980. apipie-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apipie AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
981. apitemplate-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apitemplate IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
982. apiverve-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Apiverve tasks via Rube MCP (Composio). Always search tools first for current schemas.
983. appcircle-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Appcircle tasks via Rube MCP (Composio). Always search tools first for current schemas.
984. appdrag-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Appdrag tasks via Rube MCP (Composio). Always search tools first for current schemas.
985. appointo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Appointo tasks via Rube MCP (Composio). Always search tools first for current schemas.
986. appsflyer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Appsflyer tasks via Rube MCP (Composio). Always search tools first for current schemas.
987. appveyor-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Appveyor tasks via Rube MCP (Composio). Always search tools first for current schemas.
988. aryn-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Aryn tasks via Rube MCP (Composio). Always search tools first for current schemas.
989. asc-release-flow rudrankriyam/app-store-connect-cli-skills · score 72/100 (grade C)
     Orchestrate App Store releases with asc, including staging a version, uploading or building an artifact, publishing, and submitting for review. Use when the user wants to prepare or execute a release. Keep Game Center item preparation in this skill; route other readiness failures, stuck submissions, cancellation, and retry decisions to asc-submission-health.
990. ascora-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Ascora tasks via Rube MCP (Composio). Always search tools first for current schemas.
991. asin-data-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Asin Data API tasks via Rube MCP (Composio). Always search tools first for current schemas.
992. ask-then-build davidondrej/skills · score 72/100 (grade C)
     Clarify a feature, change, or refactor through questions, then write a build prompt for another agent. Use for /ask-then-build or requests to ask questions before producing an implementation prompt.
993. aspire github/awesome-copilot · score 72/100 (grade C)
     Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.
994. astica-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Astica AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
995. async-interview-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Async Interview tasks via Rube MCP (Composio). Always search tools first for current schemas.
996. atlassian-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Atlassian tasks via Rube MCP (Composio). Always search tools first for current schemas.
997. auth0-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Auth0 tasks via Rube MCP (Composio). Always search tools first for current schemas.
998. autobound-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Autobound tasks via Rube MCP (Composio). Always search tools first for current schemas.
999. autom-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
     Automate Autom tasks via Rube MCP (Composio). Always search tools first for current schemas.
1000. automation-audit-ops affaan-m/ECC · score 72/100 (grade C)
      Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.
1001. automation-audit-ops affaan-m/everything-claude-code · score 72/100 (grade C)
      Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.
1002. axonaut-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Axonaut tasks via Rube MCP (Composio). Always search tools first for current schemas.
1003. ayrshare-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ayrshare tasks via Rube MCP (Composio). Always search tools first for current schemas.
1004. backendless-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Backendless tasks via Rube MCP (Composio). Always search tools first for current schemas.
1005. bannerbear-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bannerbear tasks via Rube MCP (Composio). Always search tools first for current schemas.
1006. bart-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bart tasks via Rube MCP (Composio). Always search tools first for current schemas.
1007. baselinker-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Baselinker tasks via Rube MCP (Composio). Always search tools first for current schemas.
1008. baserow-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Baserow tasks via Rube MCP (Composio). Always search tools first for current schemas.
1009. basin-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Basin tasks via Rube MCP (Composio). Always search tools first for current schemas.
1010. battlenet-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Battlenet tasks via Rube MCP (Composio). Always search tools first for current schemas.
1011. bdi-mental-states sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      This skill should be used when the user asks to "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration.
1012. beaconchain-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Beaconchain tasks via Rube MCP (Composio). Always search tools first for current schemas.
1013. beaconstac-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Beaconstac tasks via Rube MCP (Composio). Always search tools first for current schemas.
1014. beamer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Beamer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1015. beeminder-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Beeminder tasks via Rube MCP (Composio). Always search tools first for current schemas.
1016. bench-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bench tasks via Rube MCP (Composio). Always search tools first for current schemas.
1017. benchmark-email-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Benchmark Email tasks via Rube MCP (Composio). Always search tools first for current schemas.
1018. benzinga-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Benzinga tasks via Rube MCP (Composio). Always search tools first for current schemas.
1019. bestbuy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bestbuy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1020. better-proposals-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Better Proposals tasks via Rube MCP (Composio). Always search tools first for current schemas.
1021. better-stack-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Better Stack tasks via Rube MCP (Composio). Always search tools first for current schemas.
1022. bidsketch-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bidsketch tasks via Rube MCP (Composio). Always search tools first for current schemas.
1023. big-data-cloud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Big Data Cloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1024. bigmailer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bigmailer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1025. bigml-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bigml tasks via Rube MCP (Composio). Always search tools first for current schemas.
1026. bigpicture-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bigpicture IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1027. bio-rna-structure-covariation-analysis GPTomics/bioSkills · score 72/100 (grade C)
      Tests whether a proposed or predicted RNA secondary structure is supported by evolutionary covariation using R-scape, which scores compensatory substitutions against a phylogeny-aware null and estimates the statistical power of the alignment. Use when validating a conserved-structure claim before trusting it (the test that found no support for HOTAIR/Xist/SRA lncRNA structures); separating real covariation from phylogenetic correlation; deciding whether an alignment even has the power to test structure; or building a covariation-supported consensus (CaCoFold) to seed a covariance model or folding.
1028. bio-workflows-methylation-pipeline GPTomics/bioSkills · score 72/100 (grade C)
      Orchestrates the end-to-end bisulfite/EM-seq methylation pipeline from FASTQ to differentially methylated regions, chaining Trim Galore/fastp QC, Bismark alignment + deduplication, methylation calling, methylKit coverage-filtering/normalization, and selection-aware DMR detection (dmrseq/DSS). Use when gating the run on bisulfite conversion (lambda + pUC19 controls) BEFORE any beta value, committing the genome build + library directionality once, keeping mate-overlap deduplicated (--no_overlap), M-bias-trimming from the plot, filtering coverage before testing, choosing a count model (beta-binomial/DSS) over a bare-beta t-test, or using a region-selection-aware FDR (dmrseq/DSS) rather than raw methylKit tiles. Hands mechanism to the methylation-analysis component skills; not a re-teach of any single step.
1029. bitquery-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bitquery tasks via Rube MCP (Composio). Always search tools first for current schemas.
1030. bitwarden-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bitwarden tasks via Rube MCP (Composio). Always search tools first for current schemas.
1031. blackbaud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Blackbaud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1032. blackboard-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Blackboard tasks via Rube MCP (Composio). Always search tools first for current schemas.
1033. blocknative-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Blocknative tasks via Rube MCP (Composio). Always search tools first for current schemas.
1034. boldsign-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Boldsign tasks via Rube MCP (Composio). Always search tools first for current schemas.
1035. bolna-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bolna tasks via Rube MCP (Composio). Always search tools first for current schemas.
1036. boloforms-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Boloforms tasks via Rube MCP (Composio). Always search tools first for current schemas.
1037. bolt-iot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bolt Iot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1038. bonsai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bonsai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1039. bookingmood-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bookingmood tasks via Rube MCP (Composio). Always search tools first for current schemas.
1040. booqable-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Booqable tasks via Rube MCP (Composio). Always search tools first for current schemas.
1041. borneo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Borneo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1042. botbaba-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Botbaba tasks via Rube MCP (Composio). Always search tools first for current schemas.
1043. botpress-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Botpress tasks via Rube MCP (Composio). Always search tools first for current schemas.
1044. botsonic-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Botsonic tasks via Rube MCP (Composio). Always search tools first for current schemas.
1045. botstar-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Botstar tasks via Rube MCP (Composio). Always search tools first for current schemas.
1046. bouncer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bouncer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1047. boxhero-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Boxhero tasks via Rube MCP (Composio). Always search tools first for current schemas.
1048. brandfetch-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Brandfetch tasks via Rube MCP (Composio). Always search tools first for current schemas.
1049. breeze-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Breeze tasks via Rube MCP (Composio). Always search tools first for current schemas.
1050. breezy-hr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Breezy HR tasks via Rube MCP (Composio). Always search tools first for current schemas.
1051. brex-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Brex tasks via Rube MCP (Composio). Always search tools first for current schemas.
1052. brex-staging-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Brex Staging tasks via Rube MCP (Composio). Always search tools first for current schemas.
1053. brightdata-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Brightdata tasks via Rube MCP (Composio). Always search tools first for current schemas.
1054. brightpearl-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Brightpearl tasks via Rube MCP (Composio). Always search tools first for current schemas.
1055. brilliant-directories-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Brilliant Directories tasks via Rube MCP (Composio). Always search tools first for current schemas.
1056. browseai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Browseai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1057. browser-qa affaan-m/ECC · score 72/100 (grade C)
      Run automated post-deploy UI verification with a browser automation MCP (claude-in-chrome, Playwright, or Puppeteer): console-error and Core Web Vitals smoke checks, form and auth-flow interaction tests, screenshot visual regression across three breakpoints, and axe-core accessibility audits ending in a SHIP / DO-NOT-SHIP verdict. Use when testing a deployed feature on staging or preview, before shipping frontend changes, reviewing a frontend PR, or checking responsive layout and accessibility.
1058. browser-qa affaan-m/everything-claude-code · score 72/100 (grade C)
      Run automated post-deploy UI verification with a browser automation MCP (claude-in-chrome, Playwright, or Puppeteer): console-error and Core Web Vitals smoke checks, form and auth-flow interaction tests, screenshot visual regression across three breakpoints, and axe-core accessibility audits ending in a SHIP / DO-NOT-SHIP verdict. Use when testing a deployed feature on staging or preview, before shipping frontend changes, reviewing a frontend PR, or checking responsive layout and accessibility.
1059. browser-tool-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Browser Tool tasks via Rube MCP (Composio). Always search tools first for current schemas.
1060. browserbase-tool-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Browserbase Tool tasks via Rube MCP (Composio). Always search tools first for current schemas.
1061. browserhub-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Browserhub tasks via Rube MCP (Composio). Always search tools first for current schemas.
1062. browserless-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Browserless tasks via Rube MCP (Composio). Always search tools first for current schemas.
1063. btcpay-server-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Btcpay Server tasks via Rube MCP (Composio). Always search tools first for current schemas.
1064. bubble-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bubble tasks via Rube MCP (Composio). Always search tools first for current schemas.
1065. bugbug-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bugbug tasks via Rube MCP (Composio). Always search tools first for current schemas.
1066. bugherd-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bugherd tasks via Rube MCP (Composio). Always search tools first for current schemas.
1067. bugsnag-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bugsnag tasks via Rube MCP (Composio). Always search tools first for current schemas.
1068. buildkite-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Buildkite tasks via Rube MCP (Composio). Always search tools first for current schemas.
1069. builtwith-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Builtwith tasks via Rube MCP (Composio). Always search tools first for current schemas.
1070. bunnycdn-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Bunnycdn tasks via Rube MCP (Composio). Always search tools first for current schemas.
1071. byteforms-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Byteforms tasks via Rube MCP (Composio). Always search tools first for current schemas.
1072. c-level-agents alirezarezvani/claude-skills · score 72/100 (grade C)
      Founder-mode executive team. 13 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, GC, CDO, CAIO, CCO, VPE, Chief of Staff) and 21 /c-level-agents:* slash commands for forcing-question office hours, multi-role boardroom deliberation, strategic sprint pipeline, and meta routing. Use when the founder needs a virtual executive team, when invoking /c-level-agents:* commands, or when orchestrating multi-role decisions.
1073. cabinpanda-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cabinpanda tasks via Rube MCP (Composio). Always search tools first for current schemas.
1074. cal-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cal tasks via Rube MCP (Composio). Always search tools first for current schemas.
1075. calendarhero-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Calendarhero tasks via Rube MCP (Composio). Always search tools first for current schemas.
1076. callerapi-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Callerapi tasks via Rube MCP (Composio). Always search tools first for current schemas.
1077. callingly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Callingly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1078. callpage-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Callpage tasks via Rube MCP (Composio). Always search tools first for current schemas.
1079. campaign-cleaner-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Campaign Cleaner tasks via Rube MCP (Composio). Always search tools first for current schemas.
1080. campayn-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Campayn tasks via Rube MCP (Composio). Always search tools first for current schemas.
1081. canny-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Canny tasks via Rube MCP (Composio). Always search tools first for current schemas.
1082. canvas-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Canvas tasks via Rube MCP (Composio). Always search tools first for current schemas.
1083. carbone-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Carbone tasks via Rube MCP (Composio). Always search tools first for current schemas.
1084. cardly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cardly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1085. castingwords-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Castingwords tasks via Rube MCP (Composio). Always search tools first for current schemas.
1086. cats-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cats tasks via Rube MCP (Composio). Always search tools first for current schemas.
1087. cdr-platform-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cdr Platform tasks via Rube MCP (Composio). Always search tools first for current schemas.
1088. census-bureau-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Census Bureau tasks via Rube MCP (Composio). Always search tools first for current schemas.
1089. centralstationcrm-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Centralstationcrm tasks via Rube MCP (Composio). Always search tools first for current schemas.
1090. certifier-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Certifier tasks via Rube MCP (Composio). Always search tools first for current schemas.
1091. chaser-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Chaser tasks via Rube MCP (Composio). Always search tools first for current schemas.
1092. chatbotkit-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Chatbotkit tasks via Rube MCP (Composio). Always search tools first for current schemas.
1093. chatfai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Chatfai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1094. chatwork-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Chatwork tasks via Rube MCP (Composio). Always search tools first for current schemas.
1095. chmeetings-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Chmeetings tasks via Rube MCP (Composio). Always search tools first for current schemas.
1096. cincopa-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cincopa tasks via Rube MCP (Composio). Always search tools first for current schemas.
1097. claid-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Claid AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1098. classmarker-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Classmarker tasks via Rube MCP (Composio). Always search tools first for current schemas.
1099. claude-ally-health sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      A health assistant skill for medical information analysis, symptom tracking, and wellness guidance.
1100. clearout-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Clearout tasks via Rube MCP (Composio). Always search tools first for current schemas.
1101. clickmeeting-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Clickmeeting tasks via Rube MCP (Composio). Always search tools first for current schemas.
1102. cloudcart-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudcart tasks via Rube MCP (Composio). Always search tools first for current schemas.
1103. cloudconvert-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudconvert tasks via Rube MCP (Composio). Always search tools first for current schemas.
1104. cloudflare-api-key-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudflare API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1105. cloudflare-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudflare tasks via Rube MCP (Composio). Always search tools first for current schemas.
1106. cloudflare-browser-rendering-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudflare Browser Rendering tasks via Rube MCP (Composio). Always search tools first for current schemas.
1107. cloudlayer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudlayer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1108. cloudpress-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cloudpress tasks via Rube MCP (Composio). Always search tools first for current schemas.
1109. coassemble-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Coassemble tasks via Rube MCP (Composio). Always search tools first for current schemas.
1110. codacy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Codacy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1111. codeinterpreter-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Codeinterpreter tasks via Rube MCP (Composio). Always search tools first for current schemas.
1112. codereadr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Codereadr tasks via Rube MCP (Composio). Always search tools first for current schemas.
1113. coinmarketcal-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Coinmarketcal tasks via Rube MCP (Composio). Always search tools first for current schemas.
1114. coinmarketcap-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Coinmarketcap tasks via Rube MCP (Composio). Always search tools first for current schemas.
1115. coinranking-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Coinranking tasks via Rube MCP (Composio). Always search tools first for current schemas.
1116. college-football-data-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate College Football Data tasks via Rube MCP (Composio). Always search tools first for current schemas.
1117. command-development Galaxy-Dawn/claude-scholar · score 72/100 (grade C)
      This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
1118. composio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Composio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1119. composio-search-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Composio Search tasks via Rube MCP (Composio). Always search tools first for current schemas.
1120. connecteam-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Connecteam tasks via Rube MCP (Composio). Always search tools first for current schemas.
1121. contentful-graphql-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Contentful Graphql tasks via Rube MCP (Composio). Always search tools first for current schemas.
1122. context-engine alirezarezvani/claude-skills · score 72/100 (grade C)
      Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (older than 90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls. Use when starting any C-suite advisor session, when context looks stale or missing, or before sending company data to an external service.
1123. control-d-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Control D tasks via Rube MCP (Composio). Always search tools first for current schemas.
1124. conversation-memory sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Persistent memory systems for LLM conversations including
1125. conversion-tools-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Conversion Tools tasks via Rube MCP (Composio). Always search tools first for current schemas.
1126. convertapi-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Convertapi tasks via Rube MCP (Composio). Always search tools first for current schemas.
1127. conveyor-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Conveyor tasks via Rube MCP (Composio). Always search tools first for current schemas.
1128. convolo-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Convolo AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1129. corrently-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Corrently tasks via Rube MCP (Composio). Always search tools first for current schemas.
1130. countdown-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Countdown API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1131. coupa-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Coupa tasks via Rube MCP (Composio). Always search tools first for current schemas.
1132. craftmypdf-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Craftmypdf tasks via Rube MCP (Composio). Always search tools first for current schemas.
1133. create-readonly-db-role davidondrej/skills · score 72/100 (grade C)
      Set up read-only PostgreSQL access for agents. Use only when the user explicitly invokes /create-readonly-db-role.
1134. cro-advisor alirezarezvani/claude-skills · score 72/100 (grade C)
      Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity.
1135. crowdin-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Crowdin tasks via Rube MCP (Composio). Always search tools first for current schemas.
1136. crustdata-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Crustdata tasks via Rube MCP (Composio). Always search tools first for current schemas.
1137. cults-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cults tasks via Rube MCP (Composio). Always search tools first for current schemas.
1138. curated-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Curated tasks via Rube MCP (Composio). Always search tools first for current schemas.
1139. currents-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Currents API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1140. customgpt-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Customgpt tasks via Rube MCP (Composio). Always search tools first for current schemas.
1141. customjs-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Customjs tasks via Rube MCP (Composio). Always search tools first for current schemas.
1142. cutt-ly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Cutt Ly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1143. d2lbrightspace-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate D2lbrightspace tasks via Rube MCP (Composio). Always search tools first for current schemas.
1144. dadata-ru-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dadata Ru tasks via Rube MCP (Composio). Always search tools first for current schemas.
1145. daffy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Daffy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1146. dailybot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dailybot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1147. datagma-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Datagma tasks via Rube MCP (Composio). Always search tools first for current schemas.
1148. datapack-builder anthropics/financial-services · score 72/100 (grade C)
      Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.
1149. datarobot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Datarobot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1150. deadline-funnel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Deadline Funnel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1151. deel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Deel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1152. deepgram-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Deepgram tasks via Rube MCP (Composio). Always search tools first for current schemas.
1153. deepseek-harness-setup affaan-m/ECC · score 72/100 (grade C)
      Install and operate Everything Claude Code (ECC) on the DeepSeek Harness (DSH): native skill roots (~/.dsh/skills, .agents/skills), the @deepseek-ai/dsh-hooks-claude-code bridge for command hooks, bare-insert patch mounting, generator usage, event-support limits, and update workflow. Use when setting up ECC on DeepSeek Harness, wiring ECC hooks into a DSH profile, or debugging why ECC skills or hooks do not appear in a DSH session.
1154. deepseek-harness-setup affaan-m/everything-claude-code · score 72/100 (grade C)
      Install and operate Everything Claude Code (ECC) on the DeepSeek Harness (DSH): native skill roots (~/.dsh/skills, .agents/skills), the @deepseek-ai/dsh-hooks-claude-code bridge for command hooks, bare-insert patch mounting, generator usage, event-support limits, and update workflow. Use when setting up ECC on DeepSeek Harness, wiring ECC hooks into a DSH profile, or debugging why ECC skills or hooks do not appear in a DSH session.
1155. deerflow-maintainer-orchestrator bytedance/deer-flow · score 72/100 (grade C)
      Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance. Intended for maintainers and trusted local agents, not general contributors.
1156. delivery-gate affaan-m/ECC · score 72/100 (grade C)
      Stop hook that blocks Claude from finishing until quality checks pass. Detects rationalization patterns (surface text heuristics), stale learning logs (filesystem mtime), and low disk space. Complements self-audit by mechanically enforcing learning capture habits. Use when Claude should be mechanically blocked from declaring work finished before quality checks and learning capture actually pass.
1157. delivery-gate affaan-m/everything-claude-code · score 72/100 (grade C)
      Stop hook that blocks Claude from finishing until quality checks pass. Detects rationalization patterns (surface text heuristics), stale learning logs (filesystem mtime), and low disk space. Complements self-audit by mechanically enforcing learning capture habits. Use when Claude should be mechanically blocked from declaring work finished before quality checks and learning capture actually pass.
1158. demio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Demio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1159. desktime-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Desktime tasks via Rube MCP (Composio). Always search tools first for current schemas.
1160. detrack-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Detrack tasks via Rube MCP (Composio). Always search tools first for current schemas.
1161. developer-growth-analysis ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
1162. developing-genkit-python google/skills · score 72/100 (grade C)
      Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.
1163. dialmycalls-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dialmycalls tasks via Rube MCP (Composio). Always search tools first for current schemas.
1164. dialpad-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dialpad tasks via Rube MCP (Composio). Always search tools first for current schemas.
1165. dictionary-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dictionary API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1166. diffbot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Diffbot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1167. digicert-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Digicert tasks via Rube MCP (Composio). Always search tools first for current schemas.
1168. digital-ocean-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate DigitalOcean tasks via Rube MCP (Composio). Always search tools first for current schemas.
1169. discordbot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Discordbot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1170. dnsfilter-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dnsfilter tasks via Rube MCP (Composio). Always search tools first for current schemas.
1171. dock-certs-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dock Certs tasks via Rube MCP (Composio). Always search tools first for current schemas.
1172. docmosis-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docmosis tasks via Rube MCP (Composio). Always search tools first for current schemas.
1173. docnify-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docnify tasks via Rube MCP (Composio). Always search tools first for current schemas.
1174. docsbot-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docsbot AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1175. docsumo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docsumo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1176. docugenerate-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docugenerate tasks via Rube MCP (Composio). Always search tools first for current schemas.
1177. documenso-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Documenso tasks via Rube MCP (Composio). Always search tools first for current schemas.
1178. documint-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Documint tasks via Rube MCP (Composio). Always search tools first for current schemas.
1179. docupilot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docupilot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1180. docupost-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docupost tasks via Rube MCP (Composio). Always search tools first for current schemas.
1181. docuseal-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Docuseal tasks via Rube MCP (Composio). Always search tools first for current schemas.
1182. domain-driven-design sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Plan and route Domain-Driven Design work from strategic modeling to tactical implementation and evented architecture patterns.
1183. doppler-marketing-automation-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Doppler Marketing Automation tasks via Rube MCP (Composio). Always search tools first for current schemas.
1184. doppler-secretops-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Doppler Secretops tasks via Rube MCP (Composio). Always search tools first for current schemas.
1185. dotsimple-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dotsimple tasks via Rube MCP (Composio). Always search tools first for current schemas.
1186. dovetail-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dovetail tasks via Rube MCP (Composio). Always search tools first for current schemas.
1187. dpd2-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dpd2 tasks via Rube MCP (Composio). Always search tools first for current schemas.
1188. draftable-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Draftable tasks via Rube MCP (Composio). Always search tools first for current schemas.
1189. dreamstudio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dreamstudio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1190. drip-jobs-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Drip Jobs tasks via Rube MCP (Composio). Always search tools first for current schemas.
1191. dripcel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dripcel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1192. dromo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dromo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1193. dropbox-sign-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dropbox Sign tasks via Rube MCP (Composio). Always search tools first for current schemas.
1194. dropcontact-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dropcontact tasks via Rube MCP (Composio). Always search tools first for current schemas.
1195. dungeon-fighter-online-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Dungeon Fighter Online tasks via Rube MCP (Composio). Always search tools first for current schemas.
1196. echtpost-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Echtpost tasks via Rube MCP (Composio). Always search tools first for current schemas.
1197. elorus-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Elorus tasks via Rube MCP (Composio). Always search tools first for current schemas.
1198. emailable-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Emailable tasks via Rube MCP (Composio). Always search tools first for current schemas.
1199. emaillistverify-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Emaillistverify tasks via Rube MCP (Composio). Always search tools first for current schemas.
1200. emailoctopus-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Emailoctopus tasks via Rube MCP (Composio). Always search tools first for current schemas.
1201. emelia-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Emelia tasks via Rube MCP (Composio). Always search tools first for current schemas.
1202. encodian-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Encodian tasks via Rube MCP (Composio). Always search tools first for current schemas.
1203. endorsal-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Endorsal tasks via Rube MCP (Composio). Always search tools first for current schemas.
1204. enginemailer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Enginemailer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1205. enigma-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Enigma tasks via Rube MCP (Composio). Always search tools first for current schemas.
1206. entelligence-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Entelligence tasks via Rube MCP (Composio). Always search tools first for current schemas.
1207. entra-agent-user github/awesome-copilot · score 72/100 (grade C)
      Create Agent Users in Microsoft Entra ID from Agent Identities, enabling AI agents to act as digital workers with user identity capabilities in Microsoft 365 and Azure environments.
1208. eodhd-apis-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Eodhd Apis tasks via Rube MCP (Composio). Always search tools first for current schemas.
1209. epic-games-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Epic Games tasks via Rube MCP (Composio). Always search tools first for current schemas.
1210. esignatures-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Esignatures IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1211. espocrm-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Espocrm tasks via Rube MCP (Composio). Always search tools first for current schemas.
1212. esputnik-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Esputnik tasks via Rube MCP (Composio). Always search tools first for current schemas.
1213. etermin-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Etermin tasks via Rube MCP (Composio). Always search tools first for current schemas.
1214. etsy-shop-sales-history sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Read Etsy shop sales counters, deltas, and breakout flags from Apify Actor publicrecords/etsy-shop-velocity (MCP panel snapshot). Needs an Apify token; Actor run is billed.
1215. evenium-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Evenium tasks via Rube MCP (Composio). Always search tools first for current schemas.
1216. eventee-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Eventee tasks via Rube MCP (Composio). Always search tools first for current schemas.
1217. eventzilla-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Eventzilla tasks via Rube MCP (Composio). Always search tools first for current schemas.
1218. everhour-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Everhour tasks via Rube MCP (Composio). Always search tools first for current schemas.
1219. eversign-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Eversign tasks via Rube MCP (Composio). Always search tools first for current schemas.
1220. exa-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Exa tasks via Rube MCP (Composio). Always search tools first for current schemas.
1221. exa-search affaan-m/ECC · score 72/100 (grade C)
      Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
1222. exa-search affaan-m/everything-claude-code · score 72/100 (grade C)
      Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
1223. executing-plans obra/superpowers · score 72/100 (grade C)
      Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
1224. exist-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Exist tasks via Rube MCP (Composio). Always search tools first for current schemas.
1225. expofp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Expofp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1226. extracta-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Extracta AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1227. faceup-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Faceup tasks via Rube MCP (Composio). Always search tools first for current schemas.
1228. factorial-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Factorial tasks via Rube MCP (Composio). Always search tools first for current schemas.
1229. fal-platform sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Platform APIs for model management, pricing, and usage tracking
1230. feathery-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Feathery tasks via Rube MCP (Composio). Always search tools first for current schemas.
1231. felt-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Felt tasks via Rube MCP (Composio). Always search tools first for current schemas.
1232. fibery-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fibery tasks via Rube MCP (Composio). Always search tools first for current schemas.
1233. fidel-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fidel API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1234. files-com-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Files Com tasks via Rube MCP (Composio). Always search tools first for current schemas.
1235. fillout-forms-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fillout tasks via Rube MCP (Composio). Always search tools first for current schemas.
1236. finage-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Finage tasks via Rube MCP (Composio). Always search tools first for current schemas.
1237. finance-billing-ops affaan-m/ECC · score 72/100 (grade C)
      Evidence-first revenue, pricing, refunds, team-billing, and billing-model truth workflow for ECC. Use when the user wants a sales snapshot, pricing comparison, duplicate-charge diagnosis, or code-backed billing reality instead of generic payments advice.
1238. finance-billing-ops affaan-m/everything-claude-code · score 72/100 (grade C)
      Evidence-first revenue, pricing, refunds, team-billing, and billing-model truth workflow for ECC. Use when the user wants a sales snapshot, pricing comparison, duplicate-charge diagnosis, or code-backed billing reality instead of generic payments advice.
1239. findymail-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Findymail tasks via Rube MCP (Composio). Always search tools first for current schemas.
1240. finerworks-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Finerworks tasks via Rube MCP (Composio). Always search tools first for current schemas.
1241. fingertip-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fingertip tasks via Rube MCP (Composio). Always search tools first for current schemas.
1242. finmei-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Finmei tasks via Rube MCP (Composio). Always search tools first for current schemas.
1243. fireberry-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fireberry tasks via Rube MCP (Composio). Always search tools first for current schemas.
1244. fireflies-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fireflies tasks via Rube MCP (Composio). Always search tools first for current schemas.
1245. firmao-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Firmao tasks via Rube MCP (Composio). Always search tools first for current schemas.
1246. fitbit-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fitbit tasks via Rube MCP (Composio). Always search tools first for current schemas.
1247. fixer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fixer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1248. fixer-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fixer IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1249. flexisign-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Flexisign tasks via Rube MCP (Composio). Always search tools first for current schemas.
1250. flowiseai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Flowiseai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1251. flowstudio-power-automate-mcp github/awesome-copilot · score 72/100 (grade C)
      Foundation skill for Power Automate via FlowStudio MCP — auth setup, the reusable MCP helper (Python + Node.js), tool discovery via `list_skills` / `tool_search`, and oversized-response handling. Load this skill first when connecting an agent to Power Automate. For specialized workflows, load `flowstudio-power-automate-build`, `flowstudio-power-automate-debug`, `flowstudio-power-automate-monitoring` (Pro+), or `flowstudio-power-automate-governance` (Pro+) — each contains the workflow narrative, this skill provides the plumbing they all rely on. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app
1252. flutterwave-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Flutterwave tasks via Rube MCP (Composio). Always search tools first for current schemas.
1253. fluxguard-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fluxguard tasks via Rube MCP (Composio). Always search tools first for current schemas.
1254. folk-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Folk tasks via Rube MCP (Composio). Always search tools first for current schemas.
1255. fomo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fomo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1256. forcemanager-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Forcemanager tasks via Rube MCP (Composio). Always search tools first for current schemas.
1257. formbricks-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Formbricks tasks via Rube MCP (Composio). Always search tools first for current schemas.
1258. formcarry-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Formcarry tasks via Rube MCP (Composio). Always search tools first for current schemas.
1259. formdesk-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Formdesk tasks via Rube MCP (Composio). Always search tools first for current schemas.
1260. formsite-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Formsite tasks via Rube MCP (Composio). Always search tools first for current schemas.
1261. foundry-agentic-loop github/awesome-copilot · score 72/100 (grade C)
      Build agentic solutions on Microsoft Foundry, GitHub and Azure: hosted agents, toolbox tools and skills, Foundry IQ grounding and a React/FastAPI app. Three modes: rapid prototyping in an existing Foundry project; spec-driven development (SDD), where the foundry-agentic-loop-workflow runs Specify, Implement, Verify and Deploy to create the Foundry project and deploy with azd, or one phase runs alone; and Improve, which refines this skill and the workflow from past runs. Use for Agentic Loop requests and canvas actions, or end-to-end agent solutions from architecture to Azure deployment. Not for isolated Azure administration or unrelated UI edits.
1262. foursquare-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Foursquare tasks via Rube MCP (Composio). Always search tools first for current schemas.
1263. fraudlabs-pro-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fraudlabs Pro tasks via Rube MCP (Composio). Always search tools first for current schemas.
1264. front-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Front tasks via Rube MCP (Composio). Always search tools first for current schemas.
1265. fullenrich-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Fullenrich tasks via Rube MCP (Composio). Always search tools first for current schemas.
1266. gagelist-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gagelist tasks via Rube MCP (Composio). Always search tools first for current schemas.
1267. gamma-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gamma tasks via Rube MCP (Composio). Always search tools first for current schemas.
1268. gan-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gan AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1269. gatherup-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gatherup tasks via Rube MCP (Composio). Always search tools first for current schemas.
1270. gemini-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gemini tasks via Rube MCP (Composio). Always search tools first for current schemas.
1271. gender-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gender API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1272. genderapi-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Genderapi IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1273. genderize-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Genderize tasks via Rube MCP (Composio). Always search tools first for current schemas.
1274. geoapify-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Geoapify tasks via Rube MCP (Composio). Always search tools first for current schemas.
1275. geocodio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Geocodio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1276. geoffrey-hinton sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Agente que simula Geoffrey Hinton — Godfather of Deep Learning, Prêmio Turing 2018, coautor do trabalho de 1986 que popularizou backpropagation e das Deep Belief Networks.
1277. geokeo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Geokeo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1278. getform-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Getform tasks via Rube MCP (Composio). Always search tools first for current schemas.
1279. gift-up-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gift Up tasks via Rube MCP (Composio). Always search tools first for current schemas.
1280. gigasheet-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gigasheet tasks via Rube MCP (Composio). Always search tools first for current schemas.
1281. giphy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Giphy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1282. gist-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gist tasks via Rube MCP (Composio). Always search tools first for current schemas.
1283. givebutter-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Givebutter tasks via Rube MCP (Composio). Always search tools first for current schemas.
1284. gladia-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gladia tasks via Rube MCP (Composio). Always search tools first for current schemas.
1285. gleap-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gleap tasks via Rube MCP (Composio). Always search tools first for current schemas.
1286. globalping-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Globalping tasks via Rube MCP (Composio). Always search tools first for current schemas.
1287. go-to-webinar-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate GoToWebinar tasks via Rube MCP (Composio). Always search tools first for current schemas.
1288. godial-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Godial tasks via Rube MCP (Composio). Always search tools first for current schemas.
1289. goodbits-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Goodbits tasks via Rube MCP (Composio). Always search tools first for current schemas.
1290. goody-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Goody tasks via Rube MCP (Composio). Always search tools first for current schemas.
1291. google-address-validation-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google Address Validation tasks via Rube MCP (Composio). Always search tools first for current schemas.
1292. google-classroom-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google Classroom tasks via Rube MCP (Composio). Always search tools first for current schemas.
1293. google-cloud-vision-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google Cloud Vision tasks via Rube MCP (Composio). Always search tools first for current schemas.
1294. googlebigquery-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google BigQuery tasks via Rube MCP (Composio): run SQL queries, explore datasets and metadata, execute MBQL queries via Metabase integration. Always search tools first for current schemas.
1295. googlecalendar-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google Calendar tasks via Rube MCP (Composio). Always search tools first for current schemas.
1296. googledrive-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google Drive tasks via Rube MCP (Composio). Always search tools first for current schemas.
1297. googlesuper-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Google Super tasks via Rube MCP (Composio). Always search tools first for current schemas.
1298. gosquared-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Gosquared tasks via Rube MCP (Composio). Always search tools first for current schemas.
1299. grade-iterate alirezarezvani/claude-skills · score 72/100 (grade C)
      Phase 3 of building a Claude Managed Agent — the bounded grade→iterate loop. Define a CMA outcome (a required markdown rubric graded by an isolated grader), read each verdict, decide the next move (sharpen / re-run / promote to schedule), and once a version passes, run held-back eval cases in parallel. Use when the user says "grade my agent", "make it pass the rubric", "iterate until it's good", "is it good enough", or when the orchestrator routes phase=grade-iterate. outcome_builder.py builds the user.define_outcome payload (rubric required, max_iterations clamped 1..20 — never unbounded); verdict_reader.py reads the grader result and recommends the next move; eval_scaffold.py generates held-back cases + a parallel run plan (capped at the 25-thread CMA ceiling). Distinct from stage-launch (first launch) and run-without-you (scheduling).
1300. grafbase-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Grafbase tasks via Rube MCP (Composio). Always search tools first for current schemas.
1301. graphhopper-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Graphhopper tasks via Rube MCP (Composio). Always search tools first for current schemas.
1302. griptape-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Griptape tasks via Rube MCP (Composio). Always search tools first for current schemas.
1303. grist-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Grist tasks via Rube MCP (Composio). Always search tools first for current schemas.
1304. habitica-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Habitica tasks via Rube MCP (Composio). Always search tools first for current schemas.
1305. hackernews-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hackernews tasks via Rube MCP (Composio). Always search tools first for current schemas.
1306. happy-scribe-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Happy Scribe tasks via Rube MCP (Composio). Always search tools first for current schemas.
1307. hashnode-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hashnode tasks via Rube MCP (Composio). Always search tools first for current schemas.
1308. helcim-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Helcim tasks via Rube MCP (Composio). Always search tools first for current schemas.
1309. helloleads-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Helloleads tasks via Rube MCP (Composio). Always search tools first for current schemas.
1310. helpwise-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Helpwise tasks via Rube MCP (Composio). Always search tools first for current schemas.
1311. here-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Here tasks via Rube MCP (Composio). Always search tools first for current schemas.
1312. heyreach-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Heyreach tasks via Rube MCP (Composio). Always search tools first for current schemas.
1313. heyzine-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Heyzine tasks via Rube MCP (Composio). Always search tools first for current schemas.
1314. highergov-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Highergov tasks via Rube MCP (Composio). Always search tools first for current schemas.
1315. highlevel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Highlevel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1316. honeybadger-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Honeybadger tasks via Rube MCP (Composio). Always search tools first for current schemas.
1317. honeyhive-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Honeyhive tasks via Rube MCP (Composio). Always search tools first for current schemas.
1318. hook-development Galaxy-Dawn/claude-scholar · score 72/100 (grade C)
      This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.
1319. hookdeck-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hookdeck tasks via Rube MCP (Composio). Always search tools first for current schemas.
1320. hotspotsystem-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hotspotsystem tasks via Rube MCP (Composio). Always search tools first for current schemas.
1321. html-to-image-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Html To Image tasks via Rube MCP (Composio). Always search tools first for current schemas.
1322. hub-run alirezarezvani/claude-skills · score 72/100 (grade C)
      One-shot lifecycle command that chains init → baseline → spawn → eval → merge in a single invocation. Use when the user runs /hub:hub-run or asks to execute a full AgentHub competition end-to-end.
1323. hub-status alirezarezvani/claude-skills · score 72/100 (grade C)
      Show DAG state, agent progress, and branch status for an AgentHub session. Use when the user runs /hub:hub-status or asks how the AgentHub agents are doing.
1324. hugging-face-cli sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub.
1325. human-gate alirezarezvani/claude-skills · score 72/100 (grade C)
      Runs the human-verification lane of an agent loop, and proves review happened before work is called done. Builds a single-file HTML review page, collects batched feedback as a structured artifact instead of chat prose, and runs a gate that refuses to close while a BLOCKER is open, the reviewer is unnamed, or nobody has reviewed at all. Use when a plan, spec, RFC, report, landing page, migration, or any irreversible action needs human sign-off before shipping, or on requests such as 'get sign-off', 'have someone check this', 'hold until reviewed', 'needs approval first'. NOT for making AI text sound human (use content-humanizer or behuman). NOT for reviewing code diffs (use md-review or code-reviewer).
1326. humanitix-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Humanitix tasks via Rube MCP (Composio). Always search tools first for current schemas.
1327. humanloop-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Humanloop tasks via Rube MCP (Composio). Always search tools first for current schemas.
1328. hypeauditor-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hypeauditor tasks via Rube MCP (Composio). Always search tools first for current schemas.
1329. hyperbrowser-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hyperbrowser tasks via Rube MCP (Composio). Always search tools first for current schemas.
1330. hyperise-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hyperise tasks via Rube MCP (Composio). Always search tools first for current schemas.
1331. hystruct-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Hystruct tasks via Rube MCP (Composio). Always search tools first for current schemas.
1332. icims-talent-cloud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Icims Talent Cloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1333. icypeas-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Icypeas tasks via Rube MCP (Composio). Always search tools first for current schemas.
1334. idea-evaluator sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Evaluates an idea by hosting a multi-turn debate between a Pro and Con agent, delivering a final verdict on whether it's worth pursuing.
1335. idea-scale-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Idea Scale tasks via Rube MCP (Composio). Always search tools first for current schemas.
1336. identitycheck-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Identitycheck tasks via Rube MCP (Composio). Always search tools first for current schemas.
1337. ignisign-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ignisign tasks via Rube MCP (Composio). Always search tools first for current schemas.
1338. imagekit-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Imagekit IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1339. imgbb-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Imgbb tasks via Rube MCP (Composio). Always search tools first for current schemas.
1340. imgix-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Imgix tasks via Rube MCP (Composio). Always search tools first for current schemas.
1341. influxdb-cloud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Influxdb Cloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1342. insighto-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Insighto AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1343. instacart-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Instacart tasks via Rube MCP (Composio). Always search tools first for current schemas.
1344. intelliprint-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Intelliprint tasks via Rube MCP (Composio). Always search tools first for current schemas.
1345. interzoid-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Interzoid tasks via Rube MCP (Composio). Always search tools first for current schemas.
1346. ip2location-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ip2location tasks via Rube MCP (Composio). Always search tools first for current schemas.
1347. ip2location-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ip2location IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1348. ip2proxy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ip2proxy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1349. ip2whois-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ip2whois tasks via Rube MCP (Composio). Always search tools first for current schemas.
1350. ipdata-co-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ipdata co tasks via Rube MCP (Composio). Always search tools first for current schemas.
1351. ipinfo-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ipinfo IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1352. iqair-airvisual-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Iqair Airvisual tasks via Rube MCP (Composio). Always search tools first for current schemas.
1353. java-junit github/awesome-copilot · score 72/100 (grade C)
      Write, review and fix Java unit tests with JUnit 5 and JUnit 6 (Jupiter), AssertJ and Mockito: assertions, parameterized and nested tests, mocking rules, deterministic time and randomness, Surefire vs Failsafe, JaCoCo coverage, optional PIT mutation testing, and guardrails for agents (never skip or delete failing tests). Use when adding, refactoring or debugging tests in Maven or Gradle projects. Framework-neutral.
1354. jigsawstack-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Jigsawstack tasks via Rube MCP (Composio). Always search tools first for current schemas.
1355. jobnimbus-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Jobnimbus tasks via Rube MCP (Composio). Always search tools first for current schemas.
1356. jumpcloud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Jumpcloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1357. junglescout-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Junglescout tasks via Rube MCP (Composio). Always search tools first for current schemas.
1358. kadoa-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kadoa tasks via Rube MCP (Composio). Always search tools first for current schemas.
1359. kaggle-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kaggle tasks via Rube MCP (Composio). Always search tools first for current schemas.
1360. kaleido-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kaleido tasks via Rube MCP (Composio). Always search tools first for current schemas.
1361. keap-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Keap tasks via Rube MCP (Composio). Always search tools first for current schemas.
1362. keen-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Keen IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1363. kickbox-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kickbox tasks via Rube MCP (Composio). Always search tools first for current schemas.
1364. kit-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kit tasks via Rube MCP (Composio). Always search tools first for current schemas.
1365. klipfolio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Klipfolio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1366. ko-fi-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ko Fi tasks via Rube MCP (Composio). Always search tools first for current schemas.
1367. kontent-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kontent AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1368. kraken-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Kraken IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1369. l2s-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate L2s tasks via Rube MCP (Composio). Always search tools first for current schemas.
1370. labs64-netlicensing-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Labs64 Netlicensing tasks via Rube MCP (Composio). Always search tools first for current schemas.
1371. landbot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Landbot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1372. langbase-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Langbase tasks via Rube MCP (Composio). Always search tools first for current schemas.
1373. lastpass-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Lastpass tasks via Rube MCP (Composio). Always search tools first for current schemas.
1374. leadfeeder-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Leadfeeder tasks via Rube MCP (Composio). Always search tools first for current schemas.
1375. leadoku-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Leadoku tasks via Rube MCP (Composio). Always search tools first for current schemas.
1376. leiga-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Leiga tasks via Rube MCP (Composio). Always search tools first for current schemas.
1377. lessonspace-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Lessonspace tasks via Rube MCP (Composio). Always search tools first for current schemas.
1378. lever-sandbox-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Lever Sandbox tasks via Rube MCP (Composio). Always search tools first for current schemas.
1379. leverly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Leverly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1380. lexoffice-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Lexoffice tasks via Rube MCP (Composio). Always search tools first for current schemas.
1381. linguapop-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Linguapop tasks via Rube MCP (Composio). Always search tools first for current schemas.
1382. linkhut-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Linkhut tasks via Rube MCP (Composio). Always search tools first for current schemas.
1383. linkup-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Linkup tasks via Rube MCP (Composio). Always search tools first for current schemas.
1384. listclean-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Listclean tasks via Rube MCP (Composio). Always search tools first for current schemas.
1385. listennotes-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Listennotes tasks via Rube MCP (Composio). Always search tools first for current schemas.
1386. livesession-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Livesession tasks via Rube MCP (Composio). Always search tools first for current schemas.
1387. lmnt-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Lmnt tasks via Rube MCP (Composio). Always search tools first for current schemas.
1388. lodgify-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Lodgify tasks via Rube MCP (Composio). Always search tools first for current schemas.
1389. logo-dev-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Logo Dev tasks via Rube MCP (Composio). Always search tools first for current schemas.
1390. loomio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Loomio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1391. loop-design-check affaan-m/ECC · score 72/100 (grade C)
      Design a goal-oriented agent loop or review one for failure modes: spinning, Goodhart-gaming the verifier, or running a wrong answer to completion. Covers machine-decidable goals, loop types, plan/build/judge skeletons, and runaway prevention; mechanism wiring lives in autonomous-loops. Use when designing, writing, or checking an agent loop. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。
1392. loop-design-check affaan-m/everything-claude-code · score 72/100 (grade C)
      Design a goal-oriented agent loop or review one for failure modes: spinning, Goodhart-gaming the verifier, or running a wrong answer to completion. Covers machine-decidable goals, loop types, plan/build/judge skeletons, and runaway prevention; mechanism wiring lives in autonomous-loops. Use when designing, writing, or checking an agent loop. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。
1393. loyverse-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Loyverse tasks via Rube MCP (Composio). Always search tools first for current schemas.
1394. magnetic-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Magnetic tasks via Rube MCP (Composio). Always search tools first for current schemas.
1395. mailbluster-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mailbluster tasks via Rube MCP (Composio). Always search tools first for current schemas.
1396. mailboxlayer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mailboxlayer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1397. mailcheck-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mailcheck tasks via Rube MCP (Composio). Always search tools first for current schemas.
1398. mailcoach-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mailcoach tasks via Rube MCP (Composio). Always search tools first for current schemas.
1399. mailersend-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mailersend tasks via Rube MCP (Composio). Always search tools first for current schemas.
1400. mails-so-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mails So tasks via Rube MCP (Composio). Always search tools first for current schemas.
1401. mailsoftly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mailsoftly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1402. maintainx-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Maintainx tasks via Rube MCP (Composio). Always search tools first for current schemas.
1403. mantis-reflect google/mantis · score 72/100 (grade C)
      Extracts learnings from execution trajectories at the end of a Mantis loop. Use to parse agent conversations, extract successes, failures, and false assumptions, and append them to workspace/learnings.jsonl. Don't use for analyzing source code or writing patches.
1404. many-chat-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate ManyChat tasks via Rube MCP (Composio). Always search tools first for current schemas.
1405. mapbox-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mapbox tasks via Rube MCP (Composio). Always search tools first for current schemas.
1406. mapulus-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mapulus tasks via Rube MCP (Composio). Always search tools first for current schemas.
1407. marketing-demand-acquisition alirezarezvani/claude-skills · score 72/100 (grade C)
      Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs. Use when planning demand gen strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, technical SEO, and co-marketing partnerships. Default calibration profile is a Series A+ B2B SaaS scaling internationally (EU/US/Canada, hybrid PLG/Sales-Led) — adapt benchmarks for other stages and motions rather than skipping the skill.
1408. marketing-ops alirezarezvani/claude-skills · score 72/100 (grade C)
      Central router for the marketing skill ecosystem. Use when unsure which marketing skill to use, when orchestrating a multi-skill campaign, or when coordinating across content, SEO, CRO, channels, and analytics. Also use when the user mentions 'marketing help,' 'campaign plan,' 'what should I do next,' 'marketing priorities,' or 'coordinate marketing.'
1409. mboum-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mboum tasks via Rube MCP (Composio). Always search tools first for current schemas.
1410. mcp-server-patterns affaan-m/ECC · score 72/100 (grade C)
      Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API. Use when building or debugging an MCP server — tools, resources, prompts, validation, or transport choice.
1411. mcp-server-patterns affaan-m/everything-claude-code · score 72/100 (grade C)
      Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API. Use when building or debugging an MCP server — tools, resources, prompts, validation, or transport choice.
1412. melo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Melo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1413. mem-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mem tasks via Rube MCP (Composio). Always search tools first for current schemas.
1414. mem0-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mem0 tasks via Rube MCP (Composio). Always search tools first for current schemas.
1415. memberspot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Memberspot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1416. memberstack-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Memberstack tasks via Rube MCP (Composio). Always search tools first for current schemas.
1417. membervault-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Membervault tasks via Rube MCP (Composio). Always search tools first for current schemas.
1418. metaads-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Metaads tasks via Rube MCP (Composio). Always search tools first for current schemas.
1419. metaphor-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Metaphor tasks via Rube MCP (Composio). Always search tools first for current schemas.
1420. mezmo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mezmo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1421. microsoft-tenant-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Microsoft Tenant tasks via Rube MCP (Composio). Always search tools first for current schemas.
1422. minerstat-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Minerstat tasks via Rube MCP (Composio). Always search tools first for current schemas.
1423. missive-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Missive tasks via Rube MCP (Composio). Always search tools first for current schemas.
1424. mocean-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mocean tasks via Rube MCP (Composio). Always search tools first for current schemas.
1425. moco-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Moco tasks via Rube MCP (Composio). Always search tools first for current schemas.
1426. modelry-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Modelry tasks via Rube MCP (Composio). Always search tools first for current schemas.
1427. monetization sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Estrategia e implementacao de monetizacao para produtos digitais - Stripe, subscriptions, pricing experiments, freemium, upgrade flows, churn prevention, revenue optimization e modelos de negocio SaaS.
1428. moneybird-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Moneybird tasks via Rube MCP (Composio). Always search tools first for current schemas.
1429. moonclerk-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Moonclerk tasks via Rube MCP (Composio). Always search tools first for current schemas.
1430. moosend-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Moosend tasks via Rube MCP (Composio). Always search tools first for current schemas.
1431. mopinion-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mopinion tasks via Rube MCP (Composio). Always search tools first for current schemas.
1432. more-trees-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate More Trees tasks via Rube MCP (Composio). Always search tools first for current schemas.
1433. moxie-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Moxie tasks via Rube MCP (Composio). Always search tools first for current schemas.
1434. moz-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Moz tasks via Rube MCP (Composio). Always search tools first for current schemas.
1435. msg91-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Msg91 tasks via Rube MCP (Composio). Always search tools first for current schemas.
1436. mural-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mural tasks via Rube MCP (Composio). Always search tools first for current schemas.
1437. mvvm-toolkit-di github/awesome-copilot · score 72/100 (grade C)
      Wire CommunityToolkit.Mvvm ViewModels into Microsoft.Extensions.DependencyInjection. Covers the .NET Generic Host composition root, constructor injection, service lifetimes (Singleton / Transient / Scoped), IMessenger registration, resolving ViewModels in Views, keyed services, testing seams, and the legacy Ioc.Default escape hatch. Use across WPF, WinUI 3, .NET MAUI, Uno, and Avalonia.
1438. mx-technologies-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate MX Technologies tasks via Rube MCP (Composio). Always search tools first for current schemas.
1439. mx-toolbox-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Mx Toolbox tasks via Rube MCP (Composio). Always search tools first for current schemas.
1440. nango-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Nango tasks via Rube MCP (Composio). Always search tools first for current schemas.
1441. nano-nets-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Nano Nets tasks via Rube MCP (Composio). Always search tools first for current schemas.
1442. nasa-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Nasa tasks via Rube MCP (Composio). Always search tools first for current schemas.
1443. nasdaq-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Nasdaq tasks via Rube MCP (Composio). Always search tools first for current schemas.
1444. ncscale-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ncscale tasks via Rube MCP (Composio). Always search tools first for current schemas.
1445. needle-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Needle tasks via Rube MCP (Composio). Always search tools first for current schemas.
1446. neuronwriter-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Neuronwriter tasks via Rube MCP (Composio). Always search tools first for current schemas.
1447. neutrino-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Neutrino tasks via Rube MCP (Composio). Always search tools first for current schemas.
1448. neverbounce-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Neverbounce tasks via Rube MCP (Composio). Always search tools first for current schemas.
1449. new-grok-bot davidondrej/skills · score 72/100 (grade C)
      Design a Grok Bot role and create its setup prompt. Use only when the user explicitly invokes /new-grok-bot.
1450. news-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate News API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1451. nextdns-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Nextdns tasks via Rube MCP (Composio). Always search tools first for current schemas.
1452. ngrok-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ngrok tasks via Rube MCP (Composio). Always search tools first for current schemas.
1453. ninox-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ninox tasks via Rube MCP (Composio). Always search tools first for current schemas.
1454. nocrm-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Nocrm IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1455. npm-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate NPM tasks via Rube MCP (Composio). Always search tools first for current schemas.
1456. ocr-web-service-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate OCR Web Service tasks via Rube MCP (Composio). Always search tools first for current schemas.
1457. ocrspace-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ocrspace tasks via Rube MCP (Composio). Always search tools first for current schemas.
1458. odoo-security-rules sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Expert in Odoo access control: ir.model.access.csv, record rules (ir.rule), groups, and multi-company security patterns.
1459. oncehub-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Oncehub tasks via Rube MCP (Composio). Always search tools first for current schemas.
1460. onedesk-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Onedesk tasks via Rube MCP (Composio). Always search tools first for current schemas.
1461. onepage-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Onepage tasks via Rube MCP (Composio). Always search tools first for current schemas.
1462. onesignal-rest-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate OneSignal tasks via Rube MCP (Composio). Always search tools first for current schemas.
1463. onesignal-user-auth-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Onesignal User Auth tasks via Rube MCP (Composio). Always search tools first for current schemas.
1464. open-sea-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Open Sea tasks via Rube MCP (Composio). Always search tools first for current schemas.
1465. opencage-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Opencage tasks via Rube MCP (Composio). Always search tools first for current schemas.
1466. opengraph-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Opengraph IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1467. openperplex-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Openperplex tasks via Rube MCP (Composio). Always search tools first for current schemas.
1468. openrouter-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Openrouter tasks via Rube MCP (Composio). Always search tools first for current schemas.
1469. openweather-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Openweather API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1470. optimoroute-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Optimoroute tasks via Rube MCP (Composio). Always search tools first for current schemas.
1471. owl-protocol-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Owl Protocol tasks via Rube MCP (Composio). Always search tools first for current schemas.
1472. page-x-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Page X tasks via Rube MCP (Composio). Always search tools first for current schemas.
1473. paradym-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Paradym tasks via Rube MCP (Composio). Always search tools first for current schemas.
1474. parallel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Parallel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1475. parma-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Parma tasks via Rube MCP (Composio). Always search tools first for current schemas.
1476. parsehub-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Parsehub tasks via Rube MCP (Composio). Always search tools first for current schemas.
1477. parsera-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Parsera tasks via Rube MCP (Composio). Always search tools first for current schemas.
1478. parseur-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Parseur tasks via Rube MCP (Composio). Always search tools first for current schemas.
1479. passcreator-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Passcreator tasks via Rube MCP (Composio). Always search tools first for current schemas.
1480. passslot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Passslot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1481. payhip-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Payhip tasks via Rube MCP (Composio). Always search tools first for current schemas.
1482. pdf-api-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate PDF API IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1483. pdf-co-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate PDF co tasks via Rube MCP (Composio). Always search tools first for current schemas.
1484. pdf4me-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pdf4me tasks via Rube MCP (Composio). Always search tools first for current schemas.
1485. pdfless-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pdfless tasks via Rube MCP (Composio). Always search tools first for current schemas.
1486. pdfmonkey-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pdfmonkey tasks via Rube MCP (Composio). Always search tools first for current schemas.
1487. peopledatalabs-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Peopledatalabs tasks via Rube MCP (Composio). Always search tools first for current schemas.
1488. perigon-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Perigon tasks via Rube MCP (Composio). Always search tools first for current schemas.
1489. perplexityai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Perplexityai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1490. persistiq-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Persistiq tasks via Rube MCP (Composio). Always search tools first for current schemas.
1491. pexels-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pexels tasks via Rube MCP (Composio). Always search tools first for current schemas.
1492. piggy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Piggy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1493. piloterr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Piloterr tasks via Rube MCP (Composio). Always search tools first for current schemas.
1494. pilvio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pilvio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1495. pingdom-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pingdom tasks via Rube MCP (Composio). Always search tools first for current schemas.
1496. pipeline-crm-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pipeline CRM tasks via Rube MCP (Composio). Always search tools first for current schemas.
1497. placekey-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Placekey tasks via Rube MCP (Composio). Always search tools first for current schemas.
1498. placid-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Placid tasks via Rube MCP (Composio). Always search tools first for current schemas.
1499. plain-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Plain tasks via Rube MCP (Composio). Always search tools first for current schemas.
1500. plankton-code-quality affaan-m/ECC · score 72/100 (grade C)
      Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks. Use when setting up write-time formatting, linting, or auto-fix hooks on file edits.
1501. plankton-code-quality affaan-m/everything-claude-code · score 72/100 (grade C)
      Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks. Use when setting up write-time formatting, linting, or auto-fix hooks on file edits.
1502. plasmic-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Plasmic tasks via Rube MCP (Composio). Always search tools first for current schemas.
1503. platerecognizer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Platerecognizer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1504. playwright-pro alirezarezvani/claude-skills · score 72/100 (grade C)
      Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests, test migration, CI/CD testing, or test suites. Generate tests, fix flaky failures, migrate from Cypress/Selenium, sync with TestRail, run on BrowserStack. 55 templates, 3 agents, smart reporting.
1505. plisio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Plisio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1506. plugin-creator openai/skills · score 72/100 (grade C)
      Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, and baseline placeholders you can edit before publishing or testing. Use when Codex needs to create a new local plugin, add optional plugin structure, or generate or update repo-root `.agents/plugins/marketplace.json` entries for plugin ordering and availability metadata.
1507. polygon-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Polygon tasks via Rube MCP (Composio). Always search tools first for current schemas.
1508. polygon-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Polygon IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1509. poptin-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Poptin tasks via Rube MCP (Composio). Always search tools first for current schemas.
1510. postgrid-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Postgrid tasks via Rube MCP (Composio). Always search tools first for current schemas.
1511. postgrid-verify-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Postgrid Verify tasks via Rube MCP (Composio). Always search tools first for current schemas.
1512. power-bi-model-design-review github/awesome-copilot · score 72/100 (grade C)
      Comprehensive Power BI data model design review prompt for evaluating model architecture, relationships, and optimization opportunities.
1513. ppl-personal-crm sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Uses the ppl personal CRM over MCP to prepare for conversations, recall facts about people, log interactions and manage relationship follow-ups.
1514. precoro-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Precoro tasks via Rube MCP (Composio). Always search tools first for current schemas.
1515. prerender-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Prerender tasks via Rube MCP (Composio). Always search tools first for current schemas.
1516. printautopilot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Printautopilot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1517. prisma-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Prisma tasks via Rube MCP (Composio). Always search tools first for current schemas.
1518. process-street-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Process Street tasks via Rube MCP (Composio). Always search tools first for current schemas.
1519. procfu-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Procfu tasks via Rube MCP (Composio). Always search tools first for current schemas.
1520. productlane-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Productlane tasks via Rube MCP (Composio). Always search tools first for current schemas.
1521. project-bubble-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Project Bubble tasks via Rube MCP (Composio). Always search tools first for current schemas.
1522. proofly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Proofly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1523. proxiedmail-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Proxiedmail tasks via Rube MCP (Composio). Always search tools first for current schemas.
1524. push-skills davidondrej/skills · score 72/100 (grade C)
      Push skills and global AGENTS.md to the private repo and verify the public mirror. Use only when the user explicitly invokes /push-skills.
1525. pushbullet-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pushbullet tasks via Rube MCP (Composio). Always search tools first for current schemas.
1526. pushover-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Pushover tasks via Rube MCP (Composio). Always search tools first for current schemas.
1527. quaderno-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Quaderno tasks via Rube MCP (Composio). Always search tools first for current schemas.
1528. qualaroo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Qualaroo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1529. radar-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Radar tasks via Rube MCP (Composio). Always search tools first for current schemas.
1530. rafflys-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rafflys tasks via Rube MCP (Composio). Always search tools first for current schemas.
1531. ragic-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ragic tasks via Rube MCP (Composio). Always search tools first for current schemas.
1532. raisely-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Raisely tasks via Rube MCP (Composio). Always search tools first for current schemas.
1533. ravenseotools-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ravenseotools tasks via Rube MCP (Composio). Always search tools first for current schemas.
1534. re-amaze-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Re Amaze tasks via Rube MCP (Composio). Always search tools first for current schemas.
1535. realphonevalidation-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Realphonevalidation tasks via Rube MCP (Composio). Always search tools first for current schemas.
1536. recallai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Recallai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1537. recruitee-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Recruitee tasks via Rube MCP (Composio). Always search tools first for current schemas.
1538. refiner-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Refiner tasks via Rube MCP (Composio). Always search tools first for current schemas.
1539. remarkety-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Remarkety tasks via Rube MCP (Composio). Always search tools first for current schemas.
1540. remote-retrieval-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Remote Retrieval tasks via Rube MCP (Composio). Always search tools first for current schemas.
1541. renderform-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Renderform tasks via Rube MCP (Composio). Always search tools first for current schemas.
1542. repairshopr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Repairshopr tasks via Rube MCP (Composio). Always search tools first for current schemas.
1543. reply-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Reply tasks via Rube MCP (Composio). Always search tools first for current schemas.
1544. reply-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Reply IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1545. resend-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Resend tasks via Rube MCP (Composio). Always search tools first for current schemas.
1546. respond-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Respond IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1547. retailed-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Retailed tasks via Rube MCP (Composio). Always search tools first for current schemas.
1548. retellai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Retellai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1549. retently-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Retently tasks via Rube MCP (Composio). Always search tools first for current schemas.
1550. rev-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rev AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1551. revolt-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Revolt tasks via Rube MCP (Composio). Always search tools first for current schemas.
1552. rippling-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rippling tasks via Rube MCP (Composio). Always search tools first for current schemas.
1553. ritekit-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ritekit tasks via Rube MCP (Composio). Always search tools first for current schemas.
1554. rkvst-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rkvst tasks via Rube MCP (Composio). Always search tools first for current schemas.
1555. rocketlane-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rocketlane tasks via Rube MCP (Composio). Always search tools first for current schemas.
1556. rootly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rootly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1557. rosette-text-analytics-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Rosette Text Analytics tasks via Rube MCP (Composio). Always search tools first for current schemas.
1558. route4me-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Route4me tasks via Rube MCP (Composio). Always search tools first for current schemas.
1559. safetyculture-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Safetyculture tasks via Rube MCP (Composio). Always search tools first for current schemas.
1560. sage-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sage tasks via Rube MCP (Composio). Always search tools first for current schemas.
1561. salesforce-marketing-cloud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Salesforce Marketing Cloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1562. salesforce-service-cloud-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Salesforce Service Cloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
1563. salesmate-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Salesmate tasks via Rube MCP (Composio). Always search tools first for current schemas.
1564. sap-successfactors-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate SAP SuccessFactors tasks via Rube MCP (Composio). Always search tools first for current schemas.
1565. satismeter-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Satismeter tasks via Rube MCP (Composio). Always search tools first for current schemas.
1566. scrape-do-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Scrape Do tasks via Rube MCP (Composio). Always search tools first for current schemas.
1567. scrapegraph-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Scrapegraph AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1568. scrapfly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Scrapfly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1569. scrapingant-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Scrapingant tasks via Rube MCP (Composio). Always search tools first for current schemas.
1570. scrapingbee-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Scrapingbee tasks via Rube MCP (Composio). Always search tools first for current schemas.
1571. screenshot-fyi-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Screenshot Fyi tasks via Rube MCP (Composio). Always search tools first for current schemas.
1572. screenshotone-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Screenshotone tasks via Rube MCP (Composio). Always search tools first for current schemas.
1573. seat-geek-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Seat Geek tasks via Rube MCP (Composio). Always search tools first for current schemas.
1574. security-scan affaan-m/ECC · score 72/100 (grade C)
      Scan your Claude Code configuration (.claude/ directory) for security vulnerabilities, misconfigurations, and injection risks using AgentShield. Checks CLAUDE.md, settings.json, MCP servers, hooks, and agent definitions. Use when auditing a .claude/ directory — CLAUDE.md, settings.json, MCP servers, hooks, or agent definitions.
1575. security-scan affaan-m/everything-claude-code · score 72/100 (grade C)
      Scan your Claude Code configuration (.claude/ directory) for security vulnerabilities, misconfigurations, and injection risks using AgentShield. Checks CLAUDE.md, settings.json, MCP servers, hooks, and agent definitions. Use when auditing a .claude/ directory — CLAUDE.md, settings.json, MCP servers, hooks, or agent definitions.
1576. security-threat-model openai/skills · score 72/100 (grade C)
      Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.
1577. securitytrails-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Securitytrails tasks via Rube MCP (Composio). Always search tools first for current schemas.
1578. segmetrics-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Segmetrics tasks via Rube MCP (Composio). Always search tools first for current schemas.
1579. seismic-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Seismic tasks via Rube MCP (Composio). Always search tools first for current schemas.
1580. semanticscholar-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Semanticscholar tasks via Rube MCP (Composio). Always search tools first for current schemas.
1581. sendbird-ai-chabot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sendbird AI Chabot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1582. sendbird-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sendbird tasks via Rube MCP (Composio). Always search tools first for current schemas.
1583. sendfox-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sendfox tasks via Rube MCP (Composio). Always search tools first for current schemas.
1584. sendlane-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sendlane tasks via Rube MCP (Composio). Always search tools first for current schemas.
1585. sendloop-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sendloop tasks via Rube MCP (Composio). Always search tools first for current schemas.
1586. sendspark-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sendspark tasks via Rube MCP (Composio). Always search tools first for current schemas.
1587. sensibo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sensibo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1588. seqera-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Seqera tasks via Rube MCP (Composio). Always search tools first for current schemas.
1589. serpapi-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Serpapi tasks via Rube MCP (Composio). Always search tools first for current schemas.
1590. serpdog-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Serpdog tasks via Rube MCP (Composio). Always search tools first for current schemas.
1591. serply-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Serply tasks via Rube MCP (Composio). Always search tools first for current schemas.
1592. servicem8-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Servicem8 tasks via Rube MCP (Composio). Always search tools first for current schemas.
1593. session-handoff entireio/skills · score 72/100 (grade C)
      Use when the user wants to continue work from one agent in another agent, inspect recent sessions, or summarize a saved session or checkpoint for handoff
1594. sevdesk-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sevdesk tasks via Rube MCP (Composio). Always search tools first for current schemas.
1595. shipengine-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Shipengine tasks via Rube MCP (Composio). Always search tools first for current schemas.
1596. short-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Short IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1597. short-menu-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Short Menu tasks via Rube MCP (Composio). Always search tools first for current schemas.
1598. shorten-rest-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Shorten Rest tasks via Rube MCP (Composio). Always search tools first for current schemas.
1599. shortpixel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Shortpixel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1600. shotstack-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Shotstack tasks via Rube MCP (Composio). Always search tools first for current schemas.
1601. sidetracker-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sidetracker tasks via Rube MCP (Composio). Always search tools first for current schemas.
1602. signaturely-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Signaturely tasks via Rube MCP (Composio). Always search tools first for current schemas.
1603. signpath-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Signpath tasks via Rube MCP (Composio). Always search tools first for current schemas.
1604. signwell-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Signwell tasks via Rube MCP (Composio). Always search tools first for current schemas.
1605. similarweb-digitalrank-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate SimilarWeb tasks via Rube MCP (Composio). Always search tools first for current schemas.
1606. simla-com-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Simla Com tasks via Rube MCP (Composio). Always search tools first for current schemas.
1607. simple-analytics-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Simple Analytics tasks via Rube MCP (Composio). Always search tools first for current schemas.
1608. simplesat-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Simplesat tasks via Rube MCP (Composio). Always search tools first for current schemas.
1609. sitespeakai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sitespeakai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1610. skill-seekers sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Convert approved documentation, repositories, or PDFs into an agent skill using the Skill Seekers workflow, then review the generated content.
1611. skyfire-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Skyfire tasks via Rube MCP (Composio). Always search tools first for current schemas.
1612. slackbot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Slackbot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1613. smartproxy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Smartproxy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1614. smartrecruiters-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Smartrecruiters tasks via Rube MCP (Composio). Always search tools first for current schemas.
1615. sms-alert-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate SMS Alert tasks via Rube MCP (Composio). Always search tools first for current schemas.
1616. smtp2go-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Smtp2go tasks via Rube MCP (Composio). Always search tools first for current schemas.
1617. smugmug-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Smugmug tasks via Rube MCP (Composio). Always search tools first for current schemas.
1618. sourcegraph-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sourcegraph tasks via Rube MCP (Composio). Always search tools first for current schemas.
1619. splitwise-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Splitwise tasks via Rube MCP (Composio). Always search tools first for current schemas.
1620. spoki-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Spoki tasks via Rube MCP (Composio). Always search tools first for current schemas.
1621. spondyr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Spondyr tasks via Rube MCP (Composio). Always search tools first for current schemas.
1622. spotlightr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Spotlightr tasks via Rube MCP (Composio). Always search tools first for current schemas.
1623. sslmate-cert-spotter-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sslmate Cert Spotter API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1624. stack-exchange-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Stack Exchange tasks via Rube MCP (Composio). Always search tools first for current schemas.
1625. stannp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Stannp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1626. starton-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Starton tasks via Rube MCP (Composio). Always search tools first for current schemas.
1627. startup-metrics-framework sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Comprehensive guide to tracking, calculating, and optimizing key performance metrics for different startup business models from seed through Series A.
1628. statuscake-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Statuscake tasks via Rube MCP (Composio). Always search tools first for current schemas.
1629. stitch-loop sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Teaches agents to iteratively build websites using Stitch with an autonomous baton-passing loop pattern
1630. storeganise-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Storeganise tasks via Rube MCP (Composio). Always search tools first for current schemas.
1631. storerocket-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Storerocket tasks via Rube MCP (Composio). Always search tools first for current schemas.
1632. stormglass-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Stormglass IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1633. strava-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Strava tasks via Rube MCP (Composio). Always search tools first for current schemas.
1634. streamtime-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Streamtime tasks via Rube MCP (Composio). Always search tools first for current schemas.
1635. supadata-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Supadata tasks via Rube MCP (Composio). Always search tools first for current schemas.
1636. superchat-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Superchat tasks via Rube MCP (Composio). Always search tools first for current schemas.
1637. supportbee-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Supportbee tasks via Rube MCP (Composio). Always search tools first for current schemas.
1638. supportivekoala-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Supportivekoala tasks via Rube MCP (Composio). Always search tools first for current schemas.
1639. svix-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Svix tasks via Rube MCP (Composio). Always search tools first for current schemas.
1640. sympla-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Sympla tasks via Rube MCP (Composio). Always search tools first for current schemas.
1641. synthflow-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Synthflow AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1642. taggun-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Taggun tasks via Rube MCP (Composio). Always search tools first for current schemas.
1643. talenthr-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Talenthr tasks via Rube MCP (Composio). Always search tools first for current schemas.
1644. tally-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tally tasks via Rube MCP (Composio). Always search tools first for current schemas.
1645. tapfiliate-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tapfiliate tasks via Rube MCP (Composio). Always search tools first for current schemas.
1646. tapform-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tapform tasks via Rube MCP (Composio). Always search tools first for current schemas.
1647. task-intelligence sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Protocolo de Inteligência Pré-Tarefa — planeja a tarefa e consulta apenas agentes disponíveis, relevantes e autorizados quando o benefício justificar o custo.
1648. tavily-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tavily tasks via Rube MCP (Composio). Always search tools first for current schemas.
1649. taxjar-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Taxjar tasks via Rube MCP (Composio). Always search tools first for current schemas.
1650. teamcamp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Teamcamp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1651. telnyx-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Telnyx tasks via Rube MCP (Composio). Always search tools first for current schemas.
1652. teltel-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Teltel tasks via Rube MCP (Composio). Always search tools first for current schemas.
1653. templated-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Templated tasks via Rube MCP (Composio). Always search tools first for current schemas.
1654. text-to-pdf-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Text To PDF tasks via Rube MCP (Composio). Always search tools first for current schemas.
1655. textcortex-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Textcortex tasks via Rube MCP (Composio). Always search tools first for current schemas.
1656. textit-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Textit tasks via Rube MCP (Composio). Always search tools first for current schemas.
1657. textrazor-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Textrazor tasks via Rube MCP (Composio). Always search tools first for current schemas.
1658. thanks-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Thanks IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1659. the-odds-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate The Odds API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1660. ticketmaster-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ticketmaster tasks via Rube MCP (Composio). Always search tools first for current schemas.
1661. ticktick-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ticktick tasks via Rube MCP (Composio). Always search tools first for current schemas.
1662. timecamp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Timecamp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1663. timekit-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Timekit tasks via Rube MCP (Composio). Always search tools first for current schemas.
1664. timelinesai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Timelinesai tasks via Rube MCP (Composio). Always search tools first for current schemas.
1665. timelink-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Timelink tasks via Rube MCP (Composio). Always search tools first for current schemas.
1666. timely-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Timely tasks via Rube MCP (Composio). Always search tools first for current schemas.
1667. tinyurl-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tinyurl tasks via Rube MCP (Composio). Always search tools first for current schemas.
1668. tisane-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tisane tasks via Rube MCP (Composio). Always search tools first for current schemas.
1669. tm7-threat-model github/awesome-copilot · score 72/100 (grade C)
      Creates valid Microsoft Threat Modeling Tool (.tm7) files compatible with the Microsoft Threat Modeling Tool v7.3+. Use this skill whenever asked to create, generate, or modify a .tm7 threat model file, or when performing STRIDE threat modeling that should output a .tm7 file that opens cleanly in the Microsoft Threat Modeling Tool.
1670. tomba-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tomba tasks via Rube MCP (Composio). Always search tools first for current schemas.
1671. tomtom-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tomtom tasks via Rube MCP (Composio). Always search tools first for current schemas.
1672. toneden-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Toneden tasks via Rube MCP (Composio). Always search tools first for current schemas.
1673. tpscheck-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Tpscheck tasks via Rube MCP (Composio). Always search tools first for current schemas.
1674. triggercmd-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Triggercmd tasks via Rube MCP (Composio). Always search tools first for current schemas.
1675. tripadvisor-content-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate TripAdvisor tasks via Rube MCP (Composio). Always search tools first for current schemas.
1676. turbot-pipes-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Turbot Pipes tasks via Rube MCP (Composio). Always search tools first for current schemas.
1677. turso-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Turso tasks via Rube MCP (Composio). Always search tools first for current schemas.
1678. twelve-data-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Twelve Data tasks via Rube MCP (Composio). Always search tools first for current schemas.
1679. twitch-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Twitch tasks via Rube MCP (Composio). Always search tools first for current schemas.
1680. twocaptcha-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Twocaptcha tasks via Rube MCP (Composio). Always search tools first for current schemas.
1681. typefully-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Typefully tasks via Rube MCP (Composio). Always search tools first for current schemas.
1682. typless-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Typless tasks via Rube MCP (Composio). Always search tools first for current schemas.
1683. u301-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate U301 tasks via Rube MCP (Composio). Always search tools first for current schemas.
1684. unione-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Unione tasks via Rube MCP (Composio). Always search tools first for current schemas.
1685. updown-io-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Updown IO tasks via Rube MCP (Composio). Always search tools first for current schemas.
1686. uptimerobot-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Uptimerobot tasks via Rube MCP (Composio). Always search tools first for current schemas.
1687. userlist-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Userlist tasks via Rube MCP (Composio). Always search tools first for current schemas.
1688. v0-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate V0 tasks via Rube MCP (Composio). Always search tools first for current schemas.
1689. venly-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Venly tasks via Rube MCP (Composio). Always search tools first for current schemas.
1690. veo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Veo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1691. verifiedemail-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Verifiedemail tasks via Rube MCP (Composio). Always search tools first for current schemas.
1692. verify-agent-action github/awesome-copilot · score 72/100 (grade C)
      Review a proposed AI-agent action or human-approval packet before execution. Use when an agent wants to run a consequential tool, command, deployment, message, purchase, credential operation, or data mutation; when checking whether approval still matches the exact action; or when auditing action evidence for forged results, parameter swaps, replay, correlated reviewers, missing evidence, expiry, or stale monitoring. Produce an evidence-based review only—never execute or authorize the action.
1693. veriphone-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Veriphone tasks via Rube MCP (Composio). Always search tools first for current schemas.
1694. vero-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Vero tasks via Rube MCP (Composio). Always search tools first for current schemas.
1695. vestaboard-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Vestaboard tasks via Rube MCP (Composio). Always search tools first for current schemas.
1696. vexor sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Vector-powered CLI for semantic file search with a Claude/Codex skill
1697. virustotal-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Virustotal tasks via Rube MCP (Composio). Always search tools first for current schemas.
1698. visme-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Visme tasks via Rube MCP (Composio). Always search tools first for current schemas.
1699. voice-agents sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Voice agents represent the frontier of AI interaction - humans
1700. waboxapp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Waboxapp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1701. wachete-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Wachete tasks via Rube MCP (Composio). Always search tools first for current schemas.
1702. waiverfile-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Waiverfile tasks via Rube MCP (Composio). Always search tools first for current schemas.
1703. wakatime-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Wakatime tasks via Rube MCP (Composio). Always search tools first for current schemas.
1704. wati-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Wati tasks via Rube MCP (Composio). Always search tools first for current schemas.
1705. weather-model-run-discovery sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Resolve the newest complete numerical weather prediction cycle and forecast objects across provider mirrors without downloading full payloads.
1706. weathermap-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Weathermap tasks via Rube MCP (Composio). Always search tools first for current schemas.
1707. webscraping-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Webscraping AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1708. webvizio-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Webvizio tasks via Rube MCP (Composio). Always search tools first for current schemas.
1709. whautomate-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Whautomate tasks via Rube MCP (Composio). Always search tools first for current schemas.
1710. winston-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Winston AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1711. wit-ai-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Wit AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
1712. wiz-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Wiz tasks via Rube MCP (Composio). Always search tools first for current schemas.
1713. wolfram-alpha-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Wolfram Alpha API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1714. woodpecker-co-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Woodpecker co tasks via Rube MCP (Composio). Always search tools first for current schemas.
1715. workable-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Workable tasks via Rube MCP (Composio). Always search tools first for current schemas.
1716. workflow-automation sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Workflow automation is the infrastructure that makes AI agents
1717. workiom-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Workiom tasks via Rube MCP (Composio). Always search tools first for current schemas.
1718. worksnaps-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Worksnaps tasks via Rube MCP (Composio). Always search tools first for current schemas.
1719. writer-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Writer tasks via Rube MCP (Composio). Always search tools first for current schemas.
1720. y-gy-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Y Gy tasks via Rube MCP (Composio). Always search tools first for current schemas.
1721. yandex-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Yandex tasks via Rube MCP (Composio). Always search tools first for current schemas.
1722. yelp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Yelp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1723. ynab-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Ynab tasks via Rube MCP (Composio). Always search tools first for current schemas.
1724. yousearch-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Yousearch tasks via Rube MCP (Composio). Always search tools first for current schemas.
1725. zenrows-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zenrows tasks via Rube MCP (Composio). Always search tools first for current schemas.
1726. zenserp-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zenserp tasks via Rube MCP (Composio). Always search tools first for current schemas.
1727. zeplin-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zeplin tasks via Rube MCP (Composio). Always search tools first for current schemas.
1728. zerobounce-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zerobounce tasks via Rube MCP (Composio). Always search tools first for current schemas.
1729. zipai-optimizer sickn33/antigravity-awesome-skills · score 72/100 (grade C)
      Ultra-dense token optimizer skill for prompt caching, log pruning, AST-based inspection, and minified JSON payloads.
1730. zoho-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zoho tasks via Rube MCP (Composio). Always search tools first for current schemas.
1731. zoho-bigin-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zoho Bigin tasks via Rube MCP (Composio). Always search tools first for current schemas.
1732. zoho-inventory-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zoho Inventory tasks via Rube MCP (Composio). Always search tools first for current schemas.
1733. zoho-invoice-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zoho Invoice tasks via Rube MCP (Composio). Always search tools first for current schemas.
1734. zoho-mail-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zoho Mail tasks via Rube MCP (Composio). Always search tools first for current schemas.
1735. zoominfo-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zoominfo tasks via Rube MCP (Composio). Always search tools first for current schemas.
1736. zylvie-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zylvie tasks via Rube MCP (Composio). Always search tools first for current schemas.
1737. zyte-api-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
      Automate Zyte API tasks via Rube MCP (Composio). Always search tools first for current schemas.
1738. acreadiness-assess github/awesome-copilot · score 71/100 (grade C)
      Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.
1739. acreadiness-generate-instructions github/awesome-copilot · score 71/100 (grade C)
      Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.
1740. agent-workflow-designer alirezarezvani/claude-skills · score 71/100 (grade C)
      Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.
1741. ai-regression-testing affaan-m/ECC · score 71/100 (grade C)
      Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.
1742. ai-regression-testing affaan-m/everything-claude-code · score 71/100 (grade C)
      Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.
1743. android-cli sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Orchestrates Android development tasks including project creation, deployment, SDK management, and environment diagnostics using the `android` command-line tool.
1744. antigravity-agent-manager sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Configure and orchestrate parallel agents using the standalone Antigravity 2.0 Agent Manager and Antigravity IDE.
1745. apigee-agent-gateway-governance google/skills · score 71/100 (grade C)
      Stands up an Apigee API proxy that a Google Cloud Agent Gateway calls as an ext-proc (Service Extension) callout on an agent's LLM traffic, to meter token usage per model, extract caller identity, and apply Model Armor prompt screening or a semantic cache. Use when wiring Apigee in as an AI gateway behind an Agent Gateway, when an agent's model egress needs governing, or when a callout proxy returns no verdict and you need to find out why. The distinguishing question is whether Apigee forwards the traffic or only inspects it: this skill is inspect-only, and builds the proxy itself. Don't use it when Apigee is meant to receive a request and route it onward to a backend — including hosting an MCP server behind Apigee — which needs a proxy with a target instead. Don't use for governing the agent's calls to tools or MCP servers. Don't use for choosing or switching which model a request goes to. Don't use for creating the Agent Gateway itself, nor for Apigee hybrid.
1746. arize-evaluator github/awesome-copilot · score 71/100 (grade C)
      Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.
1747. azure-architecture-autopilot github/awesome-copilot · score 71/100 (grade C)
      Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
1748. azure-pricing github/awesome-copilot · score 71/100 (grade C)
      Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure service, wants to compare SKU prices, needs pricing data for a cost estimate, mentions Azure pricing, Azure costs, Azure billing, or asks about Copilot Studio pricing, Copilot Credits, or agent usage estimation. Covers compute, storage, networking, databases, AI, Copilot Studio, and all other Azure service families.
1749. bb-plugins davidondrej/skills · score 71/100 (grade C)
      Build, install, and debug bb plugins. Use when the user wants a bb plugin, a sidebar panel, a bb CLI subcommand, an agent tool, a theme, a provider, or to extend bb itself. For running threads and the core bb CLI, use bb-cli instead.
1750. bio-differential-splicing GPTomics/bioSkills · score 71/100 (grade C)
      Detects differential alternative splicing between conditions using rMATS-turbo (binomial LRT on junction counts), leafcutter (Dirichlet-multinomial GLM on intron clusters), MAJIQ V3 deltapsi/HET (Bayesian posterior on LSVs), SUPPA2 (empirical-null on TPM-derived PSI), or Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage). Reports FDR-corrected significance and delta PSI effect sizes. Tools differ in statistical model, annotation dependence, calibration regime, and replicate-count requirements. Use when comparing splicing patterns between treatment groups, tissues, or disease states.
1751. bio-ml-docking-rescoring GPTomics/bioSkills · score 71/100 (grade C)
      Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling of when ML beats classical docking, when classical beats ML, the PB-invalid pose problem, and rescoring as the standard production hybrid. Use when modern docking is needed: foundation-model ligand-pose prediction, AI rescoring of classical poses, or scaffold-hopping in cross-docking scenarios.
1752. bio-pathway-kegg-pathways GPTomics/bioSkills · score 71/100 (grade C)
      Tests gene lists, ranked vectors, and fold-change vectors against KEGG pathways and modules with clusterProfiler enrichKEGG/enrichMKEGG (ORA), gseKEGG (GSEA), and SPIA/graphite (signed-topology perturbation) in R. Owns the third pathway-analysis generation because KEGG ships signed directed signaling topology (KGML). Covers why a KEGG result is a timestamped join against a live REST API (irreproducible unless pinned with a gson snapshot, not the stale 2012 KEGG.db), why enrichKEGG keyType is kegg/ncbi-geneid not OrgDb ENSEMBL/SYMBOL (zero hits), why organism is a KEGG code (hsa, pae) with prokaryotic locus tags, and why SPIA works only on signaling maps. Use when finding enriched KEGG pathways or modules, scoring signed pathway perturbation, analyzing prokaryotes or non-model organisms via locus tags or KO, comparing conditions with compareCluster, or overlaying data with pathview. The hypergeometric universe lives in go-enrichment; the GSEA engine in gsea.
1753. bio-workflows-cnv-pipeline GPTomics/bioSkills · score 71/100 (grade C)
      Orchestrates the copy-number pipeline from BAM to segmented, integer-called, annotated CNVs, forking on germline-vs-somatic - CNVkit (somatic exome/panel: coverage -> assay-matched reference/PoN -> fix -> segment -> purity/ploidy-aware call), GATK gCNV (germline rare-CNV cohort), and allele-specific callers (ASCAT/FACETS/PURPLE) for purity/ploidy. Use when committing the build + target/access BED + PoN once (assay-matched), building the reference from normals BEFORE segmenting, fitting purity/ploidy BEFORE integer calls in tumors, centering on the true (non-diploid) mode before GISTIC2 recurrence, or routing cfDNA to ichorCNA. Hands mechanism to the copy-number component skills; not a re-teach of any single step.
1754. bio-workflows-liquid-biopsy-pipeline GPTomics/bioSkills · score 71/100 (grade C)
      Orchestrates the cell-free DNA / liquid-biopsy pipeline from plasma sequencing to tumor monitoring, forking tumor-naive (screening) vs tumor-informed (MRD), and chaining pre-analytic QC, UMI/duplex error-suppression (fgbio), fragment QC, ichorCNA tumor fraction (sWGS) or VarDict low-VAF calling (panel), CHIP subtraction against matched WBC, optional fragmentomics/methylation, and longitudinal tracking. Use when treating pre-analytics as the irreversible sensitivity ceiling (tube/time-to-plasma/hemolysis), running error-suppression BEFORE calling (single-strand consensus does not remove deamination; only duplex does), reporting a VAF only with input genome-equivalents (TF ~ 2x VAF only for clonal-het-diploid), subtracting CHIP before reporting somatic, or keeping tube/panel/pipeline identical across a longitudinal MRD series. Hands mechanism to the liquid-biopsy component skills; not a re-teach of any single step.
1755. bio-workflows-rnaseq-to-de GPTomics/bioSkills · score 71/100 (grade C)
      Orchestrates the end-to-end bulk RNA-seq differential-expression pipeline from FASTQ to an annotated DE gene table, chaining fastp QC/trim, Salmon (decoy-aware) or STAR+featureCounts quantification, tximport gene-level collapse, DESeq2/edgeR/limma-voom testing, apeglm shrinkage, and VST-based visualization. Use when committing the reference release and gene-ID namespace once for the whole run, sequencing steps in the defensible order (tximport before DE, raw counts into the model, VST only for viz/clustering), choosing alignment-free vs align-then-count and the DE engine, setting strandedness correctly, keeping batch in the design instead of correcting-then-testing, or handing the signed ranking statistic to downstream enrichment. Hands mechanism to the component skills; not a re-teach of any single step.
1756. bio-workflows-splicing-pipeline GPTomics/bioSkills · score 71/100 (grade C)
      Orchestrates the end-to-end bulk short-read alternative-splicing pipeline from FASTQ to differential splicing, chaining fastp QC, cohort-consistent STAR 2-pass alignment (one shared junction DB), junction QC, event-level differential splicing (rMATS-turbo + leafcutter, optional MAJIQ V3), parallel isoform-level DTU (Salmon -> tximport dtuScaledTPM -> DRIMSeq/DEXSeq -> stageR), and sashimi visualization. Use when committing the annotation GTF and a shared 2-pass junction database for the whole cohort, keeping the analysis at splice-aware resolution (never collapsing to gene), choosing event-level vs isoform-level DTU and reconciling them, applying the stageR two-stage gene->transcript FDR, or off-ramping to splice-variant / outlier / long-read / single-cell splicing. Hands mechanism to the alternative-splicing component skills; not a re-teach of any single step.
1757. breakdown-feature-implementation github/awesome-copilot · score 71/100 (grade C)
      Prompt for creating detailed feature implementation plans, following Epoch monorepo structure.
1758. bug-hunt-swarm Dimillian/Skills · score 71/100 (grade C)
      Parallel read-only multi-agent root-cause investigation for bugs, regressions, crashes, flaky behavior, or unexplained failures. Use when the user asks to investigate a bug, find the root cause, trace a regression, understand why something broke, or wants a ranked diagnosis with the fastest proof path without making code edits.
1759. capacity-planner alirezarezvani/claude-skills · score 71/100 (grade C)
      Use when an ops leader (Director of CX, Head of Support, VP Ops, Head of BizOps, Head of IT ops, Head of Finance ops) is sizing ops capacity, building a headcount plan, modeling utilization risk, planning Q3 capacity or annual support capacity, or designing CS coverage — and needs Erlang-C queueing math, P90 demand sizing, shrinkage-adjusted FTE, manager-trigger thresholds, and a quarterly hiring sequence with ramp + attrition. Apply when sustained team utilization is above 80% or when the team is growing more than 50% in 12 months. Run before committing the headcount budget. This is NOT engineering capacity (see vpe-advisor for DORA + cycle time) and NOT strategic 3-year workforce planning (see chro-advisor).
1760. cfo-advisor alirezarezvani/claude-skills · score 71/100 (grade C)
      Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash runway, preparing board materials, or when user mentions CFO, burn rate, runway, fundraising, unit economics, LTV, CAC, term sheets, or financial strategy.
1761. chief-customer-officer-advisor alirezarezvani/claude-skills · score 71/100 (grade C)
      Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.
1762. claude-d3js-skill sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      This skill provides guidance for creating sophisticated, interactive data visualisations using d3.js.
1763. config-gc affaan-m/ECC · score 71/100 (grade C)
      Garbage collection for your Claude Code configuration. Periodically scans ~/.claude (skills, memory, hooks, permissions, MCP servers, caches) for redundant, stale, orphaned, or low-value items, then walks the user through a confirm-each-deletion cleanup. Use when the user says "clean up my config", "config GC", "too many skills", "audit my setup", "my .claude is bloated", or asks for a periodic config review.
1764. config-gc affaan-m/everything-claude-code · score 71/100 (grade C)
      Garbage collection for your Claude Code configuration. Periodically scans ~/.claude (skills, memory, hooks, permissions, MCP servers, caches) for redundant, stale, orphaned, or low-value items, then walks the user through a confirm-each-deletion cleanup. Use when the user says "clean up my config", "config GC", "too many skills", "audit my setup", "my .claude is bloated", or asks for a periodic config review.
1765. continuous-learning-v2 affaan-m/ECC · score 71/100 (grade C)
      Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination. Use when capturing lessons from a session, managing instincts, or promoting them into skills, commands, or agents.
1766. continuous-learning-v2 affaan-m/everything-claude-code · score 71/100 (grade C)
      Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination. Use when capturing lessons from a session, managing instincts, or promoting them into skills, commands, or agents.
1767. conventional-branch github/awesome-copilot · score 71/100 (grade C)
      Create Git branches following the Conventional Branch specification (feature/, bugfix/, hotfix/, release/, chore/, plus AI agent prefixes ai/, copilot/, cursor/, claude/, codex/). Use when creating a new branch, naming a branch, or checking whether a branch name complies with the spec.
1768. cs-fullstack-engineer alirezarezvani/claude-skills · score 71/100 (grade C)
      Fullstack-engineering orchestrator. Walks the Matt Pocock 7-question forcing-question grill, runs the deterministic profile picker, then forks into the POWERFUL-tier specialists (api-design-reviewer, ci-cd-pipeline-builder, database-designer, performance-profiler, slo-architect — listed alphabetically; workflow order is dependency-driven) rather than reimplementing their scope. Forks own context so heavy ingestion does not pollute parent thread. Invoke via /cs-fullstack-review or Agent({subagent_type:"cs-fullstack-engineer",...}).
1769. cs-product-analyst alirezarezvani/claude-skills · score 71/100 (grade C)
      Product analytics agent for KPI definition, dashboard setup, experiment design, and test result interpretation. Use when a product question needs numbers — e.g., defining activation/retention KPIs and a dashboard spec for a new feature, or sizing an A/B test and judging whether the result is significant enough to ship.
1770. data-quality-auditor alirezarezvani/claude-skills · score 71/100 (grade C)
      Audit datasets for completeness, consistency, accuracy, and validity. Profile data distributions, detect anomalies and outliers, surface structural issues, and produce an actionable remediation plan. Use when the user asks to check data quality, profile a dataset, hunt outliers or missing values, or validate data before analysis or model training.
1771. docker-patterns affaan-m/ECC · score 71/100 (grade C)
      Docker and Docker Compose patterns for local development, hardened CLI installer harnesses, container security, networking, volumes, and multi-service orchestration. Use when creating or reviewing Dockerfiles and Compose services, testing installers across Linux distributions, or planning accurate native macOS and Windows validation.
1772. docker-patterns affaan-m/everything-claude-code · score 71/100 (grade C)
      Docker and Docker Compose patterns for local development, hardened CLI installer harnesses, container security, networking, volumes, and multi-service orchestration. Use when creating or reviewing Dockerfiles and Compose services, testing installers across Linux distributions, or planning accurate native macOS and Windows validation.
1773. dotnet-backend-patterns sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Master C#/.NET patterns for building production-grade APIs, MCP servers, and enterprise backends with modern best practices (2024/2025).
1774. gemini-api google/skills · score 71/100 (grade C)
      Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.
1775. generate-image github/awesome-copilot · score 71/100 (grade C)
      Generate images using AI. Use when asked to generate, create, or make images, textures, icons, sprites, artwork, visual assets, or mockups. Supports OpenAI (gpt-image-2) and Google Gemini (Nano Banana). Requires an API key for the chosen provider.
1776. google-ads-api-mcp-setup google/skills · score 71/100 (grade C)
      Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve reporting metrics using natural language.
1777. hierarchical-agent-memory sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.
1778. ilya-sutskever sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Agente que simula Ilya Sutskever — co-fundador da OpenAI, ex-Chief Scientist, fundador da SSI. Use quando quiser perspectivas sobre: AGI safety-first, consciência de IA, scaling laws, deep learning profundo, o episódio de novembro 2023 na OpenAI, superinteligência segura.
1779. iterative-retrieval affaan-m/ECC · score 71/100 (grade C)
      Pattern for progressively refining context retrieval to solve the subagent context problem. Use when a subagent lacks the context it needs and retrieval must be refined across passes.
1780. iterative-retrieval affaan-m/everything-claude-code · score 71/100 (grade C)
      Pattern for progressively refining context retrieval to solve the subagent context problem. Use when a subagent lacks the context it needs and retrieval must be refined across passes.
1781. java-mcp-server-generator github/awesome-copilot · score 71/100 (grade C)
      Use this skill when the user wants to create a Model Context Protocol (MCP) server in Java or in a Spring Boot app. Also use it when the user wants AI agents, such as GitHub Copilot or Claude, to use Java code, an API, or a database. Use it even if the user does not say "MCP". The skill makes a Maven or Gradle project with the MCP Java SDK 2.x, tools, JUnit tests, and client configuration. Do not use it for Quarkus/Quarkiverse MCP servers (use the `quarkus-mcp-server-sse` instruction), for an MCP client or for a server in another language.
1782. kubernetes-architect sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Expert Kubernetes architect specializing in cloud-native infrastructure, advanced GitOps workflows (ArgoCD/Flux), and enterprise container orchestration.
1783. landing alirezarezvani/claude-skills · score 71/100 (grade C)
      Generates a premium single-page HTML landing page with 3D CSS animations, GSAP scroll effects, and mouse-parallax depth. Forcing intake (product + elevator pitch, audience register, brand overrides, tone) locks down positioning before any copy or markup is written, so the page reflects the actual product rather than generic boilerplate. Use whenever the user says 'landing for X', 'create a landing page', 'build a landing page', 'make a landing page for X', 'I need a web page for Y', or provides product/service details and wants a polished website. Also triggers on 'promotional page', 'product page', 'one-pager', 'web presence', 'sales page'. Outputs a single self-contained HTML file (Claude Code) or HTML artifact (Claude.ai). Supports configurable brand colors via CSS custom property overrides.
1784. latency-critical-systems affaan-m/ECC · score 71/100 (grade C)
      Optimize and verify latency-sensitive systems — realtime dashboards, market data feeds, streaming agents, execution gateways, queues, and caches — by tracking p50/p95/p99 latency, freshness age, and queue depth, mapping hot paths, and running live readbacks. Use when p95 latency, throughput, or data freshness matters.
1785. latency-critical-systems affaan-m/everything-claude-code · score 71/100 (grade C)
      Optimize and verify latency-sensitive systems — realtime dashboards, market data feeds, streaming agents, execution gateways, queues, and caches — by tracking p50/p95/p99 latency, freshness age, and queue depth, mapping hot paths, and running live readbacks. Use when p95 latency, throughput, or data freshness matters.
1786. lbo-model anthropics/financial-services · score 71/100 (grade C)
      This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.
1787. lookdev-auto sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Automated visual tuning: a vision or video model rates rendered variants in a loop. Render several labeled variants into one artifact, ask the model to rate them and suggest better values, render the suggestions, ask it to pick the best, repeat until good — the model is the eye, you run the loop.
1788. mantis-plan google/mantis · score 71/100 (grade C)
      Formulates a targeted defensive security reviewing plan based on the active threat model and historical learnings. Use when starting a security review campaign to map the codebase boundaries and generate a roadmap (workspace/plan.json). Don't use for executing code reviews, writing test scripts, or patching code.
1789. marketing-psychology sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Apply behavioral science and mental models to marketing decisions, prioritized using a psychological leverage and feasibility scoring system.
1790. mercury-mcp sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Cheatsheet for the Mercury (proton) MCP tools. Use when connected to the Mercury MCP server to look up which mercury_* tool to call for messaging teammates, threads, tasks, automations, or admin team-graph edits.
1791. news-sentiment-engine sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Multi-source RSS news aggregation with Claude-powered sentiment analysis and structured briefing output
1792. nosql-expert sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.
1793. openai-docs openai/skills · score 71/100 (grade C)
      Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
1794. operator-approval-loop affaan-m/ECC · score 71/100 (grade C)
      Operator approval contract with internal filing notices for agent-drafted outbound messages, hashed drafts, epoch-keyed decisions, durable delivery claims and receipts, and a pre-draft baseline gate. Use when an agent drafts messages to external counterparties and a human operator must approve, reject, or steer each send before it leaves.
1795. operator-approval-loop affaan-m/everything-claude-code · score 71/100 (grade C)
      Operator approval contract with internal filing notices for agent-drafted outbound messages, hashed drafts, epoch-keyed decisions, durable delivery claims and receipts, and a pre-draft baseline gate. Use when an agent drafts messages to external counterparties and a human operator must approve, reject, or steer each send before it leaves.
1796. penpot-uiux-design github/awesome-copilot · score 71/100 (grade C)
      Comprehensive guide for creating professional UI/UX designs in Penpot using MCP tools. Use this skill when: (1) Creating new UI/UX designs for web, mobile, or desktop applications, (2) Building design systems with components and tokens, (3) Designing dashboards, forms, navigation, or landing pages, (4) Applying accessibility standards and best practices, (5) Following platform guidelines (iOS, Android, Material Design), (6) Reviewing or improving existing Penpot designs for usability. Triggers: "design a UI", "create interface", "build layout", "design dashboard", "create form", "design landing page", "make it accessible", "design system", "component library".
1797. persistent-localhost davidondrej/skills · score 71/100 (grade C)
      Manage persistent dev servers, APIs, and other local processes on a port using macOS LaunchAgents. Use when starting, stopping, restarting, inspecting, or troubleshooting local servers that should survive shell exit and restart after crashes.
1798. pptx ComposioHQ/awesome-claude-skills · score 71/100 (grade C)
      Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks
1799. prediction-market-risk-review affaan-m/ECC · score 71/100 (grade C)
      Review prediction-market, basket, oracle, and trading-agent workflows for compliance, safety, data-quality, privacy, and execution risk. Use before any workflow handles venue auth, user portfolio data, API keys, or trade planning.
1800. prediction-market-risk-review affaan-m/everything-claude-code · score 71/100 (grade C)
      Review prediction-market, basket, oracle, and trading-agent workflows for compliance, safety, data-quality, privacy, and execution risk. Use before any workflow handles venue auth, user portfolio data, API keys, or trade planning.
1801. prompt-injection briiirussell/cybersecurity-skills · score 71/100 (grade C)
      Audit applications for AI prompt injection, agent security, and LLM permission boundary vulnerabilities. Use when the user mentions 'prompt injection,' 'LLM security,' 'AI security,' 'jailbreak,' 'indirect prompt injection,' 'prompt leaking,' 'AI red team,' 'LLM vulnerabilities,' 'AI input validation,' 'system prompt extraction,' 'agent security,' 'MCP security,' 'AI permissions,' 'AI privilege escalation,' or needs to secure any application with AI features, AI agents, or LLM integrations.
1802. review-swarm Dimillian/Skills · score 71/100 (grade C)
      Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.
1803. ruby-mcp-server-generator github/awesome-copilot · score 71/100 (grade C)
      Generate a complete Model Context Protocol server project in Ruby using the official MCP Ruby SDK gem.
1804. senior-data-engineer alirezarezvani/claude-skills · score 71/100 (grade C)
      Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.
1805. skill-improver Galaxy-Dawn/claude-scholar · score 71/100 (grade C)
      This skill should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality.
1806. stable-baselines3 K-Dense-AI/claude-scientific-skills · score 71/100 (grade C)
      Trains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint normalization. Applies to reproducible RL experiments, continuous control, discrete actions, and SB3-Contrib recurrent or masked policies.
1807. steve-jobs sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Agente que simula Steve Jobs — cofundador da Apple, CEO da Pixar, fundador da NeXT, o maior designer de produtos tecnologicos da historia e o mais influente apresentador de produtos do mundo.
1808. structured-autonomy-generate github/awesome-copilot · score 71/100 (grade C)
      Structured Autonomy Implementation Generator Prompt
1809. swiftui-view-refactor Dimillian/Skills · score 71/100 (grade C)
      Refactor and review SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage. Use when cleaning up a SwiftUI view, splitting long bodies, removing inline actions or side effects, reducing computed `some View` helpers, or standardizing `@Observable` and view model initialization patterns.
1810. using-agent-skills addyosmani/agent-skills · score 71/100 (grade C)
      Discovers and invokes agent skills. Use when starting a session, or when you need to decide which skill or workflow applies to the piece of work at hand. This is the meta-skill that governs how all other skills are discovered and invoked.
1811. video-generation bytedance/deer-flow · score 71/100 (grade C)
      Use this skill when the user requests to generate, create, or imagine videos. Supports structured prompts and reference image for guided generation.
1812. warren-buffett sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Agente que simula Warren Buffett — o maior investidor do seculo XX e XXI, historicamente associado a Berkshire Hathaway, discipulo de Benjamin Graham e socio intelectual de Charlie Munger.
1813. writing-for-agents mattpocock/skills · score 71/100 (grade C)
      Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.
1814. xcode-build-fixer AvdLee/Xcode-Build-Optimization-Agent-Skill · score 71/100 (grade C)
      Apply approved Xcode build optimization changes following best practices, then re-benchmark to verify improvement. Use when a developer has an approved optimization plan from xcode-build-orchestrator, wants to apply specific build fixes, needs help implementing build setting changes, script phase guards, source-level compilation fixes, or SPM restructuring that was recommended by an analysis skill.
1815. yann-lecun-tecnico sickn33/antigravity-awesome-skills · score 71/100 (grade C)
      Sub-skill técnica de Yann LeCun. Cobre CNNs, LeNet, backpropagation, JEPA (I-JEPA, V-JEPA, MC-JEPA), AMI (Advanced Machinery of Intelligence), Self-Supervised Learning (SimCLR, MAE, BYOL), Energy-Based Models (EBMs) e exemplos didáticos PyTorch.
1816. aegisops-ai sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Autonomous DevSecOps & FinOps Guardrails. Guide to reviewing Linux kernel patches, Terraform cost changes and Kubernetes policy with a separately reviewed upstream tool and configured model.
1817. agent-decision-receipts alirezarezvani/claude-skills · score 70/100 (grade C)
      Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion.
1818. agent-harness alirezarezvani/claude-skills · score 70/100 (grade C)
      Turn any domain folder of skills into a bounded agentic loop: compile a goal into a verifiable task plan, execute tasks with the domain's own tools, verify every task with machine-run checks, retry with caps, escalate to a human when budgets exhaust, and refuse to close until everything is verified or explicitly waived. Use when you want an agent or subagent to pick up a goal and drive it to a verified close across one of this repo's 18 domains ('run this goal through the engineering harness', 'set up an agentic loop for marketing work', 'make the finance domain self-verifying'). NOT for authoring Claude Code Workflow-tool .js scripts (workflow-builder), N-agent tournaments on one task (agenthub), single-file metric optimization (autoresearch-agent), or discovering published loop recipes (loop-library).
1819. agent-memory alirezarezvani/claude-skills · score 70/100 (grade C)
      Use when a project's CLAUDE.md has grown past what anyone reads and you want the agent to learn durable facts from its own sessions instead — or when asking why the agent keeps re-learning the same correction, why a remembered rule is wrong, or where a memory line came from. Implements a four-tier store (L0 transcripts / L1 candidates / L2 project context / L3 stable persona) where promotion is earned by recurrence across sessions and days, never by one confident statement, and nothing reaches a committed file without a human adopting it.
1820. agent-orchestrator sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
1821. agent-payment-x402 affaan-m/ECC · score 70/100 (grade C)
      Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk, X Layer through OKX Payments / OKX Agent Payments Protocol, and Solana plus multi-network EVM through the upstream x402 packages with facilitator-based settlement. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.
1822. agent-payment-x402 affaan-m/everything-claude-code · score 70/100 (grade C)
      Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk, X Layer through OKX Payments / OKX Agent Payments Protocol, and Solana plus multi-network EVM through the upstream x402 packages with facilitator-based settlement. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.
1823. agent-platform-eval-flywheel google/skills · score 70/100 (grade C)
      Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when generating synthetic user scenarios, evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.
1824. agent-platform-migrate-from-ai-studio google/skills · score 70/100 (grade C)
      Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).
1825. agent-security-hardening affaan-m/ECC · score 70/100 (grade C)
      Security hardening guidance for AI agent frameworks that process untrusted content, invoke tools, write workspace files, manage runtime identifiers, or handle credentials. Use when building or reviewing an agent runtime, autonomous worker, tool gateway, memory service, or multi-tenant agent deployment. Do not use for general web application security or offensive testing.
1826. agent-security-hardening affaan-m/everything-claude-code · score 70/100 (grade C)
      Security hardening guidance for AI agent frameworks that process untrusted content, invoke tools, write workspace files, manage runtime identifiers, or handle credentials. Use when building or reviewing an agent runtime, autonomous worker, tool gateway, memory service, or multi-tenant agent deployment. Do not use for general web application security or offensive testing.
1827. agent-sort affaan-m/ECC · score 70/100 (grade C)
      Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.
1828. agent-sort affaan-m/everything-claude-code · score 70/100 (grade C)
      Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.
1829. agent-supply-chain github/awesome-copilot · score 70/100 (grade C)
      Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"
1830. ai-product sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Design and evaluate LLM product features, retrieval, validated outputs, latency, and cost controls.
1831. ai-wrapper-product sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Expert in building products that wrap AI APIs (OpenAI, Anthropic,
1832. arize-experiment github/awesome-copilot · score 70/100 (grade C)
      Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.
1833. audit-integrity github/awesome-copilot · score 70/100 (grade C)
      Enforce output quality, evidence verification, and quality gates across security audits. Use this skill when you perform SAST, SCA, threat modeling, or security code reviews. Use this skill to verify code locations and taint traces for all findings. Use this skill to prevent the suppression of valid security findings. Use this skill to evaluate reports against quality thresholds (score ≥ 8/10) before delivery.
1834. baoyu-image-gen JimLiu/baoyu-skills · score 70/100 (grade C)
      AI image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
1835. bio-crispr-screens-jacks-analysis GPTomics/bioSkills · score 70/100 (grade C)
      Runs JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens; Allen et al 2019 Genome Research) which models per-sgRNA log-fold-change as the product of a treatment-dependent gene-essentiality term and a treatment-independent guide-efficacy term. Covers the Bayesian decomposition math, the hierarchical efficacy prior shared across screens performed with the same library, when JACKS outperforms MAGeCK (multi-screen joint analysis, libraries with broad efficacy variance) and when it does not (single screen, novel libraries with no prior efficacy), library-reuse efficacy transfer, downstream essentiality interpretation, and the 2.5x sample-size reduction enabled by efficacy-aware testing. Use when running multiple screens with the same library, when guide-level noise is suspected to dominate per-gene signal, when reusing published essentiality reference screens for efficacy priors, or when comparing screens performed across cell lines that share library but differ biologically.
1836. bio-gatk-variant-calling GPTomics/bioSkills · score 70/100 (grade C)
      Call germline SNPs and indels with GATK HaplotypeCaller and the GVCF joint-genotyping workflow. Covers the local-reassembly + PairHMM mechanism (why HC beats pileup callers on indels), the -ERC GVCF reference-confidence model and <NON_REF> allele, BQSR-vs-DRAGSTR and --dragen-mode error modeling, allele-specific (AS_) annotations, and edge cases (ploidy, Mutect2 mitochondria mode, sex chromosomes/PAR, contamination gating). Use when deciding whether to use HaplotypeCaller vs a pileup or DRAGEN caller, whether BQSR still earns its place, whether to call per-sample GVCFs for a cohort, or how to handle non-diploid, mitochondrial, sex-chromosome, or contaminated samples. Not for post-calling filtering depth (see variant-calling/filtering-best-practices) or cohort joint-genotyping scaling (see variant-calling/joint-calling).
1837. bio-methylation-methylkit GPTomics/bioSkills · score 70/100 (grade C)
      Imports Bismark coverage or cytosine-report files into the methylKit object model, then runs the import-to-results spine - filterByCoverage, normalizeCoverage, unite/destrand, calculateDiffMeth, getMethylDiff - for both per-CpG (DMC) and fixed-tile (DMR) differential methylation, plus tileMethylCounts, PCA/correlation/clustering QC, and assocComp/removeComp batch handling. Covers the silent default traps that shape the false-positive rate: overdispersion='none' does no correction while 'MN' forces the F-test (ignoring test='Chisq'), adjust defaults to SLIM not BH, getMethylDiff defaults difference=25/qvalue=0.01, cov.bases=0 admits single-CpG tiles, and pool destroys biological replication. Use when importing bisulfite count tables, filtering/normalizing/uniting methylation samples, running methylKit differential testing, or QC-ing methylomes. For per-site test-choice (count vs continuous) see differential-cpg-testing; for selection-aware region FDR (dmrseq/DSS) see dmr-detection.
1838. bio-microbiome-differential-abundance GPTomics/bioSkills · score 70/100 (grade C)
      Tests which individual taxa differ between groups on an amplicon ASV/feature table (phyloseq) using compositionally-aware methods - ALDEx2 (Dirichlet-MC CLR, conservative), ANCOM-BC2/ANCOMBC (sampling-fraction bias correction, structural zeros, passed_ss, default p_adj_method=holm), MaAsLin2/MaAsLin3 (multivariable GLM, random effects, prevalence/abundance split), LinDA (CLR mixed-model regression), ZicoSeq (permutation FDR), LEfSe, and q2-composition ancombc. Covers why the hit list depends more on the DA tool than the biology (Nearing benchmark) so the deliverable is a CONSENSUS of >=2 tools, why a relative change is not absolute without a load anchor, the prevalence-filter knob, BH/FDR plus an effect-size floor, and why DESeq2/edgeR misfire here. Use when finding differentially abundant taxa, handling covariates or longitudinal designs, or choosing a method. Whole-community diversity -> diversity-analysis; shotgun DA -> metagenomics/metagenome-visualization; CoDA theory -> metagenomics/abundance-estimation
1839. bio-pharmacophore-modeling GPTomics/bioSkills · score 70/100 (grade C)
      Builds and applies 3D pharmacophore models using RDKit Pharm3D, the apo2ph4 receptor-based workflow (Heider et al. 2023), Pharmer / Pharmit for search, and PharmacoForge for protein-pocket-conditioned pharmacophore generation (Flynn et al. 2025), covering ligand-based pharmacophores from active-set alignment and receptor-based pharmacophores from binding-pocket geometry. Explicitly handles feature types, geometric tolerances, partial matching, and pharmacophore-based virtual screening. Use when identifying scaffold-hopping candidates, building shape-and-feature search queries, or transferring SAR across chemotypes.
1840. bio-qsar-modeling GPTomics/bioSkills · score 70/100 (grade C)
      Builds QSAR / QSPR models using chemprop D-MPNN, MolFormer, Uni-Mol, ChemBERTa, random forest baselines, and Gaussian processes with explicit handling of OECD 5 principles, applicability domain (kNN, leverage, conformal prediction, Mahalanobis), scaffold-balanced splits, ensemble uncertainty, calibration (Platt, isotonic), feature importance (SHAP, atomic attribution), and prospective validation. Use when building target-specific predictive models from in-house bioassay data, ADMET endpoints, or selectivity profiles.
1841. bio-retrosynthesis GPTomics/bioSkills · score 70/100 (grade C)
      Performs retrosynthetic planning using AiZynthFinder (template-based MCTS), maintained or version-pinned template-free models, ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, configurable MCTS rewards, building-block availability, and forward-prediction checks. Use when assessing synthetic feasibility of generated or selected molecules, planning multi-step syntheses, building synthesis-aware design pipelines, or screening libraries for retro-route feasibility.
1842. bio-workflows-fastq-to-variants GPTomics/bioSkills · score 70/100 (grade C)
      Orchestrates the end-to-end germline short-variant pipeline from FASTQ to a filtered, normalized, benchmarked VCF, chaining QC/trim, BWA-MEM2 alignment, duplicate marking, optional BQSR, calling (bcftools/GATK HaplotypeCaller/DeepVariant/DRAGEN), normalization, site+genotype filtering, annotation, and hap.py/vcfeval benchmarking. Use when deciding the pipeline-wide reference-genome commitment (GRCh38 analysis set vs T2T, ALT/decoy handling), sequencing the steps in the defensible order (normalize BEFORE annotate, filter site- then genotype-level), choosing the calling engine and single-sample vs cohort joint-calling, picking a filtering strategy by cohort size, or benchmarking stratified within GIAB confident regions. Hands off mechanism to the variant-calling and read-alignment component skills; not a re-teach of any single step.
1843. bio-workflows-gwas-pipeline GPTomics/bioSkills · score 70/100 (grade C)
      Orchestrates the GWAS pipeline from genotypes to association results, chaining PLINK2 QC (variant-then-sample missingness, controls-only HWE, KING relatedness), panel harmonization + joint phasing/imputation to dosages, long-range-LD-excluded PCA, and an engine chosen by sample structure (PLINK2-GLM / regenie / SAIGE / BOLT-LMM), with LDSC-intercept diagnostics. Use when committing the genome build + ancestry-matched imputation panel once (ancestry match > panel size), running the strand/allele harmonization gate (drop intermediate-frequency palindromes), imputing cases+controls TOGETHER on dosages, excluding long-range-LD regions before PCA, choosing an LMM when relatedness/structure is present (PCs cannot remove a covariance), or separating polygenicity from confounding via the LDSC intercept. Hands mechanism to the population-genetics and phasing-imputation component skills; not a re-teach of any single step.
1844. bio-workflows-scrnaseq-pipeline GPTomics/bioSkills · score 70/100 (grade C)
      Orchestrates the end-to-end single-cell RNA-seq pipeline from 10x Cell Ranger output to annotated cell types, chaining ambient-RNA removal, doublet detection, MAD-adaptive QC, normalization, integration, clustering, marker annotation, and (separately) pseudobulk DE + differential abundance. Use when honoring the made-once counting commitments (reference build/Ensembl vintage, --include-introns, cell-calling, feature namespace), ordering correct-then-detect-then-normalize (ambient before doublet before normalize), running per-sample QC before merge, integrating-then-clustering (never testing on integrated values), aggregating to pseudobulk for condition DE instead of cells-as-replicates, or pairing DE with differential abundance. Hands mechanism to the single-cell component skills; not a re-teach of any single step.
1845. bio-workflows-somatic-variant-pipeline GPTomics/bioSkills · score 70/100 (grade C)
      Chains a somatic (tumor-normal) SNV/indel and structural-variant pipeline end to end with GATK Mutect2 (or Strelka2), wiring the somatic-specific machinery - panel-of-normals and gnomAD germline-resource priors, GetPileupSummaries/CalculateContamination, and LearnReadOrientationModel FFPE/oxoG orientation-bias filtering fed into FilterMutectCalls. Use when calling somatic mutations from a tumor-normal pair (or tumor-only with PoN caveats), deciding which artifact filter removes which class of false positive, reasoning about VAF/purity/ploidy and clonal-vs-subclonal detection, adding somatic SV/CNV or TMB/MSI/signatures, or routing variants to AMP/ASCO/CAP tier and oncogenicity interpretation (never germline ACMG).
1846. bootstrap bytedance/deer-flow · score 70/100 (grade C)
      Generate a personalized SOUL.md through a warm, adaptive onboarding conversation. Trigger when the user wants to create, set up, or initialize their AI partner's identity — e.g., "create my SOUL.md", "bootstrap my agent", "set up my AI partner", "define who you are", "let's do onboarding", "personalize this AI", "make you mine", or when a SOUL.md is missing. Also trigger for updates: "update my SOUL.md", "change my AI's personality", "tweak the soul".
1847. brand-guidelines alirezarezvani/claude-skills · score 70/100 (grade C)
      When the user wants to apply, document, or enforce brand guidelines for any product or company. Also use when the user mentions 'brand guidelines,' 'brand colors,' 'typography,' 'logo usage,' 'brand voice,' 'visual identity,' 'tone of voice,' 'brand standards,' 'style guide,' 'brand consistency,' or 'company design standards.' Covers color systems, typography, logo rules, imagery guidelines, and tone matrix for any brand — including Anthropic's official identity.
1848. business-analyst sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.
1849. caveman-setup JuliusBrussee/caveman · score 70/100 (grade C)
      Wire a repository through the Caveman Cloud gateway so every LLM request is measured, with no behavior change. Use for "set up caveman" or adding LLM spend observability.
1850. cco-review alirezarezvani/claude-skills · score 70/100 (grade C)
      /c-level-agents:cco-review [plan] — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when deciding which customer segments to keep or fire.
1851. cdo-review alirezarezvani/claude-skills · score 70/100 (grade C)
      /c-level-agents:cdo-review [plan] — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data productization, or data team hiring. Use when validating training-data rights before model work, choosing warehouse vs lakehouse vs mesh, or valuing data assets for productization or M&A.
1852. cfo-review alirezarezvani/claude-skills · score 70/100 (grade C)
      /c-level-agents:cfo-review [plan] — Numerate-skeptic interrogation of any plan that touches money. Unit economics, runway, dilution, capital allocation. Use when a plan commits meaningful spend — e.g. a hiring wave, a fundraise decision, or a new channel budget.
1853. claude-speed-reader sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      -Speed read Claude's responses at 600+ WPM using RSVP with Spritz-style ORP highlighting
1854. cloud-monitoring-notification-channels-configuration google/skills · score 70/100 (grade C)
      Generates Terraform HCL configurations for Cloud Monitoring notification channels (`google_monitoring_notification_channel`) and adds notification channels to alerting policies (`google_monitoring_alert_policy`) in Google Cloud projects. Use when creating or configuring email, SMS, Slack, PagerDuty, Pub/Sub, or webhook notification channels, verifying Pub/Sub topic compatibility (including cross-project topics, message storage policies, and in-transit enforcement) and publishing permissions for the Cloud Monitoring Service Agent, or adding notification channels to existing alert policies. Don't use for authoring or editing alerting policy conditions, selecting metric descriptors, or writing PromQL or Monitoring Filter queries.
1855. code-review-and-quality addyosmani/agent-skills · score 70/100 (grade C)
      Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.
1856. competitive-teardown alirezarezvani/claude-skills · score 70/100 (grade C)
      Analyzes competitor products and companies by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices scored across 12 dimensions, SWOT analyses, positioning maps, UX audits, pricing model breakdowns, action item roadmaps, and stakeholder presentation templates. Use when conducting competitor analysis, comparing products against competitors, researching the competitive landscape, building battle cards for sales, preparing for a product strategy or roadmap session, responding to a competitor's new feature or pricing change, or performing a quarterly competitive review.
1857. computer-vision-expert sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Computer vision pipeline design and evaluation. Specialized in YOLO26, Segment Anything 3 (SAM 3), Vision Language Models, and real-time spatial analysis.
1858. conventional-commit github/awesome-copilot · score 70/100 (grade C)
      Prompt and workflow for generating conventional commit messages using a structured XML format. Guides users to create standardized, descriptive commit messages in line with the Conventional Commits specification, including instructions, examples, and validation.
1859. cs-senior-engineer alirezarezvani/claude-skills · score 70/100 (grade C)
      Senior Engineer agent for architecture decisions, code review, DevOps, and API design. Orchestrates engineering and engineering-team skills for technical implementation work. Spawn when users need system design, code quality review, CI/CD pipeline setup, or infrastructure decisions.
1860. dbt-sf-to-bq-translator google/skills · score 70/100 (grade C)
      Translates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to BigQuery on Google Cloud. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.
1861. deep-research Imbad0202/academic-research-skills · score 70/100 (grade C)
      Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, WHY HOW WHAT papers, 3W literature scan, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 三段式文獻掃描, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題, 심층 연구, 문헌 조사, 체계적 문헌고찰, 메타분석, 사실 확인, 연구 방향을 잡아줘, 연구 주제 정하는 것을 도와줘, revisión de literatura, metaanálisis
1862. design-orchestration sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order.
1863. fal-audio sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Text-to-speech and speech-to-text using fal.ai audio models
1864. finding-google-skills google/skills · score 70/100 (grade C)
      Google platform decision and setup guidance, loaded on demand from Google's skill catalog. Use when a developer is choosing or setting up part of their stack, such as where to run a service, a database, storage, messaging, authentication, analytics, ads, or AI model serving, and a Google product is a reasonable candidate - whether or not a vendor is named - or when a request names a Google product or API. Brings in the matching Google skill so the answer can weigh Google options, their trade-offs, and when they are not the right fit. Skip when the stack is already settled on another provider and no Google product is named, or the task involves no platform choice.
1865. foundry-hosted-agent-copilotkit github/awesome-copilot · score 70/100 (grade C)
      Build and evolve agentic web apps that pair a CopilotKit React frontend with a Microsoft Agent Framework agent running as a Microsoft Foundry hosted agent, connected over the AG-UI protocol. Covers choosing the wiring, using Foundry-native primitives instead of hand-rolled plumbing, agent tools, human-in-the-loop approvals, generative UI and shared state, local run and azd deploy, debugging the event stream, and safe upgrades.
1866. gateguard affaan-m/ECC · score 70/100 (grade C)
      PreToolUse fact-forcing gate that denies the first Edit/Write/Bash (including MultiEdit and NotebookEdit) attempt until the agent presents concrete facts (importers, data schemas, verbatim user instruction), then allows retry; A/B-tested at +2.25 quality points. Use when enabling or configuring the GateGuard hook, exempting paths via env vars, or handling first-touch denials.
1867. gateguard affaan-m/everything-claude-code · score 70/100 (grade C)
      PreToolUse fact-forcing gate that denies the first Edit/Write/Bash (including MultiEdit and NotebookEdit) attempt until the agent presents concrete facts (importers, data schemas, verbatim user instruction), then allows retry; A/B-tested at +2.25 quality points. Use when enabling or configuring the GateGuard hook, exempting paths via env vars, or handling first-touch denials.
1868. google-cloud-solution-agentic-ai-data-science-workflow google/skills · score 70/100 (grade C)
      Designs a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code.
1869. herdr davidondrej/skills · score 70/100 (grade C)
      Operate and coordinate AI agents in Herdr workspaces in Ghostty. Use when the user mentions Herdr or asks to inspect, message, wait for, or coordinate its agents. Excludes cmux and ordinary terminal sessions.
1870. hivemind alirezarezvani/claude-skills · score 70/100 (grade C)
      Orchestrate free opencode workers from Claude Code to cut token costs. Use when delegating grunt work to a single worker or a parallel swarm (scout/coder/tester) with worktree isolation, benchmarking against opencode, or when the user says "spawn a worker", "swarm", "delegate to opencode", or "/oc".
1871. hub-init alirezarezvani/claude-skills · score 70/100 (grade C)
      Create a new AgentHub collaboration session with task, agent count, and evaluation criteria. Use when the user runs /hub:hub-init or asks to start a multi-agent competition on a task.
1872. intent-driven-development affaan-m/ECC · score 70/100 (grade C)
      Turn ambiguous or high-impact product and engineering changes into scoped, verifiable acceptance criteria before or alongside implementation. Use when a user asks to clarify a feature, define acceptance criteria, de-risk a security/data/migration/integration change, prepare implementation requirements for another agent, or make a complex request testable. Do not trigger for trivial edits, straightforward fixes, active debugging, code review, or implementation requests whose acceptance conditions are already clear unless the user explicitly invokes this skill.
1873. intent-driven-development affaan-m/everything-claude-code · score 70/100 (grade C)
      Turn ambiguous or high-impact product and engineering changes into scoped, verifiable acceptance criteria before or alongside implementation. Use when a user asks to clarify a feature, define acceptance criteria, de-risk a security/data/migration/integration change, prepare implementation requirements for another agent, or make a complex request testable. Do not trigger for trivial edits, straightforward fixes, active debugging, code review, or implementation requests whose acceptance conditions are already clear unless the user explicitly invokes this skill.
1874. interview alirezarezvani/claude-skills · score 70/100 (grade C)
      Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives table + v1/v2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says "help me scope an agent", "I have an idea for an agent", "what should this agent be", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into payloads).
1875. laravel-plugin-discovery affaan-m/ECC · score 70/100 (grade C)
      Discover and evaluate Laravel packages via LaraPlugins.io MCP. Use when the user wants to find plugins, check package health, or assess Laravel/PHP compatibility.
1876. laravel-plugin-discovery affaan-m/everything-claude-code · score 70/100 (grade C)
      Discover and evaluate Laravel packages via LaraPlugins.io MCP. Use when the user wants to find plugins, check package health, or assess Laravel/PHP compatibility.
1877. local-llm-expert sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
1878. marketing-psychology alirezarezvani/claude-skills · score 70/100 (grade C)
      When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
1879. mcp-create-declarative-agent github/awesome-copilot · score 70/100 (grade C)
      Skill converted from mcp-create-declarative-agent.prompt.md
1880. mcp-deploy-manage-agents github/awesome-copilot · score 70/100 (grade C)
      Skill converted from mcp-deploy-manage-agents.prompt.md
1881. memory-engineering alirezarezvani/claude-skills · score 70/100 (grade C)
      Use when designing, reviewing, or paying for an agent memory system — adding memory to an agent, choosing between long-context / RAG / graph / agentic memory, auditing what a CLAUDE.md or memory directory actually holds, deciding what to keep and what to expire, or when a memory store keeps growing and nobody has said what leaves it. Prices the write path, picks which cost to pay, classifies records as facts / skills / logs, and refuses a design that has no forgetting policy.
1882. odoo-rpc-api sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Expert on Odoo's external JSON-RPC and XML-RPC APIs. Covers authentication, model calls, record CRUD, and real-world integration examples in Python, JavaScript, and curl.
1883. orch-pipeline affaan-m/ECC · score 70/100 (grade C)
      Shared orchestration engine behind the orch-* skill family — the gated Research-Plan-TDD-Review-Commit pipeline, size classifier, agent and command map, and two human gates (plan approval, commit confirmation) that orch-* operation skills delegate to. Use indirectly via orch-add-feature, orch-fix-defect, orch-change-feature, orch-refine-code, or orch-build-mvp; read directly only when adding an orch operation or tuning shared phases.
1884. orch-pipeline affaan-m/everything-claude-code · score 70/100 (grade C)
      Shared orchestration engine behind the orch-* skill family — the gated Research-Plan-TDD-Review-Commit pipeline, size classifier, agent and command map, and two human gates (plan approval, commit confirmation) that orch-* operation skills delegate to. Use indirectly via orch-add-feature, orch-fix-defect, orch-change-feature, orch-refine-code, or orch-build-mvp; read directly only when adding an orch operation or tuning shared phases.
1885. osterwalder-canvas-architect sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Iterative consultant agent for building and validating logically consistent 9-block Business Model Canvases.
1886. power-bi-performance-troubleshooting github/awesome-copilot · score 70/100 (grade C)
      Systematic Power BI performance troubleshooting prompt for identifying, diagnosing, and resolving performance issues in Power BI models, reports, and queries.
1887. power-bi-report-design-consultation github/awesome-copilot · score 70/100 (grade C)
      Power BI report visualization design prompt for creating effective, user-friendly, and accessible reports with optimal chart selection and layout design.
1888. pricing-strategy alirezarezvani/claude-skills · score 70/100 (grade C)
      Design, optimize, and communicate SaaS pricing — tier structure, value metrics, pricing pages, and price increase strategy. Use when building a pricing model from scratch, redesigning existing pricing, planning a price increase, or improving a pricing page. Trigger keywords: pricing tiers, pricing page, price increase, packaging, value metric, per seat pricing, usage-based pricing, freemium, good-better-best, pricing strategy, monetization, pricing page conversion, Van Westendorp. NOT for broader product strategy — use product-strategist for that. NOT for customer success or renewals — use customer-success-manager for expansion revenue.
1889. recursive-decision-ledger affaan-m/ECC · score 70/100 (grade C)
      Run repeated rollouts ("Prime Gauss" style recursive prompting) while keeping an append-only decision ledger of trials, marks, coherence checks, and promotion gates, so recursive confidence never auto-approves live trading, deploy, or destructive actions. Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.
1890. recursive-decision-ledger affaan-m/everything-claude-code · score 70/100 (grade C)
      Run repeated rollouts ("Prime Gauss" style recursive prompting) while keeping an append-only decision ledger of trials, marks, coherence checks, and promotion gates, so recursive confidence never auto-approves live trading, deploy, or destructive actions. Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.
1891. rust-mcp-server-generator github/awesome-copilot · score 70/100 (grade C)
      Generate a complete Rust Model Context Protocol server project with tools, prompts, resources, and tests using the official rmcp SDK
1892. salesforce-apex-quality github/awesome-copilot · score 70/100 (grade C)
      Apex code quality guardrails for Salesforce development. Enforces bulk-safety rules (no SOQL/DML in loops), sharing model requirements, CRUD/FLS security, SOQL injection prevention, PNB test coverage (Positive / Negative / Bulk), and modern Apex idioms. Use this skill when reviewing or generating Apex classes, trigger handlers, batch jobs, or test classes to catch governor limit risks, security gaps, and quality issues before deployment.
1893. search-first affaan-m/ECC · score 70/100 (grade C)
      Research-before-coding workflow: search npm/PyPI, MCP servers, skills, and GitHub for existing tools before writing custom code, then adopt, extend, or build. Launches the researcher agent for non-trivial needs. Use when starting a feature, adding a dependency or integration, or about to write a utility that may already exist.
1894. search-first affaan-m/everything-claude-code · score 70/100 (grade C)
      Research-before-coding workflow: search npm/PyPI, MCP servers, skills, and GitHub for existing tools before writing custom code, then adopt, extend, or build. Launches the researcher agent for non-trivial needs. Use when starting a feature, adding a dependency or integration, or about to write a utility that may already exist.
1895. shopify-review-triage github/awesome-copilot · score 70/100 (grade C)
      Use this skill when someone wants public Shopify App Store reviews, low-star reviews, or merchant feedback triaged, prioritized, clustered, or turned into a product or support brief. Trigger for prompts like "triage these app store reviews", "what should we fix first from this feedback", "cluster our 1-star reviews", or "write a weekly low-star review brief", for a single Shopify app or a portfolio plus watched competitors. Produces a P0-P3 brief covering incident risk, repeated friction, pricing confusion, feature requests, and an explicit needs-human-read bucket, where every item keeps its public source link and stays labeled first pass or human-checked. Do not trigger for support tickets, order data, or any other private merchant data, and never use it to reply to or contact a reviewer.
1896. skill-host-compat affaan-m/ECC · score 70/100 (grade C)
      Lint ECC skills for Codex/Cursor-safe frontmatter and Claude-only substitutions before a skill PR.
1897. skill-host-compat affaan-m/everything-claude-code · score 70/100 (grade C)
      Lint ECC skills for Codex/Cursor-safe frontmatter and Claude-only substitutions before a skill PR.
1898. skill-security-auditor alirezarezvani/claude-skills · score 70/100 (grade C)
      Security audit and vulnerability scanner for AI agent skills before installation. Use when: (1) evaluating a skill from an untrusted source, (2) auditing a skill directory or git repo URL for malicious code, (3) pre-install security gate for Claude Code plugins, OpenClaw skills, or Codex skills, (4) scanning Python scripts for dangerous patterns like os.system, eval, subprocess, network exfiltration, (5) detecting prompt injection in SKILL.md files, (6) checking dependency supply chain risks, (7) verifying file system access stays within skill boundaries. Triggers: "audit this skill", "is this skill safe", "scan skill for security", "check skill before install", "skill security check", "skill vulnerability scan".
1899. skill-stocktake affaan-m/ECC · score 70/100 (grade C)
      Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
1900. skill-stocktake affaan-m/everything-claude-code · score 70/100 (grade C)
      Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
1901. tear-sheet anthropics/financial-services · score 70/100 (grade C)
      Generate professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise single-company financial summary. This skill supports four audience types: equity research, investment banking/M&A, corporate development, and sales/business development. If the user doesn't specify an audience, ask. Works for both public and private companies.
1902. threat-modeling-expert sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Expert in threat modeling methodologies, security architecture review, and risk assessment. Masters STRIDE, PASTA, attack trees, and security requirement extraction. Use PROACTIVELY for security architecture reviews, threat identification, or building secure-by-design systems.
1903. total-review davidondrej/skills · score 70/100 (grade C)
      Run five independent max-effort reviews (Fable 5.1, Opus 5.5, GPT-6 Astra, GPT-6.1 Sol, Muse Wonder), merge their findings, and fix only what the user approves. Manual only: run when a human types /total-review; agents must never invoke it on their own.
1904. understand-knowledge Egonex-AI/Understand-Anything · score 70/100 (grade C)
      Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.
1905. varlock-claude-skill sickn33/antigravity-awesome-skills · score 70/100 (grade C)
      Secure environment variable management with explicit checks to reduce secret exposure in Claude sessions, terminals, logs, or git commits
1906. vpe-review alirezarezvani/claude-skills · score 70/100 (grade C)
      /c-level-agents:vpe-review [plan] — Throughput-first VP of Engineering interrogation of any plan that touches delivery, eng hiring, team structure, or production discipline. Use when cycle time balloons, DORA metrics slide, or before committing to an eng hiring wave or a reorg.
1907. wizard mattpocock/skills · score 70/100 (grade C)
      Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.
1908. workload-manager-basics google/skills · score 70/100 (grade C)
      Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.
1909. wrap-up alirezarezvani/claude-skills · score 70/100 (grade C)
      Close out a launched Claude Managed Agent — recap every primitive the founder now owns, regenerate the single-file overview page, and suggest the next 1-2 upgrades. Use when the user says "wrap up", "close this out", "what do I own now", "give me the summary", "recap the agent", or when the orchestrator routes phase=wrap-up. primitives_inventory.py tables everything owned (agent, environment, session, memory, outcome, deployment); overview_page.py regenerates a self-contained ./my-agent/agent-overview.html; upgrade_suggester.py ranks the next moves from recorded deferrals plus standing hardening steps. Companion to run-without-you; the last stop before phase=done.
1910. write-coding-standards-from-file github/awesome-copilot · score 70/100 (grade C)
      Write a coding standards document for a project using the coding styles from the file(s) and/or folder(s) passed as arguments in the prompt.
1911. aas-compose-stack sickn33/antigravity-awesome-skills · score 69/100 (grade C)
      Preserve the coding agent's explicit AAS skill selection as a validated stack and optional evidence.
1912. agent-designer alirezarezvani/claude-skills · score 69/100 (grade C)
      Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
1913. agent-launcher-orchestrator alirezarezvani/claude-skills · score 69/100 (grade C)
      Use when a user wants to build, launch, grade, or schedule a Claude Managed Agent (CMA) in their own Anthropic account — "build me an agent", "launch this as a managed agent", "run this on a schedule", "grade my agent against a rubric", "set up a nightly worker". Reads the per-session goal (./my-agent/goal.json), routes deterministically to one of five phase sub-skills (interview → stage-launch → grade-iterate → run-without-you → wrap-up) via goal_router.py, and compiles the goal+phase into an execution shape (single-pass workflow / bounded grade→iterate loop / recurring cron deployment loop) via loop_compiler.py. Forks context so heavy intake (build sheets, payloads, eval cases) stays out of the parent thread. All launches are emitted as BYOK curl the user runs with their own key; no tool makes API calls. Inspired by anthropics/launch-your-agent (Apache-2.0). Distinct from engineering/agent-harness (generic domain loop) and engineering/write-a-skill (authors Claude Code skills, not CMAs).
1914. agent-platform-skill-registry google/skills · score 69/100 (grade C)
      Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.
1915. agentic-eval github/awesome-copilot · score 69/100 (grade C)
      Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
1916. arize-trace github/awesome-copilot · score 69/100 (grade C)
      Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.
1917. arquiteto-de-empresa alirezarezvani/claude-skills · score 69/100 (grade C)
      Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md/log.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, few questions per block, and generates the concepts as conformant markdown. Trigger when the user wants to create, structure, or document an entire company in folders and .md files; when they mention build my company from scratch, company as code, company knowledge base for AI to read, company wiki for agents, OKF, or knowledge bundle. In English.
1918. baoyu-danger-gemini-web JimLiu/baoyu-skills · score 69/100 (grade C)
      Generates images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation", or needs vision-capable AI generation.
1919. bdistill-behavioral-xray sickn33/antigravity-awesome-skills · score 69/100 (grade C)
      X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed.
1920. bio-crispr-screens-batch-correction GPTomics/bioSkills · score 69/100 (grade C)
      Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.
1921. bio-data-visualization-genome-tracks GPTomics/bioSkills · score 69/100 (grade C)
      Build genome-browser-style multi-track figures with pyGenomeTracks (config-driven), Gviz (R), and IGV batch screenshotting. Covers BigWig coverage tracks, BED/peak overlays, gene-model rendering, Hi-C matrix tracks, BedPE link arcs, spike-in-aware normalization, and the bamCoverage --normalizeUsing trap. Use when producing publication figures of genomic loci with stacked aligned tracks (coverage, peaks, genes, interactions) for ChIP-seq, ATAC-seq, RNA-seq, Hi-C, or generic locus visualization.
1922. bio-flow-cytometry-differential-analysis GPTomics/bioSkills · score 69/100 (grade C)
      Differential abundance (DA) and differential state (DS) analysis for flow and mass cytometry - tests which cell populations change in frequency or marker expression between conditions using diffcyt (edgeR/voom/GLMM for DA, limma/LMM for DS), with cydar, CITRUS, and compositional methods (sccomp, scCODA, DCATS) as alternatives. Covers the sample-is-the-experimental-unit principle, design/contrast and mixed-model formulas, compositionality of cluster proportions, and FDR across clusters. Use when comparing populations between groups, choosing a DA method, handling paired/batch designs, or deciding whether compositional correction is needed.
1923. bio-genome-intervals-gtf-gff-handling GPTomics/bioSkills · score 69/100 (grade C)
      Parses, queries, converts, and extracts from GTF and GFF3 gene-model annotation files - walking the gene/transcript/exon/CDS hierarchy with gffutils (queryable SQLite DB), converting formats and extracting transcript/CDS/protein FASTA with gffread, slurping to dataframes with gtfparse/pyranges, and sanitizing malformed files with AGAT. Covers the 1-based-inclusive vs 0-based BED coordinate conversion (start-1 only), deriving implicit features (introns/UTRs/TSS), phase-not-frame, the stop-codon-in-or-out-of-CDS convention, and the chr1-vs-1 seqid and gene-ID-version mismatches that silently produce all-zero count matrices and dropped joins. Use when extracting features or sequences from an annotation, converting GTF<->GFF3 or GTF->BED, traversing the gene tree, or diagnosing a coordinate/provenance mismatch upstream of counting or DE.
1924. bio-metabolomics-statistical-analysis GPTomics/bioSkills · score 69/100 (grade C)
      Decision-grade statistical analysis for metabolomics intensity tables. Covers transformation and scaling (Pareto vs unit-variance as a hidden hypothesis), unsupervised structure (PCA/HCA for QC), permutation-validated PLS-DA/OPLS-DA (R2 vs Q2, double CV, VIP as heuristic), univariate testing (Welch/Mann-Whitney/ANOVA/LMM with covariate adjustment), and dependence-aware multiple testing. Use when testing which metabolites differ, building or validating a discriminant model, choosing a scaling, or correcting many correlated tests. For sample-wise normalization/drift correction see metabolomics/normalization-qc; for ML classifiers and selection-inside-CV leakage see machine-learning/biomarker-discovery and machine-learning/model-validation; for pathway interpretation see metabolomics/pathway-mapping; for design/power/multiplicity regime see experimental-design/multiple-testing.
1925. bio-metagenomics-contamination-controls GPTomics/bioSkills · score 69/100 (grade C)
      Cleans a shotgun metagenome of everything that is not the target community before profiling - host-read depletion (Hostile, bowtie2/T2T-CHM13), reagent/kitome contamination control with blanks and decontam, mock-community validation, and depth-adequacy checks (Nonpareil). Covers why a metagenomic result is a position in a choice-chain rather than a direct observation, why extraction is the experiment, why a low-biomass community can be entirely kitome, why absence means not-detectable-by-this-chain, and why a confident classifier call can still be wrong when the reference is contaminated. Use when designing controls, removing host reads, identifying reagent contaminants, validating with mocks, or judging whether a low-biomass result is real. For adapter/quality trimming see read-qc; for MAG-level decontamination see genome-assembly/metagenome-assembly.
1926. bio-multi-omics-mofa-integration GPTomics/bioSkills · score 69/100 (grade C)
      Discovers shared and view-specific latent factors across bulk multi-omics blocks (RNA-seq, proteomics, methylation) on a common sample axis with MOFA2's unsupervised Bayesian group factor model, then attributes per-view variance explained and interprets signed factor weights. Covers why a factor is an unsupervised axis of variance and not a pathway, why a factor that correlates with batch is a batch factor, why the per-view variance-explained table is the primary read-out rather than p-values, why raw counts in a Gaussian view make factor 1 the library-size factor, and why MOFA2 handles missing omics-per-sample natively. Use when integrating two or more bulk omics to find joint axes of variation, choosing factor count, labeling factors against metadata, or running enrichment on factor weights. For supervised discriminant integration see mixomics-analysis; for the method decision see integration-design; for single-cell see single-cell/multimodal-integration; for enrichment see pathway-analysis/gsea.
1927. bio-single-cell-perturb-seq GPTomics/bioSkills · score 69/100 (grade C)
      Analyze Perturb-seq / CROP-seq single-cell CRISPR screens. Use when assigning guides as a mixture problem, removing non-perturbed escaper cells with Mixscape, choosing a calibrated test (SCEPTRE conditional resampling) over naive DE, quantifying effect size with E-distance, separating compositional shifts from within-state expression change, or judging whether a perturbation-prediction foundation model actually beats a baseline.
1928. bio-workflow-management-snakemake-workflows GPTomics/bioSkills · score 69/100 (grade C)
      Authors reproducible bioinformatics pipelines with Snakemake - rules wired by output-file pattern, wildcards and expand() for sample fan-out, checkpoints for runtime-unknown outputs, resource/retry escalation, and conda/container software deployment on HPC and cloud. Use when deciding rule-based (Snakemake) vs channel/dataflow (Nextflow) authoring; wiring rules by OUTPUT-file pattern rather than imperative order; using wildcards + expand() for sample fan-out and constraining them to stop silent mis-routing; adding checkpoints when the set of outputs is unknown until a step runs (dynamic DAG); diagnosing why a job reran (or did not) under the mtime-plus-provenance trigger set; escalating memory on retry for OOM-killed jobs; and porting a Snakemake 7 `--cluster`/remote-provider command to the Snakemake 8+ executor-plugin and storage-plugin model (snakemake-executor-plugin-slurm) with `--software-deployment-method`.
1929. bio-workflows-atacseq-pipeline GPTomics/bioSkills · score 69/100 (grade C)
      Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5 +4/-5 shift, MACS3 peak calling, Corces fixed-width consensus, DiffBind/csaw differential accessibility, and TOBIAS footprinting. Use when committing the reference build + blacklist once, recognizing ATAC has NO input control (the shift-extend model IS the background), applying the Tn5 shift exactly once (never combining -f BAMPE with --shift/--extsize), removing chrM before calling, building a fixed-width consensus so per-sample counts are comparable, or choosing MACS3 vs Genrich vs HMMRATAC. Hands mechanism to the atac-seq component skills; not a re-teach of any single step.
1930. bio-workflows-causal-genomics-pipeline GPTomics/bioSkills · score 69/100 (grade C)
      End-to-end post-GWAS causal inference pipeline orchestrating heritability partitioning, genetic correlation, Mendelian randomization with CHP-aware sensitivity (CAUSE / LHC-MR), colocalization, fine-mapping with SuSiE / FOCUS, mediation, TWAS triangulation, cis-pQTL drug-target MR, effector-gene prioritization (L2G / PoPS / cS2G), and GenomicSEM common-factor GWAS. Use when triangulating causal inference across multiple complementary methods, prioritizing tissues via stratified LDSC, nominating or de-risking drug targets, mapping a lead SNP to a candidate effector gene, modeling shared genetic architecture across correlated traits, or producing a STROBE-MR-compliant publication-grade evidence battery from GWAS summary statistics.
1931. bio-workflows-spatial-pipeline GPTomics/bioSkills · score 69/100 (grade C)
      Orchestrates the end-to-end spatial transcriptomics pipeline from Space Ranger / vendor output to spatial domains and statistics, branching FIRST on platform class (imaging in-situ Xenium/MERFISH/CosMx vs sequencing/capture Visium/Visium HD/Slide-seq). Use when deciding segmentation-vs-deconvolution and the QC floors from the platform class, committing the coordinate/image-registration frame and panel identity, deconvolving multi-cell spots against an annotated scRNA reference (never relabeling spot clusters as cell types), building the spatial neighbor graph on PHYSICAL not expression space, gating spatially-variable genes on FDR, or using a real domain method (BANKSY/BayesSpace/STAGATE) rather than clustering the spatial graph alone. Hands off deconvolution and cell-cell communication to the component skills; not a re-teach of any single step.
1932. blueprint affaan-m/ECC · score 69/100 (grade C)
      Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects: one-PR-sized steps with self-contained context briefs, dependency graph with parallel-step detection, adversarial review gate, and plan mutation protocol. Use when planning a large feature, refactor, or roadmap that spans multiple PRs or sessions; not for single-PR tasks or when the user says \"just do it\".
1933. blueprint affaan-m/everything-claude-code · score 69/100 (grade C)
      Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects: one-PR-sized steps with self-contained context briefs, dependency graph with parallel-step detection, adversarial review gate, and plan mutation protocol. Use when planning a large feature, refactor, or roadmap that spans multiple PRs or sessions; not for single-PR tasks or when the user says \"just do it\".
1934. breakdown-feature-prd github/awesome-copilot · score 69/100 (grade C)
      Prompt for creating Product Requirements Documents (PRDs) for new features, based on an Epic.
1935. breakdown-plan github/awesome-copilot · score 69/100 (grade C)
      Issue Planning and Automation prompt that generates comprehensive project plans with Epic > Feature > Story/Enabler > Test hierarchy, dependencies, priorities, and automated tracking.
1936. caveman-evidence-review JuliusBrussee/caveman · score 69/100 (grade C)
      Read-only review of Caveman Cloud evidence: cost, Cave Score, workflows, traces, latency, errors, routing, savings. Use when asked what Caveman found or where LLM spend goes.
1937. claude-scientific-skills sickn33/antigravity-awesome-skills · score 69/100 (grade C)
      Scientific research and analysis skills
1938. content-management-systems github/awesome-copilot · score 69/100 (grade C)
      Workflow for building and modifying content management systems across WordPress, Shopify, Wix, Squarespace, Drupal, WooCommerce, Joomla, HubSpot CMS Hub, Webflow, Adobe Experience Manager, and similar platforms. Use when working on CMS themes, plugins, apps, modules, admin panels, media uploads, content models, editors, markdown pipelines, or static export workflows.
1939. cost-tracking affaan-m/ECC · score 69/100 (grade C)
      Track and report Claude Code token usage, spending, and budgets from the local ECC cost-tracker metrics log. Use when the user asks about costs, spending, usage, tokens, budgets, or cost breakdowns by model, session, or date.
1940. cost-tracking affaan-m/everything-claude-code · score 69/100 (grade C)
      Track and report Claude Code token usage, spending, and budgets from the local ECC cost-tracker metrics log. Use when the user asks about costs, spending, usage, tokens, budgets, or cost breakdowns by model, session, or date.
1941. cto-review alirezarezvani/claude-skills · score 69/100 (grade C)
      /c-level-agents:cto-review [plan] — Architecture and scaling interrogation. Tech debt, scaling cliffs, team scaling, build-vs-buy. Use when committing to an architecture, planning for 10x load, or weighing a rebuild against a vendor.
1942. cua-driver davidondrej/skills · score 69/100 (grade C)
      Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
1943. dbt-transformation-patterns sickn33/antigravity-awesome-skills · score 69/100 (grade C)
      Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.
1944. dependabot github/awesome-copilot · score 69/100 (grade C)
      Comprehensive guide for configuring and managing GitHub Dependabot. Use this skill when users ask about creating or optimizing dependabot.yml files, managing Dependabot pull requests, configuring dependency update strategies, setting up grouped updates, monorepo patterns, multi-ecosystem groups, security update configuration, auto-triage rules, or any GitHub Advanced Security (GHAS) supply chain security topic related to Dependabot. For pre-commit dependency vulnerability scanning in AI coding agents via the GitHub MCP Server, this skill references the Advanced Security plugin (`advanced-security@copilot-plugins`). Use this skill when an agent needs to scan dependencies for known vulnerabilities before committing.
1945. developing-genkit-go google/skills · score 69/100 (grade C)
      Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.
1946. diagnose github/awesome-copilot · score 69/100 (grade C)
      Perform a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.
1947. distribute-skill-to-all-agents davidondrej/skills · score 69/100 (grade C)
      Distribute global skills across Codex, Claude Code, Pi, Hermes, and Cursor. Use for "distribute this skill", "sync skills across agents", or after creating or updating a global skill.
1948. ecc-guide affaan-m/ECC · score 69/100 (grade C)
      Answer questions about ECC by reading the live repo surface — agents, skills, commands, hooks, rules, install profiles, and docs — instead of memory. Use when the user asks what ECC includes, how to install or reset it, which skill or command fits a task, or how project onboarding works.
1949. ecc-guide affaan-m/everything-claude-code · score 69/100 (grade C)
      Answer questions about ECC by reading the live repo surface — agents, skills, commands, hooks, rules, install profiles, and docs — instead of memory. Use when the user asks what ECC includes, how to install or reset it, which skill or command fits a task, or how project onboarding works.
1950. fal-ai-media affaan-m/ECC · score 69/100 (grade C)
      Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.
1951. fal-ai-media affaan-m/everything-claude-code · score 69/100 (grade C)
      Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.
1952. figma openai/skills · score 69/100 (grade C)
      Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
1953. gemini-interactions-api google/skills · score 69/100 (grade C)
      Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform.
1954. github-actions-hardening github/awesome-copilot · score 69/100 (grade C)
      Security hardening reviewer for GitHub Actions workflow files (.github/workflows/*.yml). Reasons about the Actions threat model that pattern matchers and general code linters miss — untrusted-input script injection, privileged triggers running fork code, mutable action references, and over-scoped tokens. Use this skill when asked to review, audit, harden, or secure a GitHub Actions workflow, when writing a new workflow, or for any request like "is this workflow safe?", "review my CI for security issues", "why is pull_request_target dangerous here?", "pin my actions", or "lock down GITHUB_TOKEN permissions". Covers script injection via ${{ }} interpolation, pull_request_target / workflow_run privilege escalation, SHA-pinning of third-party actions, least-privilege permissions, GITHUB_ENV/GITHUB_OUTPUT injection, secret exposure, OIDC over long-lived credentials, and self-hosted runner exposure on public repositories.
1955. google-cloud-solution-multi-agent-security google/skills · score 69/100 (grade C)
      Designs, deploys, and secures Google Cloud Agent Gateway solutions. Use when the user needs to configure multi-agent security, ingress (CLIENT_TO_AGENT), or egress (AGENT_TO_ANYWHERE) patterns involving Model Armor, IAP, and Agent Registry. Don't use for general Cloud Load Balancing or basic VPC setup not related to Agent Gateways.
1956. image-generation bytedance/deer-flow · score 69/100 (grade C)
      Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided generation.
1957. image-studio sickn33/antigravity-awesome-skills · score 69/100 (grade C)
      Studio de geracao de imagens inteligente — roteamento automatico entre ai-studio-image (fotos humanizadas/influencer) e stability-ai (arte/ ilustracao/edicao). Detecta o tipo de imagem solicitada e escolhe o modelo ideal automaticamente.
1958. inherit-legacy-style affaan-m/ECC · score 69/100 (grade C)
      Prevent AI style drift on legacy projects by scanning the codebase for implicit conventions, resolving conflicts with the operator one at a time, and writing an enforceable .ai-style-rules.md (Golden Files, naming rules, DONTs) plus an optional CLAUDE.md hook. Use when onboarding an AI agent onto a hand-written legacy codebase or extracting a project's unwritten coding rules.
1959. inherit-legacy-style affaan-m/everything-claude-code · score 69/100 (grade C)
      Prevent AI style drift on legacy projects by scanning the codebase for implicit conventions, resolving conflicts with the operator one at a time, and writing an enforceable .ai-style-rules.md (Golden Files, naming rules, DONTs) plus an optional CLAUDE.md hook. Use when onboarding an AI agent onto a hand-written legacy codebase or extracting a project's unwritten coding rules.
1960. integrate-context-matic github/awesome-copilot · score 69/100 (grade C)
      Discovers and integrates third-party APIs using the context-matic MCP server. Uses `fetch_api` to find available API SDKs, `ask` for integration guidance, `model_search` and `endpoint_search` for SDK details. Use when the user asks to integrate a third-party API, add an API client, implement features with an external API, or work with any third-party API or SDK.
1961. jobgpt sickn33/antigravity-awesome-skills · score 69/100 (grade C)
      Job search automation, auto apply, resume generation, application tracking, salary intelligence, and recruiter outreach using the JobGPT MCP server.
1962. lead-intelligence affaan-m/ECC · score 69/100 (grade C)
      AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.
1963. lead-intelligence affaan-m/everything-claude-code · score 69/100 (grade C)
      AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.
1964. lead-magnets coreyhaines31/marketingskills · score 69/100 (grade C)
      When the user wants to create, plan, or optimize a lead magnet for email capture or lead generation. Also use when the user mentions "lead magnet," "gated content," "content upgrade," "downloadable," "ebook," "cheat sheet," "checklist," "template download," "opt-in," "freebie," "PDF download," "resource library," "content offer," "email capture content," "Notion template," "spreadsheet template," "what should I give away for emails," "course as a skill," or "package our content as an agent skill." Use this for planning what to create and how to distribute it. For interactive tools as lead magnets, see free-tools. For writing the actual content, see copywriting. For the email sequence after capture, see emails.
1965. md-document alirezarezvani/claude-skills · score 69/100 (grade C)
      Converts long-form markdown (specs, RFCs, reports, plans, explainers) into a single-file, lightly-interactive HTML document with sticky TOC, scrollspy, search filter, code-copy buttons, and design-system-driven brand tokens. Triggers when the markdown-html-orchestrator classifies an input as DOCUMENT, or when invoked directly via /cs-md-document. Reads the design-system config via config_loader.py and inlines the user's 12 derived CSS custom properties; refuses to render if onboarding hasn't run. Single-file output — Google Fonts + Prism.js CDN are the only externals; no framework runtime, no build step. Use after orchestrator routing or after design-system onboarding is confirmed.
1966. microsoft-docs github/awesome-copilot · score 69/100 (grade C)
      Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.
1967. music-generation bytedance/deer-flow · score 69/100 (grade C)
      Use this skill when the user requests to generate, create, compose, or produce music or songs — background music, theme songs, jingles, or instrumental tracks. Generates a song from a style/mood prompt and optional lyrics via the MiniMax music API.
1968. nano-banana-pro-openrouter github/awesome-copilot · score 69/100 (grade C)
      Generate or edit images via OpenRouter with the Gemini 3 Pro Image model. Use for prompt-only image generation, image edits, and multi-image compositing; supports 1K/2K/4K output.
1969. noob-mode github/awesome-copilot · score 69/100 (grade C)
      Plain-English translation layer for non-technical Copilot CLI users. Translates every approval prompt, error message, and technical output into clear, jargon-free English with color-coded risk indicators.
1970. onboarding elevenlabs/skills · score 69/100 (grade C)
      Add ElevenLabs to a project from scratch. Use when the user wants to start using ElevenLabs, add text to speech, speech to text, voice agents, real-time voice for their own agent runtime (Speech Engine), sound effects, music, voice changing, voice isolation, or dubbing to their app, or get set up with an ElevenLabs account or API key for the first time. Handles sign-in, API key creation, SDK install and a test request end to end; the user leaves the conversation once, to approve a browser page. Not for fixing a key that stopped working or placing one an administrator issued (use setup-api-key).
1971. paywall-optimization Eronred/aso-skills · score 69/100 (grade C)
      When the user wants to design, test, or optimize their app's paywall — layout, copy, pricing display, trial offers, plan structure, hard vs soft paywall, paywall placement, or paywall A/B tests. Use when the user mentions "paywall", "paywall design", "paywall conversion", "trial-to-paid", "soft paywall", "hard paywall", "paywall A/B test", "paywall copy", "plan picker", "annual vs monthly display", "best paywall", "RevenueCat paywall", "Superwall", "Adapty", or "my paywall isn't converting". For overall pricing strategy and monetization model choice, see monetization-strategy. For trial nurture, dunning, and churn, see subscription-lifecycle. For where in the onboarding the paywall fires, see onboarding-optimization.
1972. retrieving-developer-knowledge google/skills · score 69/100 (grade C)
      Searches, retrieves, and synthesizes official Google developer documentation across Google Cloud, AI/Gemini, Android, Chrome, Web, Flutter, Go, Firebase, and other Google developer platforms. Integrates with the Developer Knowledge MCP server (search_documents, get_documents, answer_query) or the Developer Knowledge REST API fallback. Use when searching for gcloud CLI commands, API syntax, IAM permissions, official documentation, architectural comparisons, or product choice overviews. Don't use for local filesystem lookups or non-Google documentation.
1973. run-without-you alirezarezvani/claude-skills · score 69/100 (grade C)
      Phase 4 of building a Claude Managed Agent — make it run without you. Turn a graded agent into a recurring scheduled deployment (POSIX-cron), an event-driven curl trigger, or confirmed on-demand use, then finalize the versioned roadmap. Use when the user says "run it every morning", "put it on a schedule", "nightly", "weekly", "automate this", "make it recurring", or when the orchestrator routes phase=run-without-you. deployment_builder.py builds the POST /v1/deployments payload (initial_events must include user.message; optionally nests a user.define_outcome so each firing self-grades); cron_validator.py validates the 5-field cron + IANA timezone and prints the wall-clock DST note; next_directions_writer.py writes NEXT-DIRECTIONS.md. No tool makes API calls — the deployment is created via BYOK curl. Distinct from grade-iterate (the in-session loop) and wrap-up (closeout).
1974. self-improving-agent alirezarezvani/claude-skills · score 69/100 (grade C)
      Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
1975. senior-computer-vision alirezarezvani/claude-skills · score 69/100 (grade C)
      Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.
1976. senior-ml-engineer alirezarezvani/claude-skills · score 69/100 (grade C)
      ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization. Use when the user asks about deploying ML models to production, setting up MLOps infrastructure (MLflow, Kubeflow, Kubernetes, Docker), monitoring model performance or drift, building RAG pipelines, or integrating LLM APIs with retry logic and cost controls. Focused on production and operational concerns rather than model research or initial training.
1977. senior-security alirezarezvani/claude-skills · score 69/100 (grade C)
      Use when the user asks for STRIDE threat modeling, DREAD risk scoring, data-flow-diagram threat analysis, or a quick secret scan — or when a security request needs routing to the right specialist skill (pen-testing, incident response, cloud posture, red team, AI security, threat hunting, secure code review). This skill owns threat modeling; everything else routes to a sibling.
1978. stage-launch alirezarezvani/claude-skills · score 69/100 (grade C)
      Phase 2 of building a Claude Managed Agent — turn a validated build sheet into exact API payloads and a resumable BYOK curl launch script, then launch (environment → agent → session → kickoff) using the founder's OWN Anthropic key. Use when the user says "launch it", "deploy the agent", "create the agent now", or when the orchestrator routes phase=stage-launch. payload_generator.py emits the four ordered payloads; launch_script_writer.py writes launch.sh that reads $ANTHROPIC_API_KEY at runtime and never embeds it; payload_validator.py runs a pre-launch check including an API-key-leak scan. No tool in this skill makes network calls — the user runs launch.sh themselves. Distinct from interview (planning) and grade-iterate (the outcome loop).
1979. swift-mcp-server-generator github/awesome-copilot · score 69/100 (grade C)
      Generate a complete Model Context Protocol server project in Swift using the official MCP Swift SDK package.
1980. team-builder affaan-m/ECC · score 69/100 (grade C)
      Interactive picker that discovers available agent personas via the claude agents command and agents/ markdown globs, groups them into domains, has the user select up to five, dispatches them in parallel on one task, and synthesizes agreements and conflicts into a unified report. Use when composing a team of agents, browsing available agent personas, or running several specialist agents in parallel.
1981. team-builder affaan-m/everything-claude-code · score 69/100 (grade C)
      Interactive picker that discovers available agent personas via the claude agents command and agents/ markdown globs, groups them into domains, has the user select up to five, dispatches them in parallel on one task, and synthesizes agreements and conflicts into a unified report. Use when composing a team of agents, browsing available agent personas, or running several specialist agents in parallel.
1982. threejs-3d-generator majidmanzarpour/threejs-game-skills · score 69/100 (grade C)
      Generate, texture, rig, animate, stylize, convert, and download 3D assets for Three.js games via the Tripo API. Use for text-to-3D, image-to-3D, game-ready GLB/FBX, characters, creatures, buildings, props, weapons, terrain, auto-rigging, animation retargeting, model texturing, voxel/LEGO stylization, and low-poly conversion. Pair with threejs-image-generator for concept and texture references first.
1983. update-swiftui-apis AvdLee/SwiftUI-Agent-Skill · score 69/100 (grade C)
      Scan Apple's SwiftUI documentation for deprecated APIs and update the SwiftUI Expert Skill with modern replacements. Use when asked to "update latest APIs", "refresh deprecated SwiftUI APIs", "check for new SwiftUI deprecations", "scan for API changes", or after a new iOS/Xcode release. Requires the Sosumi MCP to be available.
1984. -21risk-automation ComposioHQ/awesome-claude-skills · score 68/100 (grade C)
      Automate 21risk tasks via Rube MCP (Composio). Always search tools first for current schemas.
1985. -2chat-automation ComposioHQ/awesome-claude-skills · score 68/100 (grade C)
      Automate 2chat tasks via Rube MCP (Composio). Always search tools first for current schemas.
1986. academic-paper Imbad0202/academic-research-skills · score 68/100 (grade C)
      12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, I got reviewer comments, revision roadmap, should we push back, conference rebuttal, grant panel response, audit my rebuttal, check my response draft, AI disclosure, check citations, citation check, check my references, verify references, look over the refs, 寫論文, 學術論文, 引導我寫論文, 審查意見, 我收到審查意見, 修訂路線圖, 評估回覆, 檢查引用, 引用檢查, 檢查參考文獻, 核對文獻, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견을 받았어, 심사 의견 반영, 답변서 점검, AI 사용 고지, 인용 확인, 인용 형식 검사, enmendar mi artículo, redactar artículo, guía mi artículo, analizar reseñas, auditar mi respuesta, verificar borrador de respuesta, verificar citas, divulgación de IA.
1987. ad-campaign-analyzer github/awesome-copilot · score 68/100 (grade C)
      Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.
1988. agent-platform-inference google/skills · score 68/100 (grade C)
      Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.
1989. agent-platform-tuning google/skills · score 68/100 (grade C)
      Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).
1990. agentic-engineering affaan-m/ECC · score 68/100 (grade C)
      Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.
1991. agentic-engineering affaan-m/everything-claude-code · score 68/100 (grade C)
      Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.
1992. ai-decision-authority alirezarezvani/claude-skills · score 68/100 (grade C)
      Routes marketing and GTM decisions into three AI governance zones (AI-Primary, Collaborative, Human-Primary) by stakes and reversibility. Use when deciding which AI outputs need human review, whether an agent may act autonomously on a task, why AI adoption is collapsing under review requirements, or when auditing a list of workflows for safe autonomy. Triggers on 'should a human review this', 'can the agent just do this', 'AI governance policy', 'human in the loop'.
1993. ai-first-engineering affaan-m/ECC · score 68/100 (grade C)
      Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.
1994. ai-first-engineering affaan-m/everything-claude-code · score 68/100 (grade C)
      Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.
1995. api-gateway-backend-security-and-rate-limiting google/skills · score 68/100 (grade C)
      Secures and rate limits backend services behind Google Cloud API Gateway across OpenAPI 2.0 and OpenAPI 3.0.x API configurations, including MCP-enabled gateways. Use when configuring API key or JWT authentication, locking down Cloud Run or Cloud Run functions backends with a gateway service account, reading authenticated claims from X-Apigateway-Api-Userinfo, setting per-project request quotas, or diagnosing HTTP 429 and HTTP 500 Service Control Quota errors. Do not use for Apigee, GKE Gateway API, Cloud Load Balancing custom domain setup, or LLM model routing.
1996. bigquery-optimization google/skills · score 68/100 (grade C)
      Provides workflows to optimize BigQuery environments (capacity planning, editions), storage assets (partitioning, clustering, storage lifecycles, billing models), and SQL queries. Use when optimizing cost, modeling Edition migrations, rightsizing reservations, evaluating logical vs. physical storage, designing table partitioning/clustering, generating table DDL, migrating unpartitioned tables, managing partition expiration, optimizing individual SQL queries, or evaluating acceleration structures (search indexes, materialized views, BI Engine). Do not use for raw usage reporting (use bigquery-observability), query execution plan analysis, error troubleshooting, or diagnosing why a specific job was slow (use bigquery-troubleshooting).
1997. bio-machine-learning-model-validation GPTomics/bioSkills · score 68/100 (grade C)
      Validates predictive models on omics and biomedical data with nested cross-validation, group/batch/temporal-aware splits, the full data-leakage taxonomy, probability calibration, decision-curve net benefit, optimism correction, sample-size planning, and TRIPOD+AI reporting. Use when estimating model performance honestly, choosing a CV scheme, detecting leakage, or judging whether reported discrimination means the model is actually useful. For feature selection itself see machine-learning/biomarker-discovery; for confirmatory-trial inference see clinical-biostatistics/trial-reporting.
1998. bio-multi-omics-data-harmonization GPTomics/bioSkills · score 68/100 (grade C)
      Harmonizes already-normalized per-omic matrices onto a common footing before joint integration - assembling a MultiAssayExperiment, choosing the per-omic variance-stabilizing transform, deciding per-view versus per-feature scaling, picking a cross-omic batch strategy, and triaging missing data (feature, value, or whole sample; MAR versus MNAR). Covers why a shared-latent integrator is blind to what an omic is so scaling silently decides which block dominates, why batch confounded with biology is irrecoverable and should be modeled as a covariate not scrubbed, and why stacking blocks and running one ComBat erases cross-omic signal. Use when preparing two or more omics for MOFA2, mixOmics, or SNF, deciding a transform or scaling, correcting batch across modalities, or handling missing omics per sample. For deep per-omic normalization see differential-expression, methylation-analysis, proteomics, metabolomics; for the method decision see integration-design; for fusion see mofa-integration, mixomics-analysis.
1999. bio-pathway-wikipathways GPTomics/bioSkills · score 68/100 (grade C)
      Tests a gene list (ORA, enrichWP) or a ranked gene vector (GSEA, gseWP) against the WikiPathways community-curated pathway collection with clusterProfiler and rWikiPathways. Covers why a WikiPathways result is a snapshot of a live, monthly-updated database (enrichWP/gseWP/gson_WP silently pull data.wikipathways.org/current/), why reproducibility requires pinning a dated GMT via downloadPathwayArchive(date=, format='gmt'), why the WP GMT is Entrez-keyed so symbols and Ensembl silently overlap nothing, why universe=NULL gives a biased all-WP-genes background, how to split the name%version%wpid%org term, and why WikiPathways (CC0, no peer review) complements KEGG/Reactome. Use when running open community-pathway enrichment, covering a non-model WP species, catching disease/drug pathways missing from KEGG/Reactome, or needing a reproducible dated analysis. The gene list comes from differential-expression/de-results; visualize with enrichment-visualization.
2000. bio-systems-biology-model-curation GPTomics/bioSkills · score 68/100 (grade C)
      Validates, gap-fills, and standardizes genome-scale metabolic models using memote for consistency and annotation scoring and COBRApy for manual curation, including mass/charge balance, energy-generating-cycle detection, dead-end resolution, GPR fixes, and SBML/SBO/MIRIAM annotation. Use when improving a draft model, gap-filling to a target medium, detecting erroneous ATP-from-nothing cycles, interpreting a memote score correctly (consistency vs biological validity), validating predictions against measured growth/essentiality, or preparing a model for publication.
2001. bio-workflows-grn-pipeline GPTomics/bioSkills · score 68/100 (grade C)
      Orchestrates gene regulatory network inference from processed single-cell data to regulons and in-silico perturbation, via pySCENIC (RNA-only GRNBoost2 -> cisTarget -> AUCell), SCENIC+ (multiome cisTopic -> pycistarget -> eGRN), and CellOracle perturbation. Use when recognizing that an inferred GRN is UNDIRECTED by default and reporting only the evidence tier delivered (co-expression vs motif-pruned vs enhancer-resolved vs perturbation), matching species/assembly/namespace across the TF-list + cisTarget DB + motif2TF annotation, feeding RAW counts of the cleaned/doublet-free/batch-controlled cells (never imputed/batch-corrected values), running the cisTarget pruning that buys directionality (modules are not regulons without it), or choosing the RNA-only vs multiome path. Hands mechanism to the gene-regulatory-networks component skills; not a re-teach of any single step.
2002. bio-workflows-microbiome-pipeline GPTomics/bioSkills · score 68/100 (grade C)
      End-to-end 16S/ITS amplicon workflow from demultiplexed FASTQ to a consensus differential-abundance result, orchestrating cutadapt primer removal, per-run DADA2 ASV inference (learnErrors/mergeSequenceTables/removeBimeraDenovo), region-matched taxonomy assignment, a SEPP/Greengenes2 tree, alpha/beta diversity at a declared sampling depth (phyloseq/vegan, adonis2 paired with betadisper), compositional DA as a consensus of >=2 tools (ALDEx2/ANCOM-BC2) on unrarefied counts, and optional PICRUSt2 functional prediction gated on NSTI. Covers the stage-ordering decisions (primers before truncation, per-run error model, rarefy for diversity not DA, predicted potential not activity) and defers each per-step choice to the six microbiome skills. Use when staging an amplicon study end to end or chaining ASV inference, taxonomy, diversity, and differential abundance. For shotgun reads see workflows/metagenomics-pipeline.
2003. bio-workflows-multi-omics-pipeline GPTomics/bioSkills · score 68/100 (grade C)
      Orchestrates VERTICAL bulk multi-omics integration (RNA + protein + methylation on the SAME samples) from harmonization to a validated result, routing to MOFA2 (shared factors), mixOmics/DIABLO (predictive signature), or SNF (patient subtypes). Use when confirming the correspondence is vertical (not horizontal same-features-different-cohorts), joining on a stable sample primary key rather than cbind on assumed row order, normalizing each omic in its OWN space and equalizing block variance BEFORE stacking (or the widest omic hijacks every shared factor), correcting batch ONCE in one place, and validating in a HELD-OUT cohort because in-cohort CV at n<<p is optimistically biased. Hands mechanism to the multi-omics-integration component skills; not a re-teach of any single step.
2004. bio-workflows-neoantigen-pipeline GPTomics/bioSkills · score 68/100 (grade C)
      Orchestrates neoantigen discovery from somatic variants to ranked vaccine candidates, chaining HLA typing (OptiType/arcasHLA + LOHHLA), VEP annotation (Wildtype+Frameshift plugins) + expression/readcount annotation, proximal-variant phasing, pVACseq MHC-I/II binding, CCF/clonality, and immunogenicity/quality ranking. Use when recognizing that binding is single-digit PPV and the critical steps are downstream (full-resolution HLA + LOH gating, proximal-variant phasing, clonality from purity+CN not raw VAF, expression), sequencing normalize+annotate -> phase -> HLA -> binding -> quality in the defensible order, dropping candidates on LOH-lost alleles, supplying --phased-proximal-variants-vcf so the mutant peptide is real, or ranking WITHIN patient rather than a fixed IC50 threshold. Hands mechanism to the immunoinformatics component skills; not a re-teach of any single step.
2005. caveman-discover JuliusBrussee/caveman · score 68/100 (grade C)
      Find and label every LLM workflow in the repository so Caveman Cloud groups spend by workflow instead of one bucket. Use for "discover workflows" or breaking LLM spend down by workflow.
2006. claude-coach alirezarezvani/claude-skills · score 68/100 (grade C)
      Personal coach that teaches users to become Claude power users. Use this skill the FIRST time a user asks to "learn Claude", "be a power user", "coach me", "teach me Claude tricks", "what can Claude do", "make me better at prompting", or any variation. After activation, also use it on EVERY subsequent turn to detect missed optimization opportunities (vague prompts, ignored capabilities, manual work Claude could automate) and surface a single power-user tip. Trigger generously — most users do not know what they do not know, so err on the side of coaching.
2007. code-exemplars-blueprint-generator github/awesome-copilot · score 68/100 (grade C)
      Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.
2008. codex-subagent davidondrej/skills · score 68/100 (grade C)
      Launch OpenAI Codex CLI as a subagent (ChatGPT subscription auth, no API key). Use when delegating a self-contained coding task to Codex from another agent — parallel implementation work, a second opinion, or an independent verification pass.
2009. copilot-pr-autopilot github/awesome-copilot · score 68/100 (grade C)
      Copilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re-triggers until HEAD is reviewed with zero threads awaiting the agent''s reply (remaining open threads are explicit hand-offs to the human — escalated declines, design tradeoffs). You merge a clean PR; the bot runs it. Trigger phrases: "address copilot comments", "run a copilot review loop", "fix this PR", "iterate on copilot feedback". Repo-agnostic, gh CLI + PowerShell. Full autopilot needs repo Triage/Write; external PR authors get single-iteration mode plus manual re-trigger (UI 🔄 or substantive-commit push).
2010. d365-solution-blueprint github/awesome-copilot · score 68/100 (grade C)
      Authors a Dynamics 365 Finance and Supply Chain Management Solution Blueprint from scratch through a structured, section-by-section architect interview, establishing scope, target operating model, application and data architecture, integration landscape, migration strategy, security model, ALM, testing, deployment, and support approach, with a decision log capturing rationale and rejected alternatives. Use when the user wants to create D365 implementation architecture documentation, start a D365 implementation, design the architecture, prepare a Solution Blueprint, or identify the architectural decisions the programme must make. Do not use for critique of an existing design; that is a review task rather than blueprint authoring.
2011. declarative-agents github/awesome-copilot · score 68/100 (grade C)
      Complete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integration
2012. draw-io-diagram-generator github/awesome-copilot · score 68/100 (grade C)
      Use when creating, editing, or generating draw.io diagram files (.drawio, .drawio.svg, .drawio.png). Covers mxGraph XML authoring, shape libraries, style strings, flowcharts, system architecture, sequence diagrams, ER diagrams, UML class diagrams, network topology, layout strategy, the hediet.vscode-drawio VS Code extension, and the full agent workflow from request to a ready-to-open file.
2013. fable-goal alirezarezvani/claude-skills · score 68/100 (grade C)
      Convert a rambling description of a desired outcome into one polished, autonomous /goal prompt ready to paste into a fresh session. Use when the user says "/fable-goal", "turn this into a goal prompt", "write me a fable prompt", "write the prompt that builds X", or rambles about something they want made and asks for the prompt that makes it happen. The output is a single copy-paste prompt, never the build itself. Do NOT use when the user wants the thing built right now in this session — only when they want the PROMPT that will make it happen in a fresh session.
2014. financial-analyst alirezarezvani/claude-skills · score 68/100 (grade C)
      Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.
2015. flox-environments affaan-m/ECC · score 68/100 (grade C)
      Create reproducible, cross-platform (macOS/Linux) development environments with Flox, a declarative Nix-based environment manager. Use when setting up project toolchains, installing system-level dependencies (compilers, databases, native libs), pinning exact package versions for a team, onboarding developers, running local services (PostgreSQL, Redis, Kafka), or solving 'works on my machine' problems — including agent/vibe-coding setups that need project-scoped tools without sudo. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.
2016. flox-environments affaan-m/everything-claude-code · score 68/100 (grade C)
      Create reproducible, cross-platform (macOS/Linux) development environments with Flox, a declarative Nix-based environment manager. Use when setting up project toolchains, installing system-level dependencies (compilers, databases, native libs), pinning exact package versions for a team, onboarding developers, running local services (PostgreSQL, Redis, Kafka), or solving 'works on my machine' problems — including agent/vibe-coding setups that need project-scoped tools without sudo. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.
2017. gke-manifest-generation google/skills · score 68/100 (grade C)
      Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).
2018. google-agents-cli-onboarding google/skills · score 68/100 (grade C)
      Onboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle.
2019. google-cloud-solution-build-deploy-agents google/skills · score 68/100 (grade C)
      Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.
2020. image coreyhaines31/marketingskills · score 68/100 (grade C)
      When the user wants to create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,' 'hero image,' 'social media graphic,' 'banner image,' 'cover photo,' 'profile banner,' 'listing screenshot,' 'Flux,' 'Flux Kontext,' 'Midjourney,' 'DALL-E,' 'GPT Image,' 'ChatGPT Images,' 'Ideogram,' 'Gemini image,' 'Nano Banana,' 'Recraft,' 'Stable Diffusion,' 'Canva,' 'Figma,' 'image optimization,' 'compress images,' 'WebP,' or 'OG image.' Use this for general-purpose marketing image creation and optimization. For paid ad image creative and platform-specific ad specs, see ad-creative. For video production, see video.
2021. llm-application-dev-ai-assistant sickn33/antigravity-awesome-skills · score 68/100 (grade C)
      Design and implement conversational AI assistants with context management, integration boundaries, and validation.
2022. llm-wiki alirezarezvani/claude-skills · score 68/100 (grade C)
      Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
2023. mantis-launch google/mantis · score 68/100 (grade C)
      Launches automated vulnerability review campaigns on target files or repositories. Use to initiate Mantis vulnerability review pipelines with automated preflight checks, environment auto-configuration, and runtime overrides (sandboxes, models, endpoints). Don't use for configuring settings without scanning or for manual single-stage reviews.
2024. mantis-pipeline-adapter google/mantis · score 68/100 (grade C)
      Interactively guides the design and implementation of custom deterministic orchestrator harnesses. Use when a user wants to build their own pipeline to wrap and run Mantis skills reliably. Don't use for executing the default pipeline directly.
2025. mantis-summarize google/mantis · score 68/100 (grade C)
      Pre-processes the repository by generating security-focused summaries (mantis-summary.md) for each directory to make planning and research more efficient. Use when starting a review campaign to map the codebase before threat modeling and planning. Don't use for executing code reviews, writing test scripts, or patching code.
2026. markdown-html-orchestrator alirezarezvani/claude-skills · score 68/100 (grade C)
      Use when a user wants to convert any markdown file in their Claude project into a single-file, lightly-interactive HTML — long-form documents (specs, plans, RFCs, reports, explainers), code reviews with diffs and severity-tagged annotations, or slide decks. Triggers on "convert this markdown to HTML", "make this an HTML file", "turn this into an interactive document", "render this report as HTML", "PR writeup as HTML", "slides from this markdown". Forks context to route to one of three converter sub-skills (md-document, md-review, md-slides) based on a deterministic doctype classifier, after the user has run the design-system onboarding once. Refuses if input is under 100 lines (per Shihipar — markdown still wins below the threshold) or design-system isn't onboarded. Distinct from Anthropic's official Playground plugin (which is interactive prompt-tuning controls with sliders/knobs/prompt-copy-back) and from marketing/landing/ (which is a landing-page generator).
2027. marketing-psychology coreyhaines31/marketingskills · score 68/100 (grade C)
      When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context. For applying psychology to specific pages, see cro; for pricing tactics, see pricing; for copy framing, see copywriting.
2028. mcp-security-audit github/awesome-copilot · score 68/100 (grade C)
      Audit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP package-runner dependencies use exact reviewed versions, not bare names, @latest, or ranges - Detecting mutable npm/npx, bunx, pnpm dlx, yarn dlx, and npm exec references in MCP configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]
2029. md-slides alirezarezvani/claude-skills · score 68/100 (grade C)
      Converts a markdown deck (slides separated by `---` HR boundaries or by `# ` H1 headings, with optional HTML-comment `notes:` presenter-notes blocks) into a single-file HTML presentation with arrow-key / space / PgDn / PgUp / Home / End / P / Esc keyboard navigation, presenter mode (split view with current slide + speaker notes + clock + next-slide preview), URL-hash deep linking, and `@media print` page-per-slide for PDF export. Triggers when the markdown-html-orchestrator classifies an input as SLIDES, or when invoked directly via /cs-md-slides. Reuses md-document's markdown parser for slide-body rendering and reads design-system tokens via config_loader.py. Refuses if input has no clear slide boundaries, produces a 1-slide deck, or `--strict-notes` is on with under 50% notes coverage. Use after orchestrator routing.
2030. multi-advisor sickn33/antigravity-awesome-skills · score 68/100 (grade C)
      Conselho de especialistas — consulta multiplos agentes do ecossistema em paralelo para analise multi-perspectiva de qualquer topico. Ativa personas, especialistas e agentes tecnicos simultaneamente, cada um pela sua otica unica, e consolida em sintese decisoria final.
2031. onboard-context-matic github/awesome-copilot · score 68/100 (grade C)
      Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).
2032. opensource-pipeline affaan-m/ECC · score 68/100 (grade C)
      Open-source pipeline: fork, sanitize, and package private projects for safe public release. Chains 3 agents (forker, sanitizer, packager). Triggers: '/opensource', 'open source this', 'make this public', 'prepare for open source'. Use when a private project must be forked, stripped of secrets, and packaged for public release.
2033. opensource-pipeline affaan-m/everything-claude-code · score 68/100 (grade C)
      Open-source pipeline: fork, sanitize, and package private projects for safe public release. Chains 3 agents (forker, sanitizer, packager). Triggers: '/opensource', 'open source this', 'make this public', 'prepare for open source'. Use when a private project must be forked, stripped of secrets, and packaged for public release.
2034. parallel-execution-optimizer affaan-m/ECC · score 68/100 (grade C)
      Speed up a task by turning it into a dependency graph of parallel lanes with a lane matrix, batched reads and checks, write surfaces isolated by file, worktree, branch, or service, and a final verification table. Use when the user wants a task done much faster through parallel work, concurrent agents, batched tool calls, isolated worktrees, or many independent verification lanes without losing correctness.
2035. parallel-execution-optimizer affaan-m/everything-claude-code · score 68/100 (grade C)
      Speed up a task by turning it into a dependency graph of parallel lanes with a lane matrix, batched reads and checks, write surfaces isolated by file, worktree, branch, or service, and a final verification table. Use when the user wants a task done much faster through parallel work, concurrent agents, batched tool calls, isolated worktrees, or many independent verification lanes without losing correctness.
2036. pdf ComposioHQ/awesome-claude-skills · score 68/100 (grade C)
      Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
2037. pester-migration github/awesome-copilot · score 68/100 (grade C)
      Pester migration skill for upgrading PowerShell Pester test suites across major versions — v3→v4, v4→v5, and v5→v6. Covers the Discovery/Run two-phase model, moving setup into BeforeAll, $PSScriptRoot vs $MyInvocation, mock changes (Assert-MockCalled → Should -Invoke, removed fall-through), Invoke-Pester parameters → PesterConfiguration, data-driven -ForEach/-TestCases, and the v6 breaking changes. Use when the user asks to upgrade, migrate, or modernize Pester tests, fix *.Tests.ps1 files that broke after bumping the Pester version, or convert legacy Should / Invoke-Pester syntax.
2038. powerbi-modeling github/awesome-copilot · score 68/100 (grade C)
      Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
2039. product-marketing coreyhaines31/marketingskills · score 68/100 (grade C)
      When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' 'who is my target audience,' 'describe my product,' 'ICP,' 'ideal customer profile,' 'brand voice,' 'tone of voice,' 'brand guidelines,' 'what have we learned,' 'log this learning,' or wants to avoid repeating foundational information across marketing tasks. Use this at the start of any new project before using other marketing skills — it creates `.agents/product-marketing.md` that all other skills reference for product, audience, and positioning context.
2040. prompt-optimizer github/awesome-copilot · score 68/100 (grade C)
      Turn any rough prompt, half-formed idea, or task description into a finished, ready-to-send prompt optimized for any LLM model inside a chat interface — NOT the API. Use this skill whenever the user wants to write, rewrite, optimize, improve, sharpen, or polish a prompt for chat. Trigger phrases include "rewrite this prompt", "make this a better prompt", "optimize this prompt", "turn this into a prompt", "help me prompt this", "draft a prompt that...", "I want to ask...", or whenever the user pastes a draft prompt and asks for improvements. Also trigger when the user describes a task they plan to send to an LLM model and clearly wants a reusable, well-structured prompt rather than a direct answer. The output is always a single, copy-pasteable prompt in a code block that the user sends as-is — never a template with placeholders.
2041. python-mcp-server-generator github/awesome-copilot · score 68/100 (grade C)
      Use this skill when the user wants to create a new Model Context Protocol (MCP) server in Python. Also use it to expose Python functions, an API, or a database to AI clients as MCP tools. The skill makes a uv project with the MCP Python SDK v2 (MCPServer), typed tools, in-memory tests, and client configuration. Do not use it for an MCP client or for a server in another language.
2042. regex-vs-llm-structured-text affaan-m/ECC · score 68/100 (grade C)
      Decision framework for parsing structured text (quizzes, forms, invoices, receipts, tables) with a hybrid regex-first pipeline — regex extraction handles 95%+ cheaply, a confidence scorer flags low-confidence items, and an LLM validator fixes only the edge cases. Use when choosing between regex and LLM for text extraction, building a cheap document parser, or optimizing extraction cost and accuracy.
2043. regex-vs-llm-structured-text affaan-m/everything-claude-code · score 68/100 (grade C)
      Decision framework for parsing structured text (quizzes, forms, invoices, receipts, tables) with a hybrid regex-first pipeline — regex extraction handles 95%+ cheaply, a confidence scorer flags low-confidence items, and an LLM validator fixes only the edge cases. Use when choosing between regex and LLM for text extraction, building a cheap document parser, or optimizing extraction cost and accuracy.
2044. session-handoff alirezarezvani/claude-skills · score 68/100 (grade C)
      Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'm ending this session', 'pick this up later', or any variation signaling intent to pass work to a fresh agent. Also trigger on implicit signals: the user announcing they're switching machines, ending the day mid-task, or context is growing long without a natural stopping point.
2045. social-publisher affaan-m/ECC · score 68/100 (grade C)
      Agent-driven scheduling and publishing of social media posts across 13 platforms via SocialClaw. Use when the user wants to publish to X, LinkedIn, Instagram, Facebook Pages, TikTok, Discord, Telegram, YouTube, Reddit, WordPress, or Pinterest — or when managing campaigns, uploading media, or monitoring post delivery status.
2046. social-publisher affaan-m/everything-claude-code · score 68/100 (grade C)
      Agent-driven scheduling and publishing of social media posts across 13 platforms via SocialClaw. Use when the user wants to publish to X, LinkedIn, Instagram, Facebook Pages, TikTok, Discord, Telegram, YouTube, Reddit, WordPress, or Pinterest — or when managing campaigns, uploading media, or monitoring post delivery status.
2047. stress-test alirezarezvani/claude-skills · score 68/100 (grade C)
      /em:stress-test — Business assumption stress testing. Use before betting on a plan whose core assumptions are unvalidated — e.g. stress-testing 'enterprise buyers will tolerate a 6-month pilot' or a hockey-stick revenue model.
2048. suggest-awesome-github-copilot-agents github/awesome-copilot · score 68/100 (grade C)
      Suggest relevant GitHub Copilot Custom Agents files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing custom agents in this repository, and identifying outdated agents that need updates.
2049. taste-distillation affaan-m/ECC · score 68/100 (grade C)
      Measure a set of reference videos into a reusable style pack - colour grade as a 3D LUT, cut rhythm as a shot-length distribution, hero stills, screen-blend overlay plates, and a text spec for a generative model. Use when the user wants to capture the look of reference footage, build a repeatable look, mint assets from references, or reproduce someone's grade and pacing.
2050. taste-distillation affaan-m/everything-claude-code · score 68/100 (grade C)
      Measure a set of reference videos into a reusable style pack - colour grade as a 3D LUT, cut rhythm as a shot-length distribution, hero stills, screen-blend overlay plates, and a text spec for a generative model. Use when the user wants to capture the look of reference footage, build a repeatable look, mint assets from references, or reproduce someone's grade and pacing.
2051. test:triage antithesishq/antithesis-skills · score 68/100 (grade C)
      This skill should be used when the user asks to "test the triage skill", "run triage tests", "validate antithesis triage", "test:triage", or "smoke test triage". Orchestrates end-to-end testing of the antithesis-triage skill by running real triage operations via sub-agents and reviewing the results for bugs, skill compliance issues, and papercuts.
2052. threat-modeling briiirussell/cybersecurity-skills · score 68/100 (grade C)
      Run a structured threat-modeling session for a new feature, system, or architecture — STRIDE, attack trees, data flow diagrams, abuse cases. Use when the user mentions 'threat model,' 'threat modeling,' 'STRIDE,' 'attack tree,' 'abuse case,' 'data flow diagram,' 'DFD,' 'security architecture review,' 'security review,' 'design review,' 'pre-implementation security,' 'shift left,' 'what could go wrong,' or needs strategic security thinking before code is written.
2053. academy-guide anthropics/skills · score 67/100 (grade C)
      Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
2054. agent-dx-cli-scale google-labs-code/design.md · score 67/100 (grade C)
      A scoring scale for evaluating how well a CLI is designed for AI agents, based on the "Rewrite Your CLI for AI Agents" principles.
2055. asc-localize-metadata rudrankriyam/app-store-connect-cli-skills · score 67/100 (grade C)
      Automatically translate and sync App Store metadata (description, keywords, what's new, subtitle) to multiple languages using LLM translation and asc CLI. Use when asked to localize an app's App Store listing, translate app descriptions, or add new languages to App Store Connect.
2056. audit-xls anthropics/financial-services · score 67/100 (grade C)
      Audit a spreadsheet for formula accuracy, errors, and common mistakes. Scopes to a selected range, a single sheet, or the entire model (including financial-model integrity checks like BS balance, cash tie-out, and logic sanity). Triggers on "audit this sheet", "check my formulas", "find formula errors", "QA this spreadsheet", "sanity check this", "debug model", "model check", "model won't balance", "something's off in my model", "model review".
2057. bio-chipseq-motif-analysis GPTomics/bioSkills · score 67/100 (grade C)
      Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME. Handles background selection (GC-matched, dinucleotide-shuffled, Markov order-2, peak-flanks), motif databases (JASPAR 2024 CORE PWMs, JASPAR 2026 deep-learning collection, HOCOMOCO v12, HOMER built-in), centrally-enriched motif testing, and differential motif analysis. Use when identifying TF binding motifs in peaks, testing for known TF enrichment, scanning for motif instances, comparing motif content between conditions, or interpreting motifs from deep learning models.
2058. bio-crispr-screens-hit-calling GPTomics/bioSkills · score 67/100 (grade C)
      Cross-method decision tree for calling hits in pooled CRISPR screens. Catalogs statistical models (MAGeCK RRA, MAGeCK MLE, BAGEL2, drugZ, JACKS, Chronos, CERES), experimental designs each is built for, failure modes outside design domain, reconciliation when methods disagree, multiple-testing and effect-size thresholds, the order of operations (count -> QC -> CN-correct -> hit-call -> validate), the second-best-sgRNA conservative rule, and consensus-hit strategy. Use when choosing among MAGeCK / BAGEL2 / drugZ / JACKS / Chronos for a given design, reconciling disagreement across two or three methods on the same screen, deciding whether to require consensus, gating downstream validation by hit-confidence tier, or interpreting unstable hit lists across reruns.
2059. bio-epitranscriptomics-m6a-peak-calling GPTomics/bioSkills · score 67/100 (grade C)
      Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM), MeTPeak (HMM over sliding windows), MACS3/MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody methods cannot resolve, and orthogonal validation (miCLIP/GLORI/m6A-SAC-seq/m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set, reconciling differing peak sets across tools, validating MeRIP peaks against single-base methods, interpreting 5' peaks where m6Am contamination is possible, or recommending a consensus strategy.
2060. bio-expression-matrix-metadata-joins GPTomics/bioSkills · score 67/100 (grade C)
      Aligns sample metadata with count matrices and constructs design matrices for downstream DE, handling the alphabetical-reference-level trap (relevel BEFORE DESeq), LRT reduced-model rules, the interaction-term resultsNames trap, continuous-covariate scaling and splines, repeated measures via duplicateCorrelation or dream, high-cardinality categorical pseudo-singular designs, sample swap detection via XIST/RPS4Y1 expression and somalier/NGSCheckMate genotypes, SABV (sex-as-biological-variable) mandate, Simpson's-paradox collapsing of technical replicates, and the `~ 0 + group` parameterization for clean contrasts. Use when building a design matrix, troubleshooting reversed fold-change direction, encoding paired or repeated-measures designs, detecting sample swaps, deciding sex-as-covariate, or aggregating technical replicates.
2061. bio-fragment-analysis GPTomics/bioSkills · score 67/100 (grade C)
      Extracts cfDNA fragmentomics features (DELFI genome-wide short/long ratios, WPS nucleosome positioning, Griffin GC-corrected accessibility profiles, end-motifs/MDS, OCF) for cancer detection and tissue-of-origin from plasma WGS. Centers on the nuclease-footprint reframe (every feature re-reads one nucleosome object), the mandatory GC correction, and the cross-protocol non-comparability that breaks naive classifiers. Runs FinaleToolkit (real CLI/Python, MIT) and the Griffin Snakemake pipeline; DELFI is a method, not a package. Use when deriving fragment-based signal from cfDNA, choosing a feature family for detection vs subtyping, or diagnosing why a fragmentomic model failed validation.
2062. bio-hi-c-analysis-hichip-plac-loops GPTomics/bioSkills · score 67/100 (grade C)
      Calls significant loops from protein-directed and targeted 3C assays (HiChIP, PLAC-seq, Capture Hi-C/PCHi-C, ChIA-PET) where the contact background is peak-anchored and coverage-biased, so generic Hi-C loop callers (cooltools dots, Juicer HiCCUPS) use the wrong null. Covers FitHiChIP (config-driven coverage+distance-decay spline regression, peak-to-peak vs peak-to-all foreground, loose vs stringent background, coverage vs ICE bias), MAPS (positive Poisson regression on bias factors for PLAC-seq/HiChIP), hichipper (restriction-site-distance bias model + library QC), CHiCAGO (Delaporte two-component Brownian+technical background for asymmetric bait x other-end Capture Hi-C), the with/without separate-ChIP anchor decision, and differential loops via diffloop. Use when calling loops from HiChIP/PLAC-seq/Capture Hi-C, choosing FitHiChIP/MAPS/CHiCAGO, picking peak-to-all vs peak-to-peak, setting the loop FDR, supplying ChIP peaks as anchors, QCing a HiChIP library, or comparing loops between conditions.
2063. bio-imaging-mass-cytometry-cell-segmentation GPTomics/bioSkills · score 67/100 (grade C)
      Segment single cells from multiplexed IMC/MIBI tissue images using Mesmer/DeepCell, Cellpose, or ilastik+CellProfiler, covering whole-cell vs nuclear segmentation, the summed-membrane-channel decision, nuclear-expansion bias, lateral spillover, resolution-floor parameters, and downstream-proxy evaluation. Use when delineating cells after preprocessing, choosing a segmentation model, building a cell mask for quantification, diagnosing impossible double-positive populations, or troubleshooting over/under-segmentation.
2064. bio-machine-learning-biomarker-discovery GPTomics/bioSkills · score 67/100 (grade C)
      Selects biomarker features from high-dimensional omics data using Boruta all-relevant selection, mRMR, LASSO/elastic-net, and stability selection, while controlling the leakage, irreproducibility, and correlated-feature traps that make most published signatures fail to replicate. Use when identifying candidate biomarkers, deciding between an all-relevant and a minimal-optimal selector, or judging whether a selected gene set is reproducible. For unbiased performance estimation of the resulting model see machine-learning/model-validation; for interpreting a trained model see machine-learning/prediction-explanation.
2065. bio-microbiome-amplicon-processing GPTomics/bioSkills · score 67/100 (grade C)
      Infers exact amplicon sequence variants (ASVs) from demultiplexed 16S rRNA or ITS amplicon FASTQ with DADA2 - removing primers with cutadapt (--discard-untrimmed), learning a per-run error model (filterAndTrim -> learnErrors -> dada -> mergePairs), merging run-level tables with mergeSequenceTables, then one removeBimeraDenovo. Covers why primers come OFF before truncation, why the error model is per-run, truncLen as a merge-overlap detection budget (V4 vs V3-V4), DADA2 vs Deblur and q2-dada2 (denoise-paired/single/pyro/ccs), ASV vs OTU, NovaSeq binned-quality error-fit breakage, ITSxpress for variable-length ITS, and decontam removal of reagent/kit contaminants. Use when turning demultiplexed amplicon reads into an ASV/feature table, choosing truncation lengths, handling multi-run studies, or ITS. For shotgun reads see metagenomics/kraken-classification; for QIIME2 CLI mechanics see qiime2-workflow; for primer trimming theory see read-qc/adapter-trimming.
2066. bio-molecular-descriptors GPTomics/bioSkills · score 67/100 (grade C)
      Calculates molecular fingerprints (ECFP/Morgan, FCFP, MACCS, RDKit, AtomPair, TopologicalTorsion, Avalon, MAP4, MHFP6) and physicochemical descriptors (Lipinski, QED, TPSA, Crippen LogP, 3D shape) with explicit choice tables, bit vs count semantics, and partial-charge model selection. Use when featurizing molecules for similarity, QSAR, virtual screening, or ML, or selecting the correct fingerprint for a chemotype-aware task.
2067. bio-multi-omics-mixomics-analysis GPTomics/bioSkills · score 67/100 (grade C)
      Builds supervised and unsupervised multivariate integration across bulk omics blocks with mixOmics - sPLS for sparse pairwise correlation, DIABLO (block.splsda) for a multi-block discriminant signature, rCCA for regularized canonical correlation, and MINT for multi-study integration. Covers why these projection methods maximize covariance or correlation and not truth, why DIABLO's design matrix is the central correlation-versus-discrimination decision, why cross-validation must wrap keepX selection or the reported error is leaked, why balanced error rate is required under class imbalance, and why DIABLO needs matched samples while MINT handles multiple cohorts. Use when finding a cross-omic discriminant signature for a known outcome, selecting correlated features between two omics, tuning keepX, or integrating one omic across studies. For unsupervised factors see mofa-integration; for the method decision see integration-design; for cross-validation theory see machine-learning/model-validation.
2068. bio-proteomics-differential-abundance GPTomics/bioSkills · score 67/100 (grade C)
      Tests for differentially abundant proteins between conditions with limma/DEqMS empirical-Bayes moderation, proDA/msqrob2/MSstats missingness modeling, and Python Welch+BH alternatives. Frames missing values as left-censored MNAR (model, do not impute), makes variance moderation the load-bearing step at n=3-5, and prefers feature/peptide-level testing. Use when identifying proteins with significant abundance changes between experimental groups. Summarization and normalization mechanics are proteomics/quantification; volcano and MA plots are data-visualization/volcano-and-ma-plots; pathway enrichment of the hit list is pathway-analysis/go-enrichment.
2069. bio-single-cell-cell-annotation GPTomics/bioSkills · score 67/100 (grade C)
      Automated reference-based cell type annotation for single-cell RNA-seq using CellTypist, SingleR, Azimuth, scANVI, and scmap to transfer labels from a reference. Use when annotating cell types from a reference atlas or pretrained model, transferring labels onto a query, assessing prediction confidence and rejection, or triaging whether an unexpected cluster is a novel type versus a doublet, low-quality, or batch artifact.
2070. bio-systems-biology-context-specific-models GPTomics/bioSkills · score 67/100 (grade C)
      Builds tissue-, cell-type-, and condition-specific metabolic models by integrating transcriptomic or proteomic data into a generic genome-scale model, using extraction algorithms (GIMME, iMAT, INIT/tINIT, MADE, E-Flux, CORDA, FASTCORE) via troppo and corda in Python or the COBRA Toolbox/RAVEN in MATLAB. Use when pruning a generic model to a context, choosing an extraction method and expression threshold, mapping expression through GPR rules to reactions, deciding whether an objective is required (GIMME vs iMAT), avoiding the growth-objective trap for non-proliferating tissue, or judging how much of a context-specific model is real signal versus an artifact of the threshold and method.
2071. bio-systems-biology-metabolic-reconstruction GPTomics/bioSkills · score 67/100 (grade C)
      Builds draft genome-scale metabolic models from an annotated genome using CarveMe (top-down carving of a BiGG universal model) or gapseq (bottom-up pathway-evidence reconstruction), then loads and sanity-checks the draft in COBRApy. Use when creating a model for an organism without one, choosing between CarveMe and gapseq, gap-filling to a target medium, understanding why a draft that grows is still only a hypothesis, handling BiGG-vs-ModelSEED namespace mismatch, or preparing a draft for curation and community modeling.
2072. bio-systems-biology-strain-design GPTomics/bioSkills · score 67/100 (grade C)
      Computes metabolic-engineering strain designs on genome-scale models with StrainDesign (OptKnock, RobustKnock, minimal cut sets, OptCouple) and cameo (heuristic knockout and FSEOF over/under-expression targets), finding gene/reaction interventions that couple product formation to growth. Use when designing knockouts to overproduce a target chemical, choosing between OptKnock and RobustKnock, growth-coupling a product so evolution maintains it, computing minimal cut sets, finding amplification targets with FSEOF, or understanding why MILP strain design needs a strong solver and why a design is only a hypothesis.
2073. bio-workflows-longread-sv-pipeline GPTomics/bioSkills · score 67/100 (grade C)
      Orchestrates an end-to-end long-read structural-variant pipeline - basecalling to minimap2 alignment (platform-matched preset) to Sniffles2/cuteSV/pbsv calling to optional assembly-based calling (dipcall/PAV) to two-step .snf cohort merging to Truvari benchmarking - chaining ONT and PacBio HiFi runs while handing the SV signal mechanism off to the component skills. Use when running a long-read SV workflow from reads to a benchmarked callset, choosing the minimap2 preset and SV caller by platform and goal, deciding when long reads are worth it for the insertions and repeat-mediated SVs short reads physically miss, building a joint-genotyped cohort with the two-step .snf design, or parameterizing a Truvari benchmark against GIAB HG002 Tier 1 plus CMRG. Not for the SV signal mechanism itself (see variant-calling/structural-variant-calling) or short-read SV.
2074. bio-workflows-multiome-pipeline GPTomics/bioSkills · score 67/100 (grade C)
      Orchestrates the end-to-end 10x Multiome (paired scRNA + scATAC) pipeline from Cell Ranger ARC output to a jointly-embedded, annotated object, chaining per-modality QC, AMULET fragment-based ATAC doublet detection, per-modality normalization (RNA SCT/PCA; ATAC TF-IDF/LSI), WNN (or MultiVI) integration, joint clustering, RNA-based annotation, and LinkPeaks peak-to-gene linking. Use when enforcing the shared cell-barcode intersection between modalities (cellranger-ARC not -atac), keeping per-modality QC/doublets before the joint embedding, dropping the depth-correlated LSI component, annotating identity from RNA (ATAC is regulatory state), treating peak-to-gene links as correlational hypotheses, or aggregating to pseudobulk for cross-condition DE. Hands mechanism to the single-cell and atac-seq component skills; not a re-teach of any single step.
2075. bio-workflows-outbreak-pipeline GPTomics/bioSkills · score 67/100 (grade C)
      Orchestrates genomic-epidemiology outbreak investigation from pathogen isolates to transmission networks, forking bacterial (snippy -> Gubbins recombination-masking -> IQ-TREE -> TreeTime -> TransPhylo) vs viral (Nextstrain/augur), with parallel MLST typing (cgMLST delegated to epidemiological-genomics/pathogen-typing) and AMR surveillance. Use when committing ONE reference genome for SNP calling (every isolate and distance inherits its coordinates), applying MANDATORY Gubbins recombination-masking on core.full.aln before the tree for recombining bacteria (skipping it inflates the clock 2-5x), gating time-scaling on a temporal-signal test (TempEst R2 >= 0.3), using a pathogen- AND population-specific cluster threshold rather than a universal SNP cutoff, or pinning pangolin-data/Nextclade/Freyja versions for the viral route. Hands mechanism to the epidemiological-genomics component skills; not a re-teach of any single step.
2076. bio-workflows-tcr-pipeline GPTomics/bioSkills · score 67/100 (grade C)
      Orchestrates an end-to-end immune-repertoire pipeline from FASTQ to clonotypes, diversity, overlap, somatic hypermutation and lineages, routing on two forks. Use when deciding bulk vs single-cell (bulk amplicon/RNA-seq -> MiXCR analyze preset -> VDJtools/immunarch depth-normalized diversity and overlap -> figures; 10x paired VDJ -> MiXCR 10x preset or Cell Ranger -> scirpy gene-expression integration, chain QC, clonotype clusters); and TCR vs BCR (TCR -> exact CDR3-nt+V/J clonotypes, VDJtools diversity is fine; BCR -> somatic hypermutation makes exact clonotypes wrong -> Immcantation distToNearest/findThreshold clonal clustering, germline reconstruction, SHM, Dowser lineages); selecting the MiXCR 4.x preset by chemistry and activating its license; downsampling to equal depth before comparing diversity or overlap; and optionally annotating antigen specificity.
2077. bio-workflows-timecourse-pipeline GPTomics/bioSkills · score 67/100 (grade C)
      End-to-end bulk time-course analysis from an expression matrix to temporal gene modules and per-cluster pathway enrichment. Orchestrates temporal DE (limma splines or DESeq2 LRT), Mfuzz/tslearn soft clustering of expression-profile shapes, GAM trajectory fitting, per-cluster GO enrichment against a temporal-gene background, and an OPTIONAL circadian rhythm-detection branch (MetaCycle/CosinorPy) that runs only when the design covers >=2 full cycles with >=6-8 evenly spaced samples per cycle. Use when analyzing a bulk time-series expression experiment from any omics platform and deciding limma-splines vs DESeq2-LRT for temporal DE, soft vs hard clustering, whether the sampling design even licenses rhythm detection, and which background to use for enrichment. Not for single-cell pseudotime (see temporal-genomics/trajectory-modeling for the bulk-vs-pseudotime boundary) or unknown-period discovery (see temporal-genomics/periodicity-detection).
2078. breakdown-epic-arch github/awesome-copilot · score 67/100 (grade C)
      Prompt for creating the high-level technical architecture for an Epic, based on a Product Requirements Document.
2079. c-level-skills alirezarezvani/claude-skills · score 67/100 (grade C)
      Index and router for the C-level advisory bundle: 33 skills covering 14 C-suite roles, orchestration, cross-cutting capabilities, and culture. Use when exploring what the c-level-advisor bundle contains, deciding which advisor skill fits a question, or finding the entry points (cs-onboard interview, chief-of-staff routing, board-meeting protocol).
2080. change-management alirezarezvani/claude-skills · score 67/100 (grade C)
      Framework for rolling out organizational changes without chaos. Covers the ADKAR model adapted for startups, communication templates, resistance patterns, and change fatigue management. Handles process changes, org restructures, strategy pivots, and culture changes. Use when announcing a reorg, switching tools, pivoting strategy, killing a product, changing leadership, or when user mentions change management, change rollout, managing resistance, org change, reorg, or pivot communication.
2081. cmo-review alirezarezvani/claude-skills · score 67/100 (grade C)
      /c-level-agents:cmo-review [plan] — Narrative-first interrogation of positioning, ICP, message house, and channel mix. Use when launching a campaign or repositioning, or when CAC is rising and the one-sentence positioning test fails.
2082. coding-agent-rollout alirezarezvani/claude-skills · score 67/100 (grade C)
      Use when rolling Claude Code out to a team or organization, or auditing a rollout already under way — writing or reviewing shared and managed settings.json permissions, deciding which MCP servers, plugins and marketplaces to approve, cleaning up layered CLAUDE.md files, or measuring whether the team actually uses it. Lints settings across scopes, inventories every MCP server and plugin against an approved list, resolves CLAUDE.md layers and imports, and turns local session data into privacy-safe adoption counts.
2083. context-agent sickn33/antigravity-awesome-skills · score 67/100 (grade C)
      Agente de contexto para continuidade entre sessoes. Salva resumos, decisoes, tarefas pendentes e carrega briefing automatico na sessao seguinte.
2084. context-budget affaan-m/ECC · score 67/100 (grade C)
      Routes live context checks to the native Codex or Claude Code meter without scanning files, and performs a bounded static component audit only when explicitly requested. Use for context-budget requests about remaining capacity or installed context overhead.
2085. context-budget affaan-m/everything-claude-code · score 67/100 (grade C)
      Routes live context checks to the native Codex or Claude Code meter without scanning files, and performs a bounded static component audit only when explicitly requested. Use for context-budget requests about remaining capacity or installed context overhead.
2086. convert-plaintext-to-md github/awesome-copilot · score 67/100 (grade C)
      Convert a text-based document to markdown following instructions from prompt, or if a documented option is passed, follow the instructions for that option.
2087. copilot-sdk github/awesome-copilot · score 67/100 (grade C)
      Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.
2088. cs-quality-regulatory alirezarezvani/claude-skills · score 67/100 (grade C)
      Quality & Regulatory agent for ISO 13485 QMS, MDR compliance, FDA submissions, GDPR/DSGVO, and ISMS audits. Orchestrates ra-qm-team skills. Spawn when users need regulatory strategy, audit preparation, CAPA management, risk management, or compliance documentation.
2089. directory-submissions coreyhaines31/marketingskills · score 67/100 (grade C)
      When the user wants to submit their product to startup, SaaS, AI, agent, MCP, no-code, or review directories for backlinks, domain rating, and discovery. Also use when the user mentions "directory submissions," "submit to directories," "backlinks from directories," "list my product," "submit to Product Hunt," "BetaList," "TAAFT," "Futurepedia," "G2 listing," "Capterra listing," "AlternativeTo," "SaaSHub," "AI directories," "MCP registry," "publish my MCP server," "awesome list," "llms.txt directory," "Claude plugin directory," "agent directory," "dofollow backlinks," "launch directories," or "directory tracker." Use this whenever someone is planning the directory layer of a product launch or an ongoing backlink campaign. For the broader launch moment, see launch. For programmatic SEO pages that should live behind these backlinks, see programmatic-seo. For AI citation optimization, see ai-seo.
2090. dotnet-mcp-builder github/awesome-copilot · score 67/100 (grade C)
      Build Model Context Protocol (MCP) servers in C#/.NET against the current ModelContextProtocol 2.x NuGet packages. Helps with cases the model gets wrong without guidance — stale versions (0.x preview or 1.x-era defaults), the v2 stateless-by-default HTTP flip, the 2026-07-28 spec deprecations (roots/sampling/logging), MCP Apps and Tasks extension packages, elicitation URL mode, per-session HTTP wiring, OAuth and reverse-proxy deploy specifics, and debugging MapMcp / STDIO / Streamable-HTTP errors. Also covers STDIO and Streamable HTTP transports (SSE is deprecated), tools, prompts, resources, completions, and a basic .NET MCP client. Trigger when the user says or implies any .NET MCP server work: ModelContextProtocol, McpServerTool, MapMcp, WithStdioServerTransport, "MCP server in C#", "MCP tool in dotnet", "expose this as MCP", or names a primitive (prompt/resource/elicitation/MCP App) in a .NET context. Skip for MCP work in other languages.
2091. ecc-recipes affaan-m/ECC · score 67/100 (grade C)
      Map a described workflow to the right ECC command group with run-order and stop condition, or browse all command-group recipe families read live from the commands directory. Advisory only — never executes. Use when asked which commands run a workflow, the command sequence for a task, or to list ECC pipelines; not for executing the task (route to the command itself), single-command docs (use ecc-guide), or prompt rewrites (use prompt-optimizer).
2092. ecc-recipes affaan-m/everything-claude-code · score 67/100 (grade C)
      Map a described workflow to the right ECC command group with run-order and stop condition, or browse all command-group recipe families read live from the commands directory. Advisory only — never executes. Use when asked which commands run a workflow, the command sequence for a task, or to list ECC pipelines; not for executing the task (route to the command itself), single-command docs (use ecc-guide), or prompt rewrites (use prompt-optimizer).
2093. fable-safe-prompt davidondrej/skills · score 67/100 (grade C)
      Make minimal prompt edits to reduce false-positive refusals from Fable. Use only when the user explicitly invokes /fable-safe-prompt.
2094. gdpr-compliant github/awesome-copilot · score 67/100 (grade C)
      Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
2095. ghidra-reverse sickn33/antigravity-awesome-skills · score 67/100 (grade C)
      Free/open reverse engineering with Ghidra (headless or GUI): decompilation, cross-references, scripting, and optional Ghidra MCP workflows when IDA is unavailable.
2096. gke-ai-troubleshooting-tpu-vbar-oom google/skills · score 67/100 (grade C)
      Diagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.
2097. google-cloud-solution-agentic-ai-bidirectional-streaming google/skills · score 67/100 (grade C)
      Guides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements.
2098. google-cloud-solution-agentic-ai-borderless-data-lakehouse google/skills · score 67/100 (grade C)
      Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).
2099. google-cloud-solution-agentic-analytics-spark-knowledge-catalog google/skills · score 67/100 (grade C)
      Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).
2100. google-cloud-solution-guided-gke-ai-migration google/skills · score 67/100 (grade C)
      Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
2101. Hunter Automation ComposioHQ/awesome-claude-skills · score 67/100 (grade C)
      Automate Hunter.io email intelligence -- search domains for email addresses, find specific contacts, verify email deliverability, manage leads, and monitor account usage -- using natural language through the Composio MCP integration.
2102. improve-animations emilkowalski/skills · score 67/100 (grade C)
      Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.
2103. Instantly Automation ComposioHQ/awesome-claude-skills · score 67/100 (grade C)
      Automate Instantly cold email outreach -- manage campaigns, sending accounts, lead lists, bulk lead imports, and campaign analytics -- using natural language through the Composio MCP integration.
2104. LaunchDarkly Automation ComposioHQ/awesome-claude-skills · score 67/100 (grade C)
      Automate LaunchDarkly feature flag management -- list projects and environments, create and delete trigger workflows, and track code references via the Composio MCP integration.
2105. mantis-threat-model google/mantis · score 67/100 (grade C)
      Synthesizes trust boundaries, attack surfaces, and attacker profiles into a living threat model. Use as Stage B of the Knowledge Base generation process, reading architecture and entity definitions from the KB. Don't use for analyzing source code or extracting raw learnings from JSONL files.
2106. marketing-plan coreyhaines31/marketingskills · score 67/100 (grade C)
      When the user needs a comprehensive marketing plan for a client, a company they advise, or their own product. Also use when the user mentions "marketing plan," "growth plan," "GTM plan," "go-to-market plan," "AARRR plan," "90-day marketing plan," "12-month marketing roadmap," "fractional CMO plan," "fCMO plan," "market sizing," "TAM SAM SOM," "how big is this market," or "market research." Generates an exhaustive 13-section plan structured by AARRR (Acquisition, Activation, Retention, Referral, Revenue), customized to the client's current budget, team, and stage, mapped to future funding milestones, cross-referenced with the 139-idea marketing-ideas library and an embedded 17-section current-state audit rubric, with a marketing operations stack showing which skills and MCP/API integrations execute each part. Outputs a Notion-paste-ready markdown document. For positioning and ICP context before planning, see product-marketing. For stage-specific deep work, see onboarding, signup, emails, referrals, pricing.
2107. ml-adoption-playbook affaan-m/ECC · score 67/100 (grade C)
      End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.
2108. ml-adoption-playbook affaan-m/everything-claude-code · score 67/100 (grade C)
      End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.
2109. onboarding-optimization Eronred/aso-skills · score 67/100 (grade C)
      When the user wants to improve their app's onboarding experience, increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow. Use when the user mentions "onboarding", "first-run", "activation", "tutorial", "day 1 retention", "new user flow", "permission prompts", "sign-up conversion", "onboarding funnel", or "users dropping off early". For overall retention strategy, see retention-optimization. For paywall placement, see monetization-strategy.
2110. orch-refine-code affaan-m/ECC · score 67/100 (grade C)
      Orchestrate a behavior-preserving refactor — confirm tests are green, restructure without changing behavior, keep tests green, review, and gated commit. Use when the structure should improve but behavior must not change.
2111. orch-refine-code affaan-m/everything-claude-code · score 67/100 (grade C)
      Orchestrate a behavior-preserving refactor — confirm tests are green, restructure without changing behavior, keep tests green, review, and gated commit. Use when the structure should improve but behavior must not change.
2112. project-workflow-analysis-blueprint-generator github/awesome-copilot · score 67/100 (grade C)
      Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.
2113. prototype mattpocock/skills · score 67/100 (grade C)
      Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
2114. rails-patterns affaan-m/ECC · score 67/100 (grade C)
      Ruby on Rails framework patterns for Rails 7.1+ and 8.x apps. Covers the directory contract, skinny controllers with service objects, form objects, query objects, idiomatic ActiveRecord, background jobs, ViewComponent, Hotwire, and the Rails 8 Solid stack. Use when building or reviewing Rails apps, controllers, models, services, jobs, or views.
2115. rails-patterns affaan-m/everything-claude-code · score 67/100 (grade C)
      Ruby on Rails framework patterns for Rails 7.1+ and 8.x apps. Covers the directory contract, skinny controllers with service objects, form objects, query objects, idiomatic ActiveRecord, background jobs, ViewComponent, Hotwire, and the Rails 8 Solid stack. Use when building or reviewing Rails apps, controllers, models, services, jobs, or views.
2116. rhino3d-scripts github/awesome-copilot · score 67/100 (grade C)
      Authoring and debugging scripts for Rhinoceros 3D (Rhino 8 and later). Use when asked to write RhinoScript (VBScript / .rvb / .vbs), RhinoPython, or RhinoCommon-based scripts; automate Rhino modeling tasks; build command macros; manipulate Rhino geometry, layers, blocks, or document objects; pick objects from the viewport; control redraw and undo; or load and run scripts from the Rhino Script Editor. Covers `rhinoscriptsyntax`, `scriptcontext`, the `Rhino.*` RhinoCommon namespaces (`Rhino.Geometry`, `Rhino.DocObjects`, `Rhino.Input`, `Rhino.UI`, `Rhino.Display`, `Rhino.FileIO`), and the Rhino 8 unified Script Editor.
2117. search entireio/skills · score 67/100 (grade C)
      Use when the user asks to research, investigate, look into, dig into, or search for anything — a topic, feature, bug, decision, or "what do we know about X". Invoke this as the FIRST action on such requests, before Glob, Grep, or Read: the answer is in Entire's recorded history (prompts, transcripts, and decisions, across repos), not in the local files, and a working copy that looks empty or unfamiliar is not a reason to skip it. Also use to find code across repositories ("where is X implemented in our other repos"). Not for grepping the current working copy on its own, and not for the current active session.
2118. session-crosslink entireio/skills · score 67/100 (grade C)
      Use when an agent session ran outside the repo whose commits should record it — e.g. launched from a higher-level folder, a non-Entire repo, or one repo but editing another — to attach the session to each affected Entire-enabled repo's HEAD commit.
2119. skill-comply affaan-m/ECC · score 67/100 (grade C)
      Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.
2120. skill-comply affaan-m/everything-claude-code · score 67/100 (grade C)
      Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.
2121. skill-development Galaxy-Dawn/claude-scholar · score 67/100 (grade C)
      This skill should be used when the user asks to create a new skill, repair an existing skill, improve trigger descriptions, reorganize skill structure, or make a Claude skill more reusable and internally consistent.
2122. spinning-up-deep-rl alirezarezvani/claude-skills · score 67/100 (grade C)
      Knowledge base from \"Spinning Up in Deep RL\" by Joshua Achiam (OpenAI, MIT-licensed). Use when applying Achiam's frameworks for RL fundamentals and MDPs, the model-free algorithm taxonomy, policy gradient derivations, the six reference algorithms (VPG, TRPO, PPO, DDPG, TD3, SAC), debugging silently-failing RL code, or running rigorous multi-seed RL experiments.
2123. triage mattpocock/skills · score 67/100 (grade C)
      Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.
2124. 3-statement-model anthropics/financial-services · score 66/100 (grade C)
      Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) . Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS/BS/CF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template
2125. aeo alirezarezvani/claude-skills · score 66/100 (grade C)
      Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
2126. affiliate-program-search Affitor/affiliate-skills · score 66/100 (grade C)
      Compatibility pointer for finding and comparing affiliate programs. Use find-and-verify-affiliate-program for the current MCP-first discovery and verification workflow.
2127. agent-architecture-audit affaan-m/ECC · score 66/100 (grade C)
      Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.
2128. agent-architecture-audit affaan-m/everything-claude-code · score 66/100 (grade C)
      Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.
2129. ai-risk-management briiirussell/cybersecurity-skills · score 66/100 (grade C)
      Apply the NIST AI Risk Management Framework (AI RMF 1.0) and adjacent guidance to AI / ML systems — model lifecycle governance, fairness and bias evaluation, robustness, transparency, accountability, third-party model risk, monitoring for drift, and AI incident response. Broader than prompt-injection (which is the security slice). Use when the user mentions 'AI risk,' 'AI governance,' 'NIST AI RMF,' 'AI compliance,' 'ML governance,' 'model risk management,' 'AI fairness,' 'AI bias,' 'algorithmic accountability,' 'AI Bill of Rights,' 'EU AI Act,' 'AI transparency,' 'model card,' 'AI red team,' 'AI safety,' 'responsible AI,' 'model drift,' 'concept drift,' 'AI monitoring,' 'AI incident,' or needs to assess or govern an AI / ML system.
2130. analytics coreyhaines31/marketingskills · score 66/100 (grade C)
      When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For getting conversions into ad platforms (pixels, conversion tags, CAPI, server-side) and verifying they arrived, see conversion-tracking. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing. Rate metrics divide matching closed windows — never full-period spend by partial-period results.
2131. bio-admet-prediction GPTomics/bioSkills · score 66/100 (grade C)
      Predicts ADMET properties using ADMETlab 3.0 (119 platform features, including 77 prediction models with modeled-endpoint uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR model.
2132. bio-experimental-design-sample-size GPTomics/bioSkills · score 66/100 (grade C)
      Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.
2133. bio-flow-cytometry-bead-normalization GPTomics/bioSkills · score 66/100 (grade C)
      Bead-based signal normalization and cross-batch harmonization for CyTOF and high-parameter cytometry - EQ four-element bead normalization of instrument sensitivity drift (CATALYST normCytof, premessa), and reference-anchor cross-batch normalization (CytoNorm, per-cluster quantile splines). Covers the distinction between within-run drift correction and between-batch correction, the mandatory anchor/reference sample, why normalization is per-cluster with many quantiles, and the over-correction risk. Use when correcting CyTOF signal drift, harmonizing multi-batch or multi-site studies, or deciding whether to normalize data versus model batch in the design.
2134. bio-flow-cytometry-gating-analysis GPTomics/bioSkills · score 66/100 (grade C)
      Defines cell populations in flow and spectral cytometry through manual gates (rectangle, polygon, quadrant, boolean) and reproducible automated gating (openCyto gating templates, flowDensity data-driven thresholds, flowClust model-based gates), organized as a hierarchical GatingSet (flowWorkspace) and round-tripped with FlowJo via CytoML. Covers the canonical gate order (time -> debris -> singlets -> live -> lineage), FMO-vs-isotype boundary setting, gate-order dependence and recompute semantics, rare-event/MRD gating, and per-population statistics. Use when building a gating strategy, automating a manual FlowJo scheme across samples, choosing manual vs data-driven gates, or extracting population frequencies.
2135. bio-genome-engineering-grna-design GPTomics/bioSkills · score 66/100 (grade C)
      Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.
2136. bio-long-read-sequencing-basecalling GPTomics/bioSkills · score 66/100 (grade C)
      Basecalls raw Oxford Nanopore signal (POD5/FAST5) into reads with Dorado, choosing the chemistry-matched model and accuracy tier (fast/hac/sup), requesting modified bases (5mCG_5hmCG, 6mA, m6A) at basecall time, and handling duplex, demultiplexing, trimming, and HERRO read correction. Covers why the model+version is an irreversible analysis decision, why methylation cannot be recovered later, and why downstream polish/variant models must match the basecaller. Use when converting POD5/FAST5 to reads, picking a Dorado model for R9/R10 or RNA004, enabling methylation calling, basecalling duplex, demultiplexing barcoded runs, or correcting reads for assembly.
2137. bio-machine-learning-atlas-mapping GPTomics/bioSkills · score 66/100 (grade C)
      Maps query single-cell data onto reference atlases and transfers cell-type labels using scArches surgery (scVI/scANVI), Symphony, Azimuth, CellTypist, scPoli, popV, and foundation models, with explicit out-of-distribution and label-transfer uncertainty. Use when annotating new single-cell datasets against a pre-trained reference, deciding which mapping method fits, or judging whether transferred labels are trustworthy. For de novo clustering and manual annotation see single-cell/cell-annotation; for batch integration without a reference see single-cell/batch-integration.
2138. bio-machine-learning-omics-classifiers GPTomics/bioSkills · score 66/100 (grade C)
      Builds diagnostic and prognostic classifiers on omics feature matrices with regularized logistic regression, random forest, and gradient-boosted trees, handling the p>>n regime, batch shortcut learning, class imbalance, and probability calibration. Use when building a classifier from expression, methylation, or variant data, choosing an algorithm for high-dimensional small-n data, or diagnosing a suspiciously perfect AUC. For unbiased evaluation see machine-learning/model-validation; for feature selection see machine-learning/biomarker-discovery; for time-to-event outcomes see machine-learning/survival-analysis.
2139. bio-metagenomics-visualization GPTomics/bioSkills · score 66/100 (grade C)
      Turns a shotgun profiler table (MetaPhlAn relative abundance, Bracken counts, HUMAnN function tables) into honest figures and defensible community statistics with phyloseq, vegan, microViz, and Python. Covers why an ordination/bar/diversity number is a modeling choice that can manufacture a result, the MetaPhlAn-percent-vs-Bracken-counts fork that decides everything, CLR/Aitchison vs Bray-Curtis, Hill numbers and why shotgun richness is a database readout, pairing PERMANOVA with betadisper, and the multi-tool differential-abundance consensus. Use when plotting taxonomic/functional profiles, computing alpha/beta diversity, running ordination/PERMANOVA, or testing differential abundance. For amplicon/QIIME2 stats see the microbiome category; for compositional theory see abundance-estimation.
2140. bio-methylation-differential-cpg GPTomics/bioSkills · score 66/100 (grade C)
      Tests individual CpG sites for differential methylation (DMC/DMP) from bisulfite sequencing counts or array/continuous beta-value matrices. Covers the count-vs-continuous fork that dictates the model, beta-value vs M-value logit (Du 2010), beta-binomial overdispersion count models (DSS, methylKit, MOABS, RADMeth) for sequencing, limma moderated-t on M-values (eBayes trend/robust) for arrays, the bare-beta Welch t-test caveat, coverage-as-precision coupling, delta-beta effect size, BH-FDR with the neighboring-CpG dependence problem, EWAS genome-wide thresholds, and differential variability (DiffVar/iEVORA). Use when comparing per-CpG methylation between groups from WGBS/RRBS/targeted bisulfite or 450K/EPIC arrays, choosing a per-site test, or scanning for variance (not just mean) differences. For region-level aggregation see dmr-detection; for covariate/cell-fraction strategy and genomic inflation see ewas-design.
2141. bio-tcr-bcr-analysis-scirpy-analysis GPTomics/bioSkills · score 66/100 (grade C)
      Integrates single-cell paired TCR/BCR (10x VDJ, AIRR, dandelion, BD Rhapsody) with gene expression in an AnnData/MuData object using scirpy - chain-pairing QC, clonotype definition, clonal expansion, diversity, repertoire overlap, V(D)J usage, and VDJdb specificity. Operates on the awkward-array AIRR model (adata.obsm['airr'], accessed via get.airr after pp.index_chains), not legacy per-chain obs columns. Use when deciding clonotype definition for TCR (exact CDR3-nt identity via define_clonotypes) versus BCR (nucleotide distance clustering via define_clonotype_clusters with normalized_hamming plus same_v_gene/same_j_gene, because somatic hypermutation shatters identity clonotypes); tuning receptor_arms (all vs any), dual_ir, and within_group; filtering chain_qc categories (multichain doublets, orphan dropout, extra-VJ dual-TCR) without biasing clonal-expansion and diversity estimates; and overlaying clonality onto the transcriptomic UMAP.
2142. bio-workflows-chipseq-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates the end-to-end ChIP-seq pipeline from FASTQ to blacklist-filtered, annotated peaks, chaining fastp QC, Bowtie2 alignment, pre-dedup library-complexity QC (NRF/PBC), duplicate removal, chrM + ENCODE-blacklist filtering, MACS3 peak calling against a matched input, IDR/consensus reproducibility, deepTools signal tracks, and ChIPseeker annotation. Use when committing the reference build + blacklist version + effective genome size once, pairing each IP with its matched control, computing complexity metrics BEFORE dedup, choosing narrow vs broad and MACS3 vs SEACR/Genrich, keeping per-replicate peaks for IDR, or avoiding depth-normalization that erases a spike-in global shift. Hands mechanism to the chip-seq component skills; not a re-teach of any single step.
2143. bio-workflows-crispr-editing-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates an end-to-end CRISPR editing experiment design from target gene to delivery-ready, validatable constructs. Sequences guide design, off-target assessment, edit-modality selection (knockout, base editing, prime editing, HDR knock-in), and template/donor design, with a QC checkpoint at each handoff. Use when designing a complete CRISPR experiment for knockout, point correction, or tagging and the order of operations, the modality decision, and the cross-cutting traps are needed rather than a single step. Defers each step's mechanics to the genome-engineering skills.
2144. bio-workflows-crispr-screen-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      End-to-end pooled and single-cell CRISPR screen analysis from FASTQ to hit genes. Orchestrates library design QC, guide counting, six-stage screen QC (plasmid Gini, replicate Pearson, CEGv2 PR-AUC, copy-number artifact), method-appropriate hit calling across MAGeCK RRA/MLE, BAGEL2, drugZ, JACKS, and Chronos, cancer-cell-line copy-number correction (CRISPRcleanR / Chronos), batch correction for multi-batch screens, and the specialized branches for combinatorial paralog screens, single-cell Perturb-seq, base-editor variant-function screens, prime-editor screens, and in vivo bottleneck-aware screens. Use when analyzing any pooled CRISPR screen end-to-end, matching the hit-calling method to the experimental design, integrating copy-number correction into the pipeline, or branching the workflow for single-cell, combinatorial, base-editor, prime-editor, or in vivo variants.
2145. bio-workflows-cytometry-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      End-to-end flow, spectral, and mass cytometry (CyTOF) pipeline from raw FCS files to differentially abundant/expressed cell populations. Orchestrates the read -> compensate/unmix -> transform -> QC -> doublet-removal -> cluster-or-gate -> annotate -> diffcyt DA/DS chain with flowCore/CATALYST/diffcyt, branching on instrument type and on clustering-vs-gating. Use when processing a cytometry experiment end-to-end, deciding the pipeline path for an instrument, or wiring the flow-cytometry component skills into one analysis with valid sample-level statistics.
2146. bio-workflows-expression-to-pathways GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates the full path from differential expression results to redundancy-collapsed functional enrichment: choose ORA vs GSEA, convert gene IDs per method, run enrichGO/enrichKEGG/enrichPathway/enrichWP or gseGO/gseKEGG (clusterProfiler, ReactomePA, rWikiPathways), and visualize. Use when a DESeq2/edgeR/limma result must become enriched GO terms, KEGG/Reactome/WikiPathways pathways, or a GSEA leading edge; when the input is a full ranking for all genes (GSEA, named decreasing vector) or only a pre-selected list (ORA plus a defensible background universe); or when assembling DE-to-pathway end to end. The DE list and ranking statistic come from differential-expression/de-results; per-method nuance lives in the pathway-analysis skills.
2147. bio-workflows-genome-annotation-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates genome annotation from assembled contigs to functional annotation, forking prokaryotic (Bakta one-step, genetic-code table from GTDB-Tk) vs eukaryotic (RepeatMask -> BRAKER3 -> functional -> ncRNA), then eggNOG/InterProScan functional assignment and Infernal/tRNAscan ncRNA. Use when committing the pro-vs-eukaryotic path and the genetic-code table from taxonomy (never guessing), annotating ONLY a decontaminated QC-passed assembly (CheckM2 before prokaryotic annotation is non-negotiable), committing the evidence set (RNA-seq + protein drives BRAKER3 training), soft-masking with a curated repeat library before gene prediction, or pinning the tool + DB version for any pangenome comparison. Hands mechanism to the genome-annotation component skills; not a re-teach of any single step.
2148. bio-workflows-genome-assembly-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates an end-to-end de novo genome assembly project, routing each step to the right genome-assembly skill rather than restating it. Profiles the genome first (k-mer spectrum -> size, heterozygosity, ploidy), QCs reads, chooses an assembly path by data type (SPAdes for Illumina, Flye for noisy long reads, hifiasm for HiFi, metaFlye for communities), polishes only when needed, decontaminates, scaffolds with Hi-C, and finishes with three-axis QC (contiguity + completeness + correctness). Use when assembling a genome from raw reads and deciding which assembler, whether to polish, and how to prove the result is good.
2149. bio-workflows-imc-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates imaging mass cytometry from raw MCD acquisitions to patient-level spatial analysis, chaining steinbock preprocessing, Mesmer/Cellpose segmentation, single-cell quantification, phenotyping, and squidpy spatial statistics. Use when committing the panel + segmentation frame + pixel size (every per-cell number is a mask-bounded pixel average), compensating channel spillover on PIXELS before segmentation but running REDSEA lateral-spillover on the per-cell table AFTER segmentation, using arcsinh cofactor 1 (not the suspension-CyTOF 5), and aggregating to the PATIENT before any cross-condition test (cells and ROIs from one patient are not independent replicates). Hands mechanism to the imaging-mass-cytometry component skills; not a re-teach of any single step.
2150. bio-workflows-metabolic-modeling-pipeline GPTomics/bioSkills · score 66/100 (grade C)
      Orchestrates genome-scale metabolic modeling from a protein FASTA to flux predictions, chaining CarveMe/gapseq reconstruction, memote QC, gap-filling, media-constrained FBA/FVA, gene essentiality, and context-specific models. Use when committing the reconstruction tool (which locks the identifier NAMESPACE forever - BiGG vs ModelSEED vs KEGG, no automatic translation), setting the medium BEFORE FBA (the exchange bounds ARE the medium; essentiality and gap-fill are computed relative to it), curating iteratively (stoichiometric-consistency first, then mass/charge, then directionality, then GPR) with energy-generating-cycle removal, and reading a MEMOTE score as well-formedness NOT correctness. Hands mechanism to the systems-biology component skills; not a re-teach of any single step.
2151. cli-mastery github/awesome-copilot · score 66/100 (grade C)
      Interactive training for the GitHub Copilot CLI. Guided lessons, quizzes, scenario challenges, and a full reference covering slash commands, shortcuts, modes, agents, skills, MCP, and configuration. Say "cliexpert" to start.
2152. cost-aware-llm-pipeline affaan-m/ECC · score 66/100 (grade C)
      Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching. Use when LLM spend needs to come down, or when routing tasks across model tiers and budgets.
2153. cost-aware-llm-pipeline affaan-m/everything-claude-code · score 66/100 (grade C)
      Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching. Use when LLM spend needs to come down, or when routing tasks across model tiers and budgets.
2154. cro-review alirezarezvani/claude-skills · score 66/100 (grade C)
      /c-level-agents:cro-review [plan] — Pipeline-paranoid interrogation of revenue, win rate, NRR, and ramp time. Use when the forecast misses pipeline coverage, win rates drop, or before scaling the sales team.
2155. cs-backend-engineer alirezarezvani/claude-skills · score 66/100 (grade C)
      Backend-engineering orchestrator. Walks the 7 Matt Pocock forcing questions (read/write ratio + QPS, tenancy, sync vs async, data sensitivity, pattern, RPO/RTO, SLO), picks the language + pattern profile, forks into specialists (api-design-reviewer, database-designer, migration-architect, observability-designer, slo-architect — listed alphabetically; workflow order is dependency-driven) rather than reimplementing their scope. Forks own context. Invoke via /cs-backend-review or Agent({subagent_type:"cs-backend-engineer",...}).
2156. cs-content-creator alirezarezvani/claude-skills · score 66/100 (grade C)
      Long-form marketing content producer orchestrating the content-production skill (research → brief → draft → optimize → gate). Use when content must be written, scored, or made publish-ready — e.g., drafting a 2,000-word blog post against a target keyword and blocking publish until content_quality_gates.py passes, or auditing a draft for brand-voice drift with brand_voice_analyzer.py before it ships. Routes planning requests (topic clusters, calendars) to content-strategy. Supersedes the deprecated content-creator skill.
2157. cs-engineering-lead alirezarezvani/claude-skills · score 66/100 (grade C)
      Engineering Team Lead agent for coordinating QA, security, data engineering, ML, and frontend/backend teams. Orchestrates engineering-team skills for team-level technical decisions. Spawn when users need team coordination, tech stack evaluation, incident response, or cross-functional engineering work.
2158. deep-research affaan-m/ECC · score 66/100 (grade C)
      Produce cited research reports from multiple web sources using firecrawl and exa MCP tools — plan sub-questions, search and deep-read sources, then synthesize findings with inline citations and confidence levels. Use when the user asks to research a topic in depth, run a deep dive or investigation, or do competitive analysis, technology evaluation, market sizing, or due diligence on a company.
2159. deep-research affaan-m/everything-claude-code · score 66/100 (grade C)
      Produce cited research reports from multiple web sources using firecrawl and exa MCP tools — plan sub-questions, search and deep-read sources, then synthesize findings with inline citations and confidence levels. Use when the user asks to research a topic in depth, run a deep dive or investigation, or do competitive analysis, technology evaluation, market sizing, or due diligence on a company.
2160. detection-engineering-coverage-evaluation google/skills · score 66/100 (grade C)
      Automates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage, and deploying gap-closing rules. Don't use for standalone YARA-L 2.0 rule authoring/tuning (use secops-detection-engineering), threat hunting, or SOC investigation.
2161. domain-modeling mattpocock/skills · score 66/100 (grade C)
      Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
2162. ffuf-claude-skill sickn33/antigravity-awesome-skills · score 66/100 (grade C)
      Web fuzzing with ffuf
2163. find-skills bytedance/deer-flow · score 66/100 (grade C)
      Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
2164. flowstudio-power-automate-monitoring github/awesome-copilot · score 66/100 (grade C)
      Pro+ subscription required. Tenant-wide Power Automate monitoring using the FlowStudio MCP cached store: failure rates, run-health trends, maker/app inventory, inactive owners, and compliance/health reports. Use only for aggregated tenant views. For one environment, one flow, run control, or root-cause debugging, use flowstudio-power-automate-mcp, flowstudio-power-automate-debug, or the server monitor-flow bundle. Requires FlowStudio for Teams or MCP Pro+.
2165. gc-review alirezarezvani/claude-skills · score 66/100 (grade C)
      /c-level-agents:gc-review [plan] — General Counsel interrogation of contracts, IP, regulatory, term sheets, and employment-law surface. Use when reviewing a term sheet before signing, redlining a customer MSA, or checking IP assignment and regulatory exposure on a new product.
2166. gemini-agents-api google/skills · score 66/100 (grade C)
      Manages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.
2167. google-cloud-waf-sustainability google/skills · score 66/100 (grade C)
      Provides recommendations for environmental sustainability, carbon footprint reduction, and energy efficiency based on the Sustainability pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks to assess, design, or optimize Google Cloud workloads for sustainability—including the shared responsibility model, selecting low-carbon regions (CFE%), reducing resource and AI/ML energy waste, designing efficient software and storage lifecycles, or measuring and tracking emissions using Google Cloud Carbon Footprint. Don't use for financial cost reduction (use google-cloud-waf-cost-optimization), latency and throughput tuning (use google-cloud-waf-performance-optimization), or high availability and disaster recovery (use google-cloud-waf-reliability).
2168. ios-debugger-agent Dimillian/Skills · score 66/100 (grade C)
      Use XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state, capture logs/console output, or diagnose runtime behavior using XcodeBuildMCP tools.
2169. llm-trading-agent-security affaan-m/ECC · score 66/100 (grade C)
      Security patterns for autonomous trading agents with wallet or transaction authority. Covers prompt injection, spend limits, pre-send simulation, circuit breakers, MEV protection, and key handling. Use when an autonomous agent holds wallet or transaction authority and its limits, simulation, or key handling need review.
2170. llm-trading-agent-security affaan-m/everything-claude-code · score 66/100 (grade C)
      Security patterns for autonomous trading agents with wallet or transaction authority. Covers prompt injection, spend limits, pre-send simulation, circuit breakers, MEV protection, and key handling. Use when an autonomous agent holds wallet or transaction authority and its limits, simulation, or key handling need review.
2171. md-review alirezarezvani/claude-skills · score 66/100 (grade C)
      Converts a markdown PR writeup or code review (one with ```diff fenced blocks and severity-tagged GFM callouts [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer. Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs-md-review. Refuses without explicit --reviewer (a code review must name a human), refuses if no diff hunks present (route to md-document instead), and refuses to encode severity in color only (every badge ships color + icon + aria-label per WCAG 1.4.1). Use after orchestrator routing.
2172. mmx-cli MiniMax-AI/skills · score 66/100 (grade C)
      Use mmx to generate text, images, video, speech, and music via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, perform web search, or manage MiniMax API resources from the terminal.
2173. ot-ics sickn33/antigravity-awesome-skills · score 66/100 (grade C)
      Authorized OT/ICS security assessment: Purdue-model zoning review, PLC/SCADA exposure, industrial protocol discovery, and passive-first evaluation discipline.
2174. pytorch-patterns affaan-m/ECC · score 66/100 (grade C)
      PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Use when writing or reviewing PyTorch training loops, model architectures, or data loading, or when a run will not reproduce.
2175. pytorch-patterns affaan-m/everything-claude-code · score 66/100 (grade C)
      PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Use when writing or reviewing PyTorch training loops, model architectures, or data loading, or when a run will not reproduce.
2176. rag-architect alirezarezvani/claude-skills · score 66/100 (grade C)
      Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for this corpus', 'evaluate my retriever against ground truth'. NOT for general LLM cost tuning (use llm-cost-optimizer) or agent loops over retrieval (use agenthub).
2177. react-performance affaan-m/ECC · score 66/100 (grade C)
      React and Next.js performance optimization patterns adapted from Vercel Engineering's React Best Practices (https://github.com/vercel-labs/agent-skills). Organizes 70+ rules across 8 priority categories — waterfalls, bundle size, server-side, client fetching, re-render, rendering, JS micro-perf, advanced. Use when writing, reviewing, or refactoring React/Next.js code for performance.
2178. react-performance affaan-m/everything-claude-code · score 66/100 (grade C)
      React and Next.js performance optimization patterns adapted from Vercel Engineering's React Best Practices (https://github.com/vercel-labs/agent-skills). Organizes 70+ rules across 8 priority categories — waterfalls, bundle size, server-side, client fetching, re-render, rendering, JS micro-perf, advanced. Use when writing, reviewing, or refactoring React/Next.js code for performance.
2179. senior-data-scientist alirezarezvani/claude-skills · score 66/100 (grade C)
      World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing, two-proportion z-tests, Bonferroni correction), difference-in-differences, feature engineering pipelines (Scikit-learn, XGBoost), cross-validated model evaluation (AUC-ROC, AUC-PR, SHAP), and MLflow experiment tracking — using Python (NumPy, Pandas, Scikit-learn), R, and SQL. Use when designing or analysing controlled experiments, building and evaluating classification or regression models, performing causal analysis on observational data, engineering features for structured tabular datasets, or translating statistical findings into data-driven business decisions.
2180. skillopt-sleep alirezarezvani/claude-skills · score 66/100 (grade C)
      Use when the user wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill consolidation, or says things like 'make my agent better the more I use it', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule offline self-optimization. Drives the skillopt_sleep engine: harvest past sessions → mine recurring tasks → replay offline → consolidate validated CLAUDE.md and SKILL.md behind a held-out gate.
2181. sql-code-review github/awesome-copilot · score 66/100 (grade C)
      Universal SQL code review assistant that performs comprehensive security, maintainability, and code quality analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Focuses on SQL injection prevention, access control, code standards, and anti-pattern detection. Complements SQL optimization prompt for complete development coverage.
2182. threejs-aaa-graphics-builder majidmanzarpour/threejs-game-skills · score 66/100 (grade C)
      Upgrade Three.js games from prototype visuals to premium browser graphics: art-direction critique, procedural model building, material and texture libraries, world prop kits, shaders, VFX, lighting and render pipeline, LOD and instancing, render budgets, and a 10-category visual scorecard. Use when screenshots still look basic or the user asks for premium, AAA, high-fidelity, showcase, or less-basic graphics.
2183. token-card affaan-m/ECC · score 66/100 (grade C)
      Render a token-usage stat card from local Claude Code, Codex, Gemini CLI, and OpenCode session logs and commit it into the repository as a file. Use when someone wants a current usage figure in a README, or asks for a shareable card of their coding-agent activity.
2184. token-card affaan-m/everything-claude-code · score 66/100 (grade C)
      Render a token-usage stat card from local Claude Code, Codex, Gemini CLI, and OpenCode session logs and commit it into the repository as a file. Use when someone wants a current usage figure in a README, or asks for a shareable card of their coding-agent activity.
2185. workspace-surface-audit affaan-m/ECC · score 66/100 (grade C)
      Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.
2186. workspace-surface-audit affaan-m/everything-claude-code · score 66/100 (grade C)
      Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.
2187. acreadiness-policy github/awesome-copilot · score 65/100 (grade C)
      Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.
2188. asc-testflight-orchestration rudrankriyam/app-store-connect-cli-skills · score 65/100 (grade C)
      Orchestrate TestFlight distribution, groups, testers, and What to Test notes using asc. Use when rolling out betas.
2189. bio-atac-seq-deep-learning-atac GPTomics/bioSkills · score 65/100 (grade C)
      Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or Enformer. Use when correcting Tn5 bias with neural networks beyond k-mer models, predicting per-base accessibility profiles, scoring in silico variant effects at GWAS or rare-variant SNPs, discovering motifs via DeepLIFT/TF-MoDISco from a trained model, or generating cell-type-specific accessibility predictions for unobserved cell states.
2190. bio-comparative-genomics-positive-selection GPTomics/bioSkills · score 65/100 (grade C)
      Detect positive (diversifying / episodic / pervasive) selection using codon dN/dS frameworks. Implements PAML codeml site models (M0/M1a/M2a/M7/M8/M8a), branch models, branch-site model A (Zhang 2005), and HyPhy methods (BUSTED, BUSTED-S, BUSTED-MH, BUSTED-PH, MEME, FEL, FUBAR, aBSREL, SLAC, RELAX, GARD, FUBAR-MH). Includes McDonald-Kreitman framework (asymptotic alpha, impMKT, polyDFE, DFE-alpha, GRAPES) for within-species + divergence inference, RERconverge for trait-correlated rate shifts, CSUBST for convergent substitution, and PhyloAcc for accelerated noncoding evolution. Use when testing adaptive evolution at codons, branches, or full gene; running GARD recombination pre-screen; controlling alignment-error and gBGC false positives; reconciling PAML vs HyPhy results; or performing genome-scale selection scans.
2191. bio-copy-number-copy-ratio-segmentation GPTomics/bioSkills · score 65/100 (grade C)
      Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.
2192. bio-data-visualization-interactive-visualization GPTomics/bioSkills · score 65/100 (grade C)
      Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.
2193. bio-experimental-design-power-analysis GPTomics/bioSkills · score 65/100 (grade C)
      Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.
2194. bio-immunoinformatics-epitope-prediction GPTomics/bioSkills · score 65/100 (grade C)
      Predict B-cell and T-cell epitopes for vaccine antigen design and epitope mapping with BepiPred-3.0, DiscoTope-3.0, the IEDB tools, and EL-mode MHC presentation. Encodes the load-bearing asymmetry that T-cell epitope prediction is mature (it reduces to MHC presentation, AUC>0.9) while B-cell prediction is unreliable (linear predictors ~AUC 0.6 because ~90% of real epitopes are conformational) — so structure-based DiscoTope-3.0 on AlphaFold models is the only defensible B-cell path, propensity scales are obsolete, and NetChop is largely redundant on EL-trained models. Use when mapping epitopes or selecting vaccine antigens. MHC binding lives in mhc-binding-prediction.
2195. bio-microbiome-qiime2-workflow GPTomics/bioSkills · score 65/100 (grade C)
      Operates the QIIME2 framework as the glue for an amplicon analysis - the .qza/.qzv artifact model, semantic types (FeatureTable[Frequency], SampleData[PairedEndSequencesWithQuality], Phylogeny[Rooted], FeatureData[Taxonomy]), embedded provenance plus provenance replay, import (Casava/manifest/EMP/BIOM), export, the Metadata object, and the q2cli vs Artifact API interfaces. Covers why a .qza is data-plus-executable-history not a file, why export drops provenance, why a .qzv is terminal, why classifier .qza are version-pinned, and the 2026 distribution/rachis rename. Use when importing reads, choosing a manifest/Casava/EMP/BIOM path, reading or replaying provenance, exporting to BIOM/phyloseq, fixing semantic-type or Phred or sklearn-version errors, or orchestrating the pipeline. Denoising -> amplicon-processing; classifier/DB -> taxonomy-assignment; diversity metric/depth -> diversity-analysis; DA tool -> differential-abundance; PICRUSt2 -> functional-prediction; shotgun moshpit -> metagenomics.
2196. bio-phylo-bayesian-inference GPTomics/bioSkills · score 65/100 (grade C)
      Frames Bayesian phylogenetics as approximating a posterior distribution over trees conditioned on data AND priors via an MCMC that must be proven to have converged, using MrBayes, BEAST2, RevBayes, and PhyloBayes-MPI. Covers why convergence (ESS, PSRF, ASDSF, topology vs scalar) is the load-bearing claim, why posterior probabilities are systematically higher than bootstrap and overconfident under model misspecification, why the default branch-length prior inflates tree length, why the harmonic-mean estimator must never select models (use stepping-stone), and when site-heterogeneous CAT-GTR is required at depth. Use when needing posterior clade support, model averaging, marginal-likelihood model comparison, or CAT models for deep phylogeny. Routes topology-only ML to modern-tree-inference, divergence times to divergence-dating, and tree summarization to tree-io.
2197. bio-phylo-divergence-dating GPTomics/bioSkills · score 65/100 (grade C)
      Estimate divergence times under molecular-clock models with BEAST2, MCMCTree/PAML, TreePL, and LSD2, framing a date as a product of the calibration prior and the clock model far more than of the sequence data. Covers why branch length = rate x time is nonidentifiable so only calibrations convert relative rate-time into absolute age; why the effective (marginal) prior on a calibrated node differs from the density specified, mandating a sample-from-prior run; the fossil-as-minimum rule, soft bounds, tip-dating, and the fossilized birth-death process; the temporal-signal check (TempEst root-to-tip regression + date-randomization) required before dating viruses or ancient DNA; and clock-model choice via the coefficient of variation. Use when dating nodes, calibrating with fossils or sampling dates, choosing a clock or dating engine, or routing topology to modern-tree-inference, posteriors to bayesian-inference, and rooting to tree-manipulation.
2198. bio-population-genetics-selection-statistics GPTomics/bioSkills · score 65/100 (grade C)
      Scans genomes for natural selection with SFS tests (Tajima's D, Fay & Wu H, Zeng E, SweepFinder2 CLR), haplotype tests (iHS, nSL, XP-EHH, Rsb, H12), and differentiation (FST, PBS) using scikit-allel, selscan, and SweepFinder2. No single statistic separates selection from demography at one locus, so the deliverable is empirical genome-wide outliers plus multiple orthogonal signals, not an absolute cutoff. iHS detects incomplete sweeps and collapses to zero at fixation while XP-EHH catches fixed sweeps; iHS/nSL standardize within derived-allele-frequency bins but XP-EHH gets a genome-wide z-score; derived-allele tests need substitution-model polarization; background selection mimics FST and CLR. Use when computing selection statistics like FST, Tajima's D, iHS, or XP-EHH, or scanning for selective sweeps. For phasing inputs see phasing-imputation/haplotype-phasing; for dN/dS see comparative-genomics/positive-selection.
2199. bio-proteomics-protein-inference GPTomics/bioSkills · score 65/100 (grade C)
      Groups proteins from peptide identifications and controls protein-level FDR, framing inference as a chosen explanation (parsimony or a probability model) of underdetermined peptide evidence rather than a measurement. Reports protein GROUPS (proteins indistinguishable by observed peptides) with a leading protein, not flat lists. Covers shared-vs-unique peptides, indistinguishable/subsumable proteins, parsimony vs probabilistic (ProteinProphet, EPIFANY) vs razor inference, picked-protein and picked-group FDR, and why the two-peptide rule is wrong. Use when resolving which proteins are present from a peptide list, building protein groups, or estimating protein-level FDR. PSM/peptide FDR and search engines are peptide-identification; razor-vs-unique quant consequences are quantification; isoform/proteoform resolution is top-down and out of scope.
2200. bio-ribo-seq-translation-efficiency GPTomics/bioSkills · score 65/100 (grade C)
      Quantify translation efficiency (TE) as ribosome occupancy relative to mRNA abundance and test for differential TE between conditions. Use when separating translational from transcriptional regulation, distinguishing genuine translational control from buffering, or choosing between riborex, Xtail, anota2seq, and DESeq2 interaction models.
2201. bio-rna-structure-structure-probing GPTomics/bioSkills · score 65/100 (grade C)
      Processes experimental RNA structure probing data (SHAPE-MaP, DMS-MaPseq) into per-nucleotide reactivity profiles with ShapeMapper2, then uses them as soft restraints on thermodynamic folding. Covers reagent and readout choice (SHAPE vs DMS, mutational-profiling vs RT-stop), the three control samples, per-transcript normalization, the Deigan vs Zarringhalam pseudo-energy models, in-cell versus in-vitro interpretation, and multi-conformation deconvolution. Use when converting probing reads to reactivities; deciding SHAPE versus DMS parameters; judging whether low reactivity means base-paired or protein-bound; or detecting whether an RNA populates more than one structure.
2202. bio-structural-biology-structure-preparation GPTomics/bioSkills · score 65/100 (grade C)
      Prepares a deposited or predicted structure for docking, molecular dynamics, or electrostatics by adding hydrogens, assigning protonation and tautomer states, and filling missing atoms and short loops with PDBFixer, reduce, PROPKA, and PDB2PQR. Use when adding hydrogens an X-ray model never resolved; assigning His HID/HIE/HIP tautomers, Asn/Gln/His 180-degree flips, and Cys/Lys/Asp/Glu pKa-shifted protonation at a stated pH and microenvironment rather than trusting standard pKa 7; filling missing side-chain atoms and modeling short missing loops as disorder hypotheses; making a receptor docking- or MD-ready and recording what was built; preparing a predicted model after trimming low-pLDDT regions; and writing a PQR for Poisson-Boltzmann electrostatics. Keywords PDBFixer, reduce, PROPKA, PDB2PQR, protonation, tautomer, missing atoms, hydrogens, pKa, docking prep, MD prep.
2203. bio-systems-biology-community-metabolic-modeling GPTomics/bioSkills · score 65/100 (grade C)
      Builds and simulates multi-species metabolic community models from member genome-scale models, using MICOM for abundance-weighted steady-state community FBA and cooperative tradeoff, SMETANA for cross-feeding and competition scoring, and SteadyCom/COMETS for common-growth-rate and dynamic simulation. Use when modeling a microbiome or co-culture, predicting cross-feeding and competition, abundance-weighting members from metagenomics, choosing steady-state vs dynamic community modeling, avoiding the compartment-pooling artifact, or judging how member-model quality and namespace propagate into community predictions.
2204. bio-variant-calling-deepvariant GPTomics/bioSkills · score 65/100 (grade C)
      Calls germline SNPs and indels with Google DeepVariant, which reframes variant calling as CNN image classification over multi-channel pileup tensors. Covers platform-specific model selection (WGS, WES, PACBIO, ONT_R104, HYBRID_PACBIO_ILLUMINA), one-shot run_deepvariant vs the three-stage make_examples/call_variants/postprocess_variants pipeline, GPU acceleration of call_variants, DeepTrio for family/trio and de-novo calling, and joint genotyping of gVCFs with GLnexus (not GenotypeGVCFs). Use when deciding DeepVariant vs GATK vs DRAGEN, picking the right --model_type for a sequencing platform, avoiding post-hoc GATK hard filters or BQSR that degrade CNN calls, calling de-novo variants in a trio, merging a DeepVariant cohort, or weighing GIAB-trained benchmark accuracy before clinical deployment.
2205. bio-workflows-metagenomics-pipeline GPTomics/bioSkills · score 65/100 (grade C)
      End-to-end shotgun metagenomics workflow from FASTQ to taxonomic and functional profiles, orchestrating controls/host depletion, Kraken2+Bracken classification, MetaPhlAn marker profiling, and HUMAnN functional profiling. Covers the controls-first ordering, why Kraken2 read counts are not abundances and MetaPhlAn cell fractions do not equal Bracken read fractions, and the consistent-pipeline framing. Use when profiling shotgun metagenomic samples end to end, or chaining classification, abundance, and function. For resistome see metagenomics/amr-detection; for strains see metagenomics/strain-tracking; for assembly see genome-assembly/metagenome-assembly.
2206. chief-of-staff alirezarezvani/claude-skills · score 65/100 (grade C)
      C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically. Use when a founder question needs routing to the right advisor — e.g. 'should we raise now or cut burn?' — or when a multi-domain decision needs a board meeting convened.
2207. ck affaan-m/ECC · score 65/100 (grade C)
      Persistent per-project memory for Claude Code (Context Keeper) driven by deterministic Node.js /ck commands: init, save, resume, info, list, forget, and v1-to-v2 migrate, plus a SessionStart hook that injects a compact project brief. Use when context must survive across sessions, saving session state with next steps and decisions, resuming where a previous session left off, or picking up a project without re-explaining it.
2208. ck affaan-m/everything-claude-code · score 65/100 (grade C)
      Persistent per-project memory for Claude Code (Context Keeper) driven by deterministic Node.js /ck commands: init, save, resume, info, list, forget, and v1-to-v2 migrate, plus a SessionStart hook that injects a compact project brief. Use when context must survive across sessions, saving session state with next steps and decisions, resuming where a previous session left off, or picking up a project without re-explaining it.
2209. connect-apps ComposioHQ/awesome-claude-skills · score 65/100 (grade C)
      Connect Claude to external apps like Gmail, Slack, GitHub. Use this skill when the user wants to send emails, create issues, post messages, or take actions in external services.
2210. constraint-driven-development addyosmani/agent-skills · score 65/100 (grade C)
      Establishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.
2211. data-scraper-agent affaan-m/ECC · score 65/100 (grade C)
      Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
2212. data-scraper-agent affaan-m/everything-claude-code · score 65/100 (grade C)
      Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
2213. gh-address-comments openai/skills · score 65/100 (grade C)
      Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.
2214. git-guardrails-claude-code mattpocock/skills · score 65/100 (grade C)
      Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.
2215. google-cloud-solution-rag-enterprise-search-gke-sqldb google/skills · score 65/100 (grade C)
      Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.
2216. gpt-review davidondrej/skills · score 65/100 (grade C)
      Launch an independent GPT-6.1-Sol Max code review and return it verbatim. Use only when the user explicitly invokes /gpt-review.
2217. Gumroad Automation ComposioHQ/awesome-claude-skills · score 65/100 (grade C)
      Automate Gumroad product management, sales tracking, license verification, and webhook subscriptions using natural language through the Composio MCP integration.
2218. investor-materials affaan-m/ECC · score 65/100 (grade C)
      Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
2219. investor-materials affaan-m/everything-claude-code · score 65/100 (grade C)
      Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
2220. living-docs-governance affaan-m/ECC · score 65/100 (grade C)
      Keep a long-lived project's documentation from rotting by assigning existing project docs clear constitution, map, status, and history roles, then wiring the active agent harness to those canonical sources. Use in the maintain phase when docs drift from code, agents lose context between sessions, or intentional removals keep being recreated. Prefer adopting the repository's current docs structure over creating new root files. 中文触发：文档治理、活文档、项目状态追踪、防文档漂移、项目地图、健康仪表盘、删除区、长期项目治理
2221. living-docs-governance affaan-m/everything-claude-code · score 65/100 (grade C)
      Keep a long-lived project's documentation from rotting by assigning existing project docs clear constitution, map, status, and history roles, then wiring the active agent harness to those canonical sources. Use in the maintain phase when docs drift from code, agents lose context between sessions, or intentional removals keep being recreated. Prefer adopting the repository's current docs structure over creating new root files. 中文触发：文档治理、活文档、项目状态追踪、防文档漂移、项目地图、健康仪表盘、删除区、长期项目治理
2222. mvvm-toolkit-messenger github/awesome-copilot · score 65/100 (grade C)
      CommunityToolkit.Mvvm Messenger pub/sub for decoupled communication between ViewModels (or any objects). Covers WeakReferenceMessenger vs StrongReferenceMessenger, IRecipient<TMessage>, RequestMessage<T> / AsyncRequestMessage<T> / CollectionRequestMessage<T>, ValueChangedMessage<T>, channels (tokens), and the ObservableRecipient activation lifecycle. Use across WPF, WinUI 3, .NET MAUI, Uno, and Avalonia.
2223. ralphinho-rfc-pipeline affaan-m/ECC · score 65/100 (grade C)
      Split an RFC into a multi-agent execution DAG — decompose into work units with dependencies and acceptance tests, run research, plan, implement, test, and review per unit, then merge through a queue with re-based branches and final system verification. Use when a feature is too large for a single agent pass, orchestrating RFC-driven multi-agent execution, or managing merge queues across agent-built units.
2224. ralphinho-rfc-pipeline affaan-m/everything-claude-code · score 65/100 (grade C)
      Split an RFC into a multi-agent execution DAG — decompose into work units with dependencies and acceptance tests, run research, plan, implement, test, and review per unit, then merge through a queue with re-based branches and final system verification. Use when a feature is too large for a single agent pass, orchestrating RFC-driven multi-agent execution, or managing merge queues across agent-built units.
2225. Replicate Automation ComposioHQ/awesome-claude-skills · score 65/100 (grade C)
      Automate Replicate AI model operations -- run predictions, upload files, inspect model schemas, list versions, and manage prediction history via the Composio MCP integration.
2226. seo-autopilot Illyism/seo-skills · score 65/100 (grade C)
      When the user wants an agent to run SEO for a product end to end on a daily schedule, with state kept in a seo/ folder in the repo. Covers site health checks, fact checks against commits, page 2 to page 1 pushes, AI answer tracking, competitor sitemap diffs, a monthly keyword map, articles, comparison pages, free tools and link drafts. Also use when the user mentions "seo autopilot" or asks for a daily SEO run.
2227. spawn alirezarezvani/claude-skills · score 65/100 (grade C)
      Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.
2228. strict-api alirezarezvani/claude-skills · score 65/100 (grade C)
      Use when the user says 'no hallucinations', 'verify APIs', 'reality check', or 'don't invent functions'. Prevents the agent from calling methods, imports, or variables that do not provably exist in the user's installed version.
2229. structured-autonomy-plan github/awesome-copilot · score 65/100 (grade C)
      Structured Autonomy Planning Prompt
2230. threejs-asset-pipeline cloudai-x/threejs-skills · score 65/100 (grade C)
      Shrinking glTF assets for three.js with gltf-transform: inspect, validate and optimize commands, Draco, meshopt and quantization, KTX2, WebP and AVIF textures, the loader setup each output needs, and gltfjsx for React. Use when compressing, optimizing or validating 3D models before loading them.
2231. tradingview-mcp himself65/finance-skills · score 65/100 (grade C)
      Query TradingView market data through the bundled tradingview MCP server without a desktop app or login. Use whenever the user wants a technical analysis readout (RSI, MACD, Bollinger rating, BUY/SELL summary), multi-timeframe alignment (weekly→daily→4h→1h→15m), exchange-wide scans (Bollinger squeeze, volume breakout, consecutive candles, smart volume), top gainers/losers by exchange, futures market data (NQ/ES/CL/GC overview, overnight movers, category snapshots), pre-market / after-hours quotes, a quick options chain or unusual options activity (volume/OI by strike), bulk stock prices, a global market snapshot, strategy backtests (Sharpe, drawdown, win rate), or crypto exchange scans. Triggers include "TA on X", "multi-timeframe read", "BB squeeze scan", "futures movers", "NQ overnight", "pre-market price", "unusual options activity", "backtest RSI on AAPL", and "top gainers on NASDAQ". For options greeks, watchlists, alerts, or chart screenshots use tradingview-reader instead.
2232. tradingview-reader himself65/finance-skills · score 65/100 (grade C)
      Read the user's local TradingView desktop app through opencli: quotes, options chains with greeks and per-strike IV, options expiries, screener results across stocks, crypto, forex, futures, and bonds, gainers and losers, news headlines and full stories, alerts (active, fired, offline fires), watchlists including colored flag lists, symbol search, chart state, and chart screenshots. Use this skill whenever the user asks for any of these from TradingView ("TV") — for example an options chain, puts, or IV skew for a ticker, an oversold-stock screen, their red flag list, which alerts fired, or a screenshot of their chart. For plain quotes, TA readouts, scans, or futures without the desktop app, prefer tradingview-mcp. Read-only: it never places trades or edits watchlists, alerts, or layouts.
2233. wayfinder mattpocock/skills · score 65/100 (grade C)
      Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
2234. agent-harness-construction affaan-m/ECC · score 64/100 (grade D)
      Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's tool set, action space, or observation format.
2235. agent-harness-construction affaan-m/everything-claude-code · score 64/100 (grade D)
      Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's tool set, action space, or observation format.
2236. attribution coreyhaines31/marketingskills · score 64/100 (grade D)
      When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI and conversion tracking, see conversion-tracking. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.
2237. bio-causal-genomics-genomic-sem GPTomics/bioSkills · score 64/100 (grade D)
      Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with Q_SNP heterogeneity, multivariate Wald tests, and stratified GenomicSEM partitioned heritability. Reconciles results against MTAG multi-trait analysis. Handles sample overlap via the LDSC sampling-covariance matrix, identifies and resolves Heywood cases, and verifies model fit with CFI / RMSEA. Use when modeling latent genetic architecture across correlated traits, running multivariate GWAS on a shared factor, distinguishing factor-mediated from trait-specific SNP effects, or comparing GenomicSEM common-factor results against MTAG when both depend on accurate sampling covariance.
2238. bio-causal-genomics-transcriptome-wide-association GPTomics/bioSkills · score 64/100 (grade D)
      Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2, and probabilistic fine-mapping with FOCUS and MA-FOCUS. Use when running TWAS from GWAS sumstats, prioritising candidate causal genes from a GWAS lead locus, picking single-tissue vs cross-tissue models, identifying LD-induced TWAS false positives, choosing ancestry-matched prediction weights, fine-mapping co-regulated TWAS hits, or triangulating TWAS with cis-eQTL Mendelian randomization and colocalization to nominate a causal gene.
2239. bio-chipseq-peak-calling GPTomics/bioSkills · score 64/100 (grade D)
      Calls ChIP-seq peaks with MACS3, MACS2, HOMER, or SPP across narrow (TF) and broad (histone) modes. Handles input control matching, fragment-size modeling vs --nomodel, effective genome size, ENCODE-style IDR vs naive overlap, hyper-ChIPable artifacts, and aligner-specific shifts. Use when calling peaks from ChIP-seq alignments, choosing between narrow vs broad mode for a histone mark, deciding model vs nomodel for low-depth data, applying ENCODE pseudoreplicate IDR, or reconciling MACS vs HOMER vs SPP results.
2240. bio-clip-seq-clip-deep-learning GPTomics/bioSkills · score 64/100 (grade D)
      Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.
2241. bio-comparative-genomics-whole-genome-duplication GPTomics/bioSkills · score 64/100 (grade D)
      Detect, date, and contextualize whole-genome duplication (WGD / paleopolyploidy) events using wgd v2 (Chen et al 2024), KsRates (Sensalari 2022 substitution-rate-corrected Ks dating), DupGen_finder (Qiao 2019), MAPS (Li 2018 phylogenomic), POInT (Conant 2008 ordered-block), SLEDGe (2024 ML-based), Whale.jl (Bayesian DL+WGD), and synteny-anchored paranome construction. Use when identifying ancient polyploidy from Ks distributions and synteny block analysis, positioning WGD events relative to speciation, distinguishing tandem from segmental from WGD duplications, dating the 2R/3R vertebrate / fish / salmonid WGDs, building paranome and Ks-age mixture models, applying KsRates substitution-rate correction across lineages, or testing alternative biased-fractionation / dosage-balance models post-WGD.
2242. bio-copy-number-gatk-cnv GPTomics/bioSkills · score 64/100 (grade D)
      Call copy number variants with the GATK best-practices workflows — the somatic CNV pipeline (CollectReadCounts, DenoiseReadCounts with tangent normalization, ModelSegments, CallCopyRatioSegments) and the germline GATK-gCNV pipeline (DetermineGermlineContigPloidy, GermlineCNVCaller cohort/case mode, PostprocessGermlineCNVCalls). Covers panel-of-normals construction, AnnotateIntervals/FilterIntervals, allelic-count integration, and QS-based filtering. Use when integrating CNV calling into a GATK variant pipeline, calling rare germline CNVs from an exome cohort, deciding between the somatic and germline GATK workflows, or diagnosing why tangent normalization removed a real event or why gCNV output has low precision.
2243. bio-copy-number-hrd-scoring GPTomics/bioSkills · score 64/100 (grade D)
      Quantify homologous recombination deficiency (HRD) from tumor copy number using the three genomic-scar metrics — loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (TAI) — with scarHRD, and via the whole-genome HRDetect and CHORD models. Covers the genomic instability score, the PARP-inhibitor clinical context, whole-genome-doubling correction, and the scar-versus-state distinction. Use when computing an HRD score for PARP-inhibitor eligibility, deriving LOH/LST/TAI scars from allele-specific copy number, deciding between scar-based and mutational-signature HRD methods, or interpreting an HRD result in a BRCA-reverted or low-purity tumor.
2244. bio-crispr-screens-in-vivo-screens GPTomics/bioSkills · score 64/100 (grade D)
      Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.
2245. bio-genome-annotation-ncrna-annotation GPTomics/bioSkills · score 64/100 (grade D)
      Identifies non-coding RNAs (tRNA, rRNA, snoRNA, snRNA, riboswitches, sRNAs) using Infernal covariance-model search against Rfam, tRNAscan-SE 2.0 for tRNA, barrnap for rRNA, and ARAGORN for tmRNA, plus the small-RNA-seq boundary for miRNA and the transcript-assembly boundary for lncRNA. Covers the structure-conserved-not-sequence-conserved principle (why BLAST fails), GA-threshold and clan-competition correctness, tRNAscan-SE domain modes and pseudogene flags, rDNA copy-number collapse, and why homology annotation is a recall floor. Use when performing genome-wide ncRNA annotation, choosing the right tool for an RNA class, or interpreting ncRNA counts.
2246. bio-genome-annotation-repeat-annotation GPTomics/bioSkills · score 64/100 (grade D)
      Discovers, classifies, and masks repetitive elements and transposable elements with RepeatModeler2 (de novo family library), RepeatMasker (masking against a library), EDTA (plant/structural TEs), or EarlGrey (auto-curating wrapper), and quantifies TE expression from RNA-seq with TEtranscripts/SQuIRE. Covers de-novo-library-as-curation-project, soft-vs-hard masking, the domesticated-gene over-masking massacre, Dfam-vs-RepBase, TE classification (Class I/II, family-vs-copy), Kimura repeat landscapes, LAI, and the RNA-seq multimapping problem. Use when masking repeats before gene prediction, building a TE library for a non-model genome, or analyzing transposable-element content or expression.
2247. bio-genome-intervals-overlap-significance GPTomics/bioSkills · score 64/100 (grade D)
      Tests whether two genomic interval sets overlap (colocalize) more than expected by chance using a permutation test against a structured-genome null model. Covers bedtools fisher (analytic 2x2 screen), bedtools shuffle + jaccard permutation, GAT (isochore/GC-conditioned simulation with FDR), regioneR (flexible permutation, randomizeRegions vs circularRandomizeRegions, localZScore), LOLA (universe-relative Fisher against a region database), and GREAT/rGREAT (regulatory-domain binomial + hypergeometric for ontology-from-regions). Stresses the universe/background choice, matched background, blacklist exclusion, and multiple-testing control. Use when asking whether peaks/regions are enriched at enhancers/TFBS/features, scoring region-set colocalization or region-set enrichment, comparing CNV/SV concordance, or turning an overlap count into a defensible p-value.
2248. bio-long-read-sequencing-clair3-variants GPTomics/bioSkills · score 64/100 (grade D)
      Calls germline small variants (SNPs and indels) from Oxford Nanopore and PacBio HiFi long reads with Clair3, a two-stage (pileup + full-alignment) deep-learning caller, selecting the chemistry- and basecaller-version-matched model, enabling read-based phasing, and benchmarking against GIAB with stratification. Covers why the model string is the experiment (no auto-detection, silent degradation on mismatch), why ONT homopolymer/STR indels are the residual error whole-genome F1 hides, and the somatic/trio/RNA boundary to the ClairS/Clair3-Trio family. Use when calling germline SNVs/indels from ONT or HiFi BAMs, choosing a Clair3 model, phasing variants, or benchmarking long-read calls.
2249. bio-machine-learning-survival-analysis GPTomics/bioSkills · score 64/100 (grade D)
      Builds and validates predictive time-to-event models on clinical and omics data with penalized Cox, random survival forests, gradient-boosted and deep survival models, and prediction-grade evaluation (Uno's C, time-dependent AUC, integrated Brier, calibration, competing risks). Use when building an individualized risk predictor or prognostic omics signature, choosing a survival model, or evaluating one beyond the C-index. For Kaplan-Meier, log-rank, and classical Cox hazard-ratio inference in a trial see clinical-biostatistics/survival-analysis.
2250. bio-metabolomics-normalization-qc GPTomics/bioSkills · score 64/100 (grade D)
      Designs QC, corrects signal drift, removes batch effects, filters features, normalizes samples, and imputes missing values for untargeted LC-MS/GC-MS metabolomics, framing each step as a measurement model that can create or erase biological signal. Use when processing a peak/feature table before statistical analysis, choosing a drift-correction or sample-normalization method, deciding QC RSD vs D-ratio filtering, or handling left-censored missing values. The feature table is produced by metabolomics/xcms-preprocessing or metabolomics/msdial-preprocessing; transformation/scaling for modeling defers to metabolomics/statistical-analysis; cross-study design issues link to experimental-design/batch-design.
2251. bio-methylation-dmr-detection GPTomics/bioSkills · score 64/100 (grade D)
      Detects differentially methylated regions (DMRs) from short-read bisulfite (WGBS/RRBS), array, and long-read methylation count tables using dmrseq (permutation region-FDR over the region selection), DSS callDMR (beta-binomial), methylKit tiles, bsseq BSmooth, DMRcate Gaussian-kernel smoothing, metilene, and comb-p. Covers why a DMR is DEFINED by arbitrary thresholds (min-CpGs, max-gap, delta-beta, q) and a smoothing bandwidth, why selecting extreme runs of CpGs then testing them on the same data is post-selection inference, why region q-values are not comparable across tools, and a single-sample domain-segmentation section (PMD, UMR/LMR, MethylSeekR, solo-WCGW) that must run before focal calling on cancer/aging genomes. Use when calling region-level methylation differences, choosing a DMR caller, controlling region-level FDR, or segmenting megabase methylation domains. For per-site testing see differential-cpg-testing; for the methylKit object model see methylkit-analysis.
2252. bio-methylation-epigenetic-clocks GPTomics/bioSkills · score 64/100 (grade D)
      Computes DNA methylation age (DNAm age) and pace of aging by applying frozen elastic-net epigenetic clocks to a clean beta matrix with methylclock, dnaMethyAge, or methylCIPHER. Covers the clock menu by question (chronological Horvath/Hannum/skin&blood; health-mortality PhenoAge/GrimAge; DunedinPACE pace; pediatric/gestational; mitotic epiTOC), age acceleration (EAA/IEAA/EEAA) as the real endpoint, the principal-component (PC) clock fix for the per-CpG reliability crisis, and EPICv2 clock-CpG dropout with missing-CpG imputation bias. Use when estimating epigenetic age, computing age acceleration, choosing a clock for an outcome, assessing clock reliability, or porting a clock to EPICv2. A clock is a frozen predictor: do not GO-enrich its CpGs and do not train it here. For cell-count adjustment (IEAA) see cell-type-deconvolution; for predictor training/validation/leakage see machine-learning/model-validation; for survival modeling of age acceleration see clinical-biostatistics/survival-analysis.
2253. bio-rna-structure-ncrna-search GPTomics/bioSkills · score 64/100 (grade D)
      Searches for non-coding RNA homologs and classifies RNA families with Infernal covariance models against Rfam, scoring sequence AND secondary-structure conservation jointly. Use when deciding whether a covariance model is the right tool versus BLAST/nhmmer (structured ncRNA versus lncRNA or mature miRNA); choosing the Rfam gathering threshold over a flat E-value; resolving clan overlaps; building and calibrating a custom CM from a structure-annotated alignment; or preferring a family-specialized tool (tRNAscan-SE, barrnap) over a generic Rfam scan.
2254. bio-structural-biology-binding-site-detection GPTomics/bioSkills · score 64/100 (grade D)
      Detects putative ligand-binding pockets and druggable cavities de novo on an apo protein structure with fpocket, P2Rank, CASTp, and DoGSiteScorer, ranking them by druggability/ligandability score. Use when detecting cavities on an apo structure with no bound ligand; choosing geometric pocket enumeration (fpocket alpha-spheres, CASTp) vs ML ligandability scoring (P2Rank, DoGSiteScorer); recognizing that a geometric cavity is a hypothesis, not automatically a functional or druggable site (may be a crystal-additive or non-functional cleft); knowing druggability scores were trained on holo sets and under-detect apo, shallow, and cryptic pockets; detecting cryptic or transient pockets over an MD or conformational ensemble (mdpocket); and detecting on a predicted model whose pocket-lining rotamers are the least reliable atoms. Keywords binding site, pocket, cavity, druggability, ligandability, fpocket, P2Rank, CASTp, DoGSiteScorer, apo, cryptic pocket, alpha sphere, mdpocket.
2255. bio-workflows-merip-pipeline GPTomics/bioSkills · score 64/100 (grade D)
      Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation curves, exomePeak2 (transcript-aware, GC-bias-aware negative-binomial GLM) peak calling, optional MACS3 broad-peak cross-check, DRACH motif confirmation as a sanity check (NOT a per-peak filter), exomePeak2 differential calling via the four-BAM-vector interface (bam_ip + bam_input control; bam_treated_ip + bam_treated_input treatment), ChIPseeker annotation, and the canonical Guitar metagene with stop-codon enrichment as the biological QC anchor. Use when running a complete MeRIP analysis from raw reads, when chaining the constituent epitranscriptomics skills (merip-preprocessing -> m6a-peak-calling -> m6a-differential -> modification-visualization), or when wrapping the pipeline in Snakemake / Nextflow.
2256. boardroom alirezarezvani/claude-skills · score 64/100 (grade D)
      /c-level-agents:boardroom [brief] — 6-phase multi-role deliberation across the C-suite with Phase 2 isolation, critic pre-screen, and synthesis. Outputs a board memo. Use when a decision spans multiple executive domains — e.g. a pricing change touching finance, positioning, and product, or a raise-vs-cut runway call.
2257. cs-webinar-marketer alirezarezvani/claude-skills · score 64/100 (grade D)
      Webinar & virtual-event marketing specialist agent. Use when planning, promoting, running, or rescuing a webinar, virtual event, live demo, workshop, masterclass, fireside chat, or virtual summit. Orchestrates the webinar-marketing skill — sizes the funnel backward from the business goal, builds the promotion runway, designs the show-up and live-to-close sequences, scores an existing funnel to find the broken stage, and plans evergreen/on-demand automation. Treats a webinar as a funnel, not an event. Voice — outcome-obsessed demand operator; refuses to celebrate registrations when nobody shows up or buys; fixes the stage that's actually broken instead of rewriting the landing page by reflex.
2258. demo-video alirezarezvani/claude-skills · score 64/100 (grade D)
      Use when the user asks to create a demo video, product walkthrough, feature showcase, animated presentation, marketing video, or GIF from screenshots or scene descriptions. Orchestrates playwright, ffmpeg, and edge-tts MCPs to produce polished video content.
2259. documentation-lookup affaan-m/ECC · score 64/100 (grade D)
      Use up-to-date library and framework docs via Context7 MCP instead of training data. Activates for setup questions, API references, code examples, or when the user names a framework (e.g. React, Next.js, Prisma).
2260. documentation-lookup affaan-m/everything-claude-code · score 64/100 (grade D)
      Use up-to-date library and framework docs via Context7 MCP instead of training data. Activates for setup questions, API references, code examples, or when the user names a framework (e.g. React, Next.js, Prisma).
2261. eval alirezarezvani/claude-skills · score 64/100 (grade D)
      Evaluate and rank agent results by metric or LLM judge for an AgentHub session. Use when the user runs /hub:eval or asks to score, compare, or pick a winner among completed AgentHub agents.
2262. fintel-data himself65/finance-skills · score 64/100 (grade D)
      Query Fintel (fintel.io) institutional market data through its REST API or official MCP server. Use this skill whenever the user mentions Fintel or asks about short interest, short interest ratio or days to cover, short squeeze data, borrow rate or cost to borrow, shares available to borrow, daily short volume, fails-to-deliver (FTD), 13F institutional owners ("who owns X"), insider buying or selling from SEC Form 3/4/5, analyst price targets, ratings and forecasts, dividend or earnings history and calendars, EOD or last prices, security lookup by ticker, CUSIP, ISIN, or FIGI, Fintel leaderboards, or their Fintel watchlists and alerts. Read-only: GET endpoints only.
2263. folder-structure-blueprint-generator github/awesome-copilot · score 64/100 (grade D)
      Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
2264. freecad-scripts github/awesome-copilot · score 64/100 (grade D)
      Expert skill for writing FreeCAD Python scripts, macros, and automation. Use when asked to create FreeCAD models, parametric objects, Part/Mesh/Sketcher scripts, workbench tools, GUI dialogs with PySide, Coin3D scenegraph manipulation, or any FreeCAD Python API task. Covers FreeCAD scripting basics, geometry creation, FeaturePython objects, interface tools, and macro development.
2265. gke-productionize google/skills · score 64/100 (grade D)
      Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-workload-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead).
2266. gsap-framer-scroll-animation github/awesome-copilot · score 64/100 (grade D)
      Use this skill whenever the user wants to build scroll animations, scroll effects, parallax, scroll-triggered reveals, pinned sections, horizontal scroll, text animations, or any motion tied to scroll position — in vanilla JS, React, or Next.js. Covers GSAP ScrollTrigger (pinning, scrubbing, snapping, timelines, horizontal scroll, ScrollSmoother, matchMedia) and Framer Motion / Motion v12 (useScroll, useTransform, useSpring, whileInView, variants). Use this skill even if the user just says "animate on scroll", "fade in as I scroll", "make it scroll like Apple", "parallax effect", "sticky section", "scroll progress bar", or "entrance animation". Also triggers for Copilot prompt patterns for GSAP or Framer Motion code generation. Pairs with the premium-frontend-ui skill for creative philosophy and design-level polish.
2267. handoff alirezarezvani/claude-skills · score 64/100 (grade D)
      Compact the current conversation into a handoff document for another agent to pick up. References existing artifacts (PRDs, plans, ADRs, issues, commits, diffs) by path or URL instead of duplicating them. Use when user wants to hand off the conversation to a fresh agent or starts a new session that picks up prior work.
2268. image-prompt davidondrej/skills · score 64/100 (grade D)
      Write four distinct prompts for AI image models. Use for image, thumbnail, banner, logo, or illustration prompts. Produces prompt text only.
2269. knowledge-ops affaan-m/ECC · score 64/100 (grade D)
      Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.
2270. knowledge-ops affaan-m/everything-claude-code · score 64/100 (grade D)
      Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.
2271. merge alirezarezvani/claude-skills · score 64/100 (grade D)
      Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning AgentHub result and tidy the session.
2272. orch-add-feature affaan-m/ECC · score 64/100 (grade D)
      Orchestrate building a brand-new feature end to end — research, plan, TDD implementation, review, and gated commit — by delegating each phase to the matching ECC agent. Use when adding a capability that does not exist yet.
2273. orch-add-feature affaan-m/everything-claude-code · score 64/100 (grade D)
      Orchestrate building a brand-new feature end to end — research, plan, TDD implementation, review, and gated commit — by delegating each phase to the matching ECC agent. Use when adding a capability that does not exist yet.
2274. orch-change-feature affaan-m/ECC · score 64/100 (grade D)
      Orchestrate altering an existing, working feature to new desired behavior — update its tests to the new spec, change the implementation to match, review, and gated commit. Use when behavior is not broken but should be different.
2275. orch-change-feature affaan-m/everything-claude-code · score 64/100 (grade D)
      Orchestrate altering an existing, working feature to new desired behavior — update its tests to the new spec, change the implementation to match, review, and gated commit. Use when behavior is not broken but should be different.
2276. orch-fix-defect affaan-m/ECC · score 64/100 (grade D)
      Orchestrate fixing a bug — reproduce it as a failing regression test, fix to green, review, and gated commit — by delegating each phase to the matching ECC agent. Use when existing behavior is broken or wrong.
2277. orch-fix-defect affaan-m/everything-claude-code · score 64/100 (grade D)
      Orchestrate fixing a bug — reproduce it as a failing regression test, fix to green, review, and gated commit — by delegating each phase to the matching ECC agent. Use when existing behavior is broken or wrong.
2278. readme-blueprint-generator github/awesome-copilot · score 64/100 (grade D)
      Intelligent README.md generation prompt that analyzes project documentation structure and creates comprehensive repository documentation. Scans .github/copilot directory files and copilot-instructions.md to extract project information, technology stack, architecture, development workflow, coding standards, and testing approaches while generating well-structured markdown documentation with proper formatting, cross-references, and developer-focused content.
2279. threejs-loaders cloudai-x/threejs-skills · score 64/100 (grade D)
      Loading three.js assets: glTF with Draco, meshopt and KTX2 compression, other model formats, textures, HDR and EXR environments, progress, caching, cloning and disposal. Use when loading 3D models, textures or environment maps, or managing loading progress, on WebGL or with WebGPU and TSL.
2280. agent-governance github/awesome-copilot · score 63/100 (grade D)
      Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
2281. ai-seo coreyhaines31/marketingskills · score 63/100 (grade D)
      When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'llms-full.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' 'agent-readable site,' 'agent readiness,' 'is my site agent-ready,' 'WebMCP,' 'do listicles still work for AI,' 'ChatGPT stopped citing comparison pages,' 'how do LLMs see our brand,' 'LinkedIn for AEO,' or 'AI citation format shift.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.
2282. bio-crispr-screens-copy-number-correction GPTomics/bioSkills · score 63/100 (grade D)
      Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.
2283. bio-differential-expression-timeseries-de GPTomics/bioSkills · score 63/100 (grade D)
      Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.
2284. bio-ecological-genomics-community-ecology GPTomics/bioSkills · score 63/100 (grade D)
      Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.
2285. bio-ecological-genomics-edna-metabarcoding GPTomics/bioSkills · score 63/100 (grade D)
      Processes eDNA metabarcoding from raw paired-end reads to species tables, navigating ASV (DADA2, UNOISE3) vs OTU (swarm v2) decision (Callahan 2017 vs Schloss multi-copy-16S critique), marker/primer choice (Leray COI, MiFish 12S, 515F/806R 16S, ITS2) with primer-specific bias, OBITools3 v3 command-name break (obi stats plural; .tar.gz taxonomy), tag-jumping with dual-indexing (Schnell 2015; NovaSeq 10x MiSeq), decontam as screening-not-classifier (Davis 2018), read-counts-not-abundance critique (Lamb 2019), site-occupancy modeling (Ficetola 2015), Naive-Bayes calibration limits (Bokulich 2018), and eDNA decay (Strickler 2015). Use when going from raw eDNA FASTQ to species tables, picking marker + denoising pipeline, deciding whether read counts represent abundance, applying occupancy modeling, configuring OBITools3 v3, or interpreting decontam output. Not for clinical 16S microbiome (see microbiome/amplicon-processing).
2286. bio-experimental-design-batch-design GPTomics/bioSkills · score 63/100 (grade D)
      Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.
2287. bio-gene-regulatory-networks-coexpression-networks GPTomics/bioSkills · score 63/100 (grade D)
      Build weighted gene co-expression networks to identify modules of co-regulated genes, relate them to phenotypes, and find hub genes using WGCNA, hdWGCNA, MEGENA, CEMiTool, and Gaussian graphical models. Covers signed-network choice, soft-threshold selection, module preservation, and the marginal-vs-partial-correlation distinction. Use when finding co-expression modules, identifying hub genes, relating gene networks to clinical or experimental traits, or building single-cell co-expression networks. For directed TF-target inference see scenic-regulons and grn-inference; for condition rewiring see differential-networks.
2288. bio-phasing-imputation-genotype-imputation GPTomics/bioSkills · score 63/100 (grade D)
      Imputes untyped genotypes against a phased reference panel with Beagle, Minimac4, or IMPUTE5 (array data) or from genotype likelihoods with GLIMPSE2, QUILT2, or STITCH (low-coverage WGS), producing per-variant dosages (DS) with a self-estimated quality (Beagle DR2, Minimac R2, IMPUTE INFO). Covers why the honest output is a dosage posterior not a hard call, why GWAS regresses on DS, why the quality metric is an ESTIMATE of r2 from posterior spread (not validation against truth), the DS/GP/HDS fields, the phasing prerequisite, chunking, chrX ploidy, the Michigan/TOPMed servers (the only access to HRC/TOPMed), and low-coverage WGS as the modern array replacement. Use when increasing variant density for GWAS, harmonizing arrays, inferring untyped variants, or imputing low-coverage sequence. Phase first with haplotype-phasing; prepare the panel with reference-panels; filter with imputation-qc; the GWAS test is population-genetics/association-testing; end-to-end orchestration is workflows/gwas-pipeline.
2289. bio-phylo-modern-tree-inference GPTomics/bioSkills · score 63/100 (grade D)
      Infers maximum-likelihood phylogenetic trees with IQ-TREE2 and RAxML-NG -- model selection (ModelFinder), branch support (UFBoot2, SH-aLRT), concordance factors (gCF/sCF), partitioning, topology tests, and long-branch-attraction control. Covers why an ML tree inherits every flaw of the assumed model and the fixed alignment, why reported support measures repeatability under resampling and not correctness, why UFBoot uses a >=95 cutoff and not the bootstrap-70 rule, and why a node with UFBoot 100 but gCF ~35 is essentially unresolved ILS rather than a clade. Use when inferring an ML tree, selecting a substitution or partition model, choosing or interpreting support measures, testing an a-priori topology, or diagnosing LBA. Routes model-free distance trees to distance-calculations, posteriors to bayesian-inference, and species trees under ILS to species-trees.
2290. bio-population-genetics-association-testing GPTomics/bioSkills · score 63/100 (grade D)
      Single-variant common-variant GWAS with plink2 --glm (linear/logistic, Firth) and the linear mixed models GEMMA, BOLT-LMM, SAIGE, regenie (SPA). A GWAS statistic is valid only when genotype is independent of unmodeled phenotype drivers after the chosen covariates and random effects, so the engine follows sample structure and case:control imbalance, not taste: PC covariates absorb continuous ancestry but cannot remove relatedness (a covariance structure needing an LMM), genomic inflation above 1 is mostly true polygenic signal not confounding (the LDSC intercept is the diagnostic), LOCO prevents proximal contamination, and SPA/Firth keep the tail calibrated at extreme imbalance and low MAC. Use when running single-variant GWAS, choosing between a GLM and a mixed model, or controlling stratification, relatedness, and case:control imbalance. For rare-variant aggregation (burden, SKAT, SKAT-O, ACAT) see rare-variant-association; fine-mapping and MR see causal-genomics; PRS see clinical-databases/polygenic-risk.
2291. bio-systems-biology-gene-essentiality GPTomics/bioSkills · score 63/100 (grade D)
      Performs in-silico single and double gene deletions, condition-dependent essentiality, and synthetic-lethality screens on genome-scale metabolic models with COBRApy, evaluating gene-protein-reaction rules and comparing FBA re-optimization against MOMA/ROOM minimal-adjustment. Use when predicting essential genes, finding synthetic-lethal pairs for drug targets, choosing a growth cutoff, deciding FBA vs MOMA vs ROOM for a knockout, making essentiality medium-specific to match an experiment, or validating predictions against Keio/Tn-seq/CRISPR screens with MCC.
2292. bio-workflows-metabolomics-pipeline GPTomics/bioSkills · score 63/100 (grade D)
      Orchestrates the untargeted LC-MS metabolomics pipeline end-to-end (xcms 4.x feature extraction, QC/drift/normalization, confidence-stratified annotation, permutation-validated statistics, background-aware pathway mapping), naming what each stage decides and where it silently fails. Use when running a full LC-MS metabolomics study from raw mzML to enriched pathways and needing the honest handoffs between stages. Each stage defers to its component skill for parameters and traps; for stable-isotope flux (a separate branch, not this untargeted flow) see metabolomics/isotope-tracing.
2293. bio-workflows-proteomics-pipeline GPTomics/bioSkills · score 63/100 (grade D)
      Orchestrates bottom-up proteomics from a search engine's output (MaxQuant/FragPipe/DIA-NN) to differential protein abundance with limma/DEqMS/MSstats. Use when committing the search database + acquisition mode (DDA vs DIA) up front, re-controlling FDR at PSM AND peptide AND protein-group level (not just PSM), removing contaminant/reverse rows and inspecting RAW distributions before normalizing, bridging cross-plex TMT with an IRS reference channel, modeling MNAR missingness rather than downshift-imputing on/off proteins, batching as a covariate (not pre-subtracted), and testing with treat()/DEqMS. Hands mechanism to the proteomics component skills; not a re-teach of any single step.
2294. bio-workflows-smrna-pipeline GPTomics/bioSkills · score 63/100 (grade D)
      Orchestrates the end-to-end small RNA-seq pipeline from FASTQ to differential miRNAs and expression-filtered targets, chaining kit-aware cutadapt trimming (adapter on every read, UMI/4N handling), miRge3 known+isomiR quantification or miRDeep2 novel discovery, compositionally-aware DESeq2, and miRanda target prediction. Use when committing the library-kit adapter/UMI handling once, choosing the NORMALIZER (which drives which miRNAs are called DE more than the DE model does), deciding known quantification vs novel discovery, handling biofluid/plasma libraries that lack a trustworthy endogenous normalizer, routing tRF/piRNA reads to their own profiling, or feeding RAW (not RPM) counts with size-factor inspection into DE. Hands mechanism to the small-rna-seq component skills; not a re-teach of any single step.
2295. ciso-review alirezarezvani/claude-skills · score 63/100 (grade D)
      /c-level-agents:ciso-review [plan] — Risk-paranoid interrogation of any plan that touches data, compliance, or production access. Use when launching features that handle customer data, before a SOC 2 / ISO audit, or after any incident or near-miss.
2296. code-review mattpocock/skills · score 63/100 (grade D)
      Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to \"review since X\".
2297. connect ComposioHQ/awesome-claude-skills · score 63/100 (grade D)
      Connect Claude to any app. Send emails, create issues, post messages, update databases - take real actions across Gmail, Slack, GitHub, Notion, and 1000+ services.
2298. execute alirezarezvani/claude-skills · score 63/100 (grade D)
      /c-level-agents:execute [decision] — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision. Use when a logged decision needs to become an operating plan — e.g. turning an approved market-entry call into weekly milestones with DRIs.
2299. finalize-agent-prompt github/awesome-copilot · score 63/100 (grade D)
      Finalize prompt file using the role of an AI agent to polish the prompt for the end user.
2300. generative-ui himself65/finance-skills · score 63/100 (grade D)
      Design system and templates for interactive HTML/SVG visuals in Claude and Codex, using an available inline renderer or a standalone HTML file. Use this skill whenever the user wants visual or interactive output rather than plain text or markdown: charts and dashboards, diagrams, flowcharts and architecture drawings, mockups, comparison grids, illustrations, interactive explainers ("explain how X works" with a visual), or tools with sliders, toggles, and live-updating displays — including financial data shown visually and requests phrased as "show me", "visualize", "draw", or "chart this".
2301. marketing-campaign affaan-m/ECC · score 63/100 (grade D)
      End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.
2302. marketing-campaign affaan-m/everything-claude-code · score 63/100 (grade D)
      End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.
2303. obsidian-project-kb-core Galaxy-Dawn/claude-scholar · score 63/100 (grade D)
      Use this as the main Claude Scholar skill for a vault-first, project-scoped Obsidian research knowledge base rooted at Research/{project-slug}/. It owns bootstrap, routing, daily logging, hub/plan/index maintenance, registry updates, lifecycle actions, and lint orchestration.
2304. paywalls coreyhaines31/marketingskills · score 63/100 (grade D)
      When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," "in-app pricing," "free users won't upgrade," "trial to paid conversion," or "how do I get users to pay." Use this for any in-product moment where you're asking users to upgrade. Distinct from public pricing pages (see cro) — this focuses on in-product upgrade moments where the user has already experienced value. For pricing decisions, see pricing.
2305. playwright-generate-test github/awesome-copilot · score 63/100 (grade D)
      Generate a Playwright test based on a scenario using Playwright MCP
2306. safety-guard affaan-m/ECC · score 63/100 (grade D)
      Guard against destructive operations with three modes: Careful intercepts dangerous commands (rm -rf, git push --force, DROP TABLE) for confirmation, Freeze locks writes to one directory, and Guard combines both. Advisory: the agent applies these rules itself; no hook ships with it. Use when working on production systems, running agents autonomously, restricting edits to a directory, or during migrations, deploys, and data changes.
2307. safety-guard affaan-m/everything-claude-code · score 63/100 (grade D)
      Guard against destructive operations with three modes: Careful intercepts dangerous commands (rm -rf, git push --force, DROP TABLE) for confirmation, Freeze locks writes to one directory, and Guard combines both. Advisory: the agent applies these rules itself; no hook ships with it. Use when working on production systems, running agents autonomously, restricting edits to a directory, or during migrations, deploys, and data changes.
2308. security-guidance alirezarezvani/claude-skills · score 63/100 (grade D)
      PreToolUse security-anti-pattern hook for Claude Code. Catches 12 common security risks (command injection, XSS, SQL injection, unsafe deserialization, GitHub Actions workflow injection, eval/new Function code injection) BEFORE the Edit/Write/MultiEdit operation completes. Session-state caching prevents duplicate warnings on the same file+rule combo. Stdlib only — no dependencies. Use when you want a safety net during Claude Code sessions that touch security-sensitive code (auth, payments, user input handling, IaC). Disable with ENABLE_SECURITY_REMINDER=0 if you need to perform a verified-safe operation that would otherwise trip a pattern. Triggers — "add security hook", "block unsafe code", "detect command injection before write", "prevent SQL injection patterns", "security warning hook".
2309. signal-write github/awesome-copilot · score 63/100 (grade D)
      Emit structured agent signals — hands-up, blocked, done, checkpoint, partnership. Signals are written as JSON to .signals/ for dashboard consumption and noted in the journal for persistence.
2310. threat-model-analyst github/awesome-copilot · score 63/100 (grade D)
      Full STRIDE-A threat model analysis and incremental update skill for repositories and systems. Supports two modes: (1) Single analysis — full STRIDE-A threat model of a repository, producing architecture overviews, DFD diagrams, STRIDE-A analysis, prioritized findings, and executive assessments. (2) Incremental analysis — takes a previous threat model report as baseline, compares the codebase at the latest (or a given commit), and produces an updated report with change tracking (new, resolved, still-present threats), STRIDE heatmap, findings diff, and an embedded HTML comparison. Only activate when the user explicitly requests a threat model analysis, incremental update, or invokes /threat-model-analyst directly.
2311. write-swift emilkowalski/skills · score 63/100 (grade D)
      How to write modern Swift well — modeling with value types, Swift 6 data-race safety and approachable concurrency (@concurrent, main-actor-by-default, actors, task groups), protocols and generics (some vs any), API design, performance and ARC, Swift Testing, macros, and the modern language features agents don't know about yet. Use when writing, reviewing, or migrating Swift, or when a concurrency error, a hang, a data race, a retain cycle, or a performance problem needs fixing.
2312. ai-ready github/awesome-copilot · score 62/100 (grade D)
      Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".
2313. animation-vocabulary emilkowalski/skills · score 62/100 (grade D)
      Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
2314. bio-clinical-biostatistics-logistic-regression GPTomics/bioSkills · score 62/100 (grade D)
      Performs logistic regression for clinical trial outcomes (binary, ordinal, multinomial) with marginal-vs-conditional estimand reporting per FDA 2023 covariate adjustment guidance, g-computation/standardisation for marginal effects, modified Poisson for RR, Brant test for proportional odds, Firth penalty for separation, and Hauck-Donner detection. Use when modeling binary or ordinal endpoints in confirmatory or exploratory clinical trials.
2315. bio-comparative-genomics-gene-family-evolution GPTomics/bioSkills · score 62/100 (grade D)
      Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.
2316. bio-ecological-genomics-species-delimitation GPTomics/bioSkills · score 62/100 (grade D)
      Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.
2317. bio-genome-assembly-assembly-polishing GPTomics/bioSkills · score 62/100 (grade D)
      Decides whether and how to polish a draft genome assembly to raise consensus accuracy (QV) with read-type-matched tools - Racon and medaka (ONT consensus), dorado polish, Polypolish and pypolca (Illumina, repeat-aware), Pilon (legacy short-read), NextPolish/NextPolish2, Hapo-G (haplotype-aware), ntEdit, and DeepPolisher/PEPPER-Margin-DeepVariant for human. Covers the do-not-polish-HiFi rule, the medaka basecaller-model footgun, held-out Merqury QV as the only honest stop signal, and the haplotype-collapse trap. Use when correcting homopolymer indels or residual SNPs in a long-read assembly, deciding if a HiFi assembly needs polishing, or choosing an ONT vs hybrid vs short-read polishing chain.
2318. bio-genome-engineering-off-target-prediction GPTomics/bioSkills · score 62/100 (grade D)
      Nominates and assesses CRISPR off-target sites genome-wide. Enumerates candidate sites by mismatch and bulge tolerance with Cas-OFFinder/CRISPRitz, ranks them with the published CFD score (SpCas9-only, relative ranker) or MIT/CRISTA/energy models, runs variant-aware screening against gnomAD/individual genomes (CRISPRme), and frames the empirical genome-wide discovery assays (GUIDE-seq, CIRCLE-seq, CHANGE-seq, DISCOVER-seq, Digenome-seq) and high-fidelity nuclease choice (HiFi Cas9, Sniper-Cas9, eSpCas9, SpCas9-HF1). Use when assessing guide RNA specificity, choosing among candidate guides, screening a therapeutic guide against population variation, or planning empirical off-target validation. Distinguishes predicted vs detected vs validated. On-target activity scoring and deaminase (Cas-independent) base/prime-editor off-targets are separate skills.
2319. bio-long-read-sequencing-medaka-polishing GPTomics/bioSkills · score 62/100 (grade D)
      Polishes Oxford Nanopore draft assemblies to higher consensus accuracy with medaka, a basecaller-model-specific neural consensus net, produces haploid variant calls (VCF) for microbial, mitochondrial, or viral samples, and generates amplicon/viral consensus sequences. Covers the model-matching footgun that silently degrades output, why Racon-first is obsolete and medaka runs directly on Flye output as a single pass, why HiFi must never be fed to medaka, the v1->v2 subcommand renames, and the precise medaka_variant deprecation. Use when polishing an ONT-only assembly, generating an amplicon/viral consensus, calling a haploid ONT consensus, or deciding whether medaka, dorado polish, or Clair3 is the right tool.
2320. bio-temporal-genomics-differential-rhythmicity GPTomics/bioSkills · score 62/100 (grade D)
      Compares how a rhythm CHANGES between conditions, genotypes, treatments, tissues, or ages (differential rhythmicity), classifying each feature as gain-of-rhythm, loss-of-rhythm, phase change, amplitude change, unchanged-rhythmic, or arrhythmic-in-both, and distinguishing differential EXPRESSION (condition main effect) from differential RHYTHMICITY (condition x time interaction). Uses model-based approaches that borrow strength across conditions - LimoRhyde (sin/cos interaction terms in a limma/edgeR/DESeq2 design), dryR (BIC model selection across >=2 conditions), compareRhythms (direct gain/loss/change/same classification), DODR, CircaCompare - instead of the detect-then-Venn anti-pattern that overestimates reprogramming. Use when testing whether rhythms differ between conditions/genotypes/tissues/ages, classifying gain/loss/phase/amplitude change, or separating differential expression from differential rhythmicity. Not for detecting rhythms in one condition (see temporal-genomics/circadian-rhythms).
2321. bio-temporal-genomics-temporal-grn GPTomics/bioSkills · score 62/100 (grade D)
      Infers directed, time-delayed gene regulatory edges from BULK time-series expression using Granger causality (statsmodels VAR F-test), dynGENIE3 (tree ensembles regressing ODE-derived derivatives; Random Forests by default, Extra-Trees optional), and dynamic Bayesian networks (bnlearn). Use when the output is a RANKED HYPOTHESIS list for perturbation validation, not validated causal edges; deciding Granger vs dynGENIE3 vs DBN by timepoint count and linearity; sizing maxlag against the n>3*maxlag+1 degrees-of-freedom floor; handling stationarity/differencing before Granger; restricting regulators to known TFs; and comparing network rewiring across conditions at matched edge density. Not for single-cell pseudotime GRNs (see gene-regulatory-networks/scenic-regulons) or static co-expression (see gene-regulatory-networks/coexpression-networks).
2322. brand-guidelines ComposioHQ/awesome-claude-skills · score 62/100 (grade D)
      Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
2323. brand-guidelines anthropics/skills · score 62/100 (grade D)
      Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
2324. caveman-learn JuliusBrussee/caveman · score 62/100 (grade D)
      Act on a Caveman learn report - review the ranked token sinks, apply cost-lowering fixes with per-edit consent, and report what those fixes returned. Use when asked to lower an agent's token cost, what caveman has saved, to trim a heavy CLAUDE.md, or to offload re-pasted context into cavemem.
2325. cs-frontend-engineer alirezarezvani/claude-skills · score 62/100 (grade D)
      Frontend-engineering orchestrator. Walks the 7 Matt Pocock forcing questions (device, LCP target, rendering, bundle budget, SEO vs auth, design system, WCAG), picks the framework/rendering profile, forks into specialists (a11y-audit, apple-hig-expert, epic-design, performance-profiler, playwright-pro — listed alphabetically; workflow order is dependency-driven) rather than reimplementing their scope. Forks own context. Invoke via /cs-frontend-review or Agent({subagent_type:"cs-frontend-engineer",...}).
2326. cs-wiki-linter alirezarezvani/claude-skills · score 62/100 (grade D)
      Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages, missing frontmatter, duplicate titles, log gaps), does semantic checks (contradictions, stale claims, cross-reference gaps, concepts missing their own page), and produces a markdown report with suggested actions. Spawn weekly, after batch ingests, or when the user says "check the wiki" / "lint my wiki" / "audit the vault".
2327. ElevenLabs Automation ComposioHQ/awesome-claude-skills · score 62/100 (grade D)
      Automate ElevenLabs text-to-speech workflows -- generate speech from text, browse and inspect voices, check subscription limits, list models, stream audio, and retrieve history via the Composio MCP integration.
2328. flowstudio-power-automate-governance github/awesome-copilot · score 62/100 (grade D)
      Govern Power Automate flows and Power Apps at scale using the FlowStudio MCP cached store. Classify flows by business impact, detect orphaned resources, audit connector usage, enforce compliance standards, manage notification rules, and compute governance scores — all without Dataverse or the CoE Starter Kit. Load this skill when asked to: tag or classify flows, set business impact, assign ownership, detect orphans, audit connectors, check compliance, compute archive scores, manage notification rules, run a governance review, generate a compliance report, offboard a maker, or any task that involves writing governance metadata to flows. Requires a FlowStudio for Teams or MCP Pro+ subscription — see https://mcp.flowstudio.app
2329. Lemlist Automation ComposioHQ/awesome-claude-skills · score 62/100 (grade D)
      Automate Lemlist multichannel outreach -- manage campaigns, enroll leads, add personalization variables, export campaign data, and handle unsubscribes via the Composio MCP integration.
2330. mcp-cli github/awesome-copilot · score 62/100 (grade D)
      Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers, list available MCP servers/tools, or call MCP tools from command line.
2331. mcp-create-adaptive-cards github/awesome-copilot · score 62/100 (grade D)
      Skill converted from mcp-create-adaptive-cards.prompt.md
2332. memory-status alirezarezvani/claude-skills · score 62/100 (grade D)
      Memory health dashboard showing line counts, topic files, capacity, stale entries, and recommendations. Use when the user runs /si:memory-status or asks how full or healthy the agent memory is.
2333. Mistral AI Automation ComposioHQ/awesome-claude-skills · score 62/100 (grade D)
      Automate Mistral AI operations -- manage files and libraries, upload documents for fine-tuning, batch processing, and OCR, track fine-tuning jobs, and build RAG pipelines via the Composio MCP integration.
2334. OpenAI Automation ComposioHQ/awesome-claude-skills · score 62/100 (grade D)
      Automate OpenAI API operations -- generate responses with multimodal and structured output support, create embeddings, generate images, and list models via the Composio MCP integration.
2335. pptx-author anthropics/financial-services · score 62/100 (grade D)
      Produce a .pptx file on disk (headless) instead of driving a live PowerPoint document — for managed-agent sessions with no open Office app.
2336. pricing coreyhaines31/marketingskills · score 62/100 (grade D)
      When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'can AI read my pricing.' Use this whenever someone is figuring out what to charge, how to structure their plans, or wants to audit a pricing page (for humans and for the AI agents that shortlist tools). For in-app upgrade screens, see paywalls. For offer construction (bonuses, guarantees, value framing, naming) on services/courses/coaching/high-ticket B2B, see offers.
2337. react-audit-grep-patterns github/awesome-copilot · score 62/100 (grade D)
      Provides the complete, verified grep scan command library for auditing React codebases before a React 18.3.1 or React 19 upgrade. Use this skill whenever running a migration audit - for both the react18-auditor and react19-auditor agents. Contains every grep pattern needed to find deprecated APIs, removed APIs, unsafe lifecycle methods, batching vulnerabilities, test file issues, dependency conflicts, and React 19 specific removals. Always use this skill when writing audit scan commands - do not rely on memory for grep syntax, especially for the multi-line async setState patterns which require context flags.
2338. xlsx-author anthropics/financial-services · score 62/100 (grade D)
      Produce a .xlsx file on disk (headless) instead of driving a live Excel workbook — for managed-agent sessions with no open Office app.
2339. agentic-workflows github/awesome-copilot · score 61/100 (grade D)
      Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
2340. asc-shots-pipeline rudrankriyam/app-store-connect-cli-skills · score 61/100 (grade D)
      Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.
2341. bio-chipseq-chip-deep-learning GPTomics/bioSkills · score 61/100 (grade D)
      Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.
2342. bio-chipseq-chromatin-state-segmentation GPTomics/bioSkills · score 61/100 (grade D)
      Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
2343. bio-epidemiological-genomics-transmission-inference GPTomics/bioSkills · score 61/100 (grade D)
      Infers person-to-person transmission from pathogen genomes using outbreaker2, TransPhylo, phybreak, BadTrIP, SCOTTI, BEASTLIER, and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs; MRSA <=15; C. difficile <=2; Klebsiella <=21), models within-host diversity and transmission bottlenecks, integrates contact-tracing data, distinguishes generation from serial interval, and attributes source via Bayesian source attribution (islandR). Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after a dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB or chronic HIV.
2344. bio-genome-assembly-genome-profiling GPTomics/bioSkills · score 61/100 (grade D)
      Profiles a genome from raw reads BEFORE assembly with a k-mer spectrum (KMC or Jellyfish histogram), then models it with GenomeScope2 to estimate genome size, heterozygosity, repeat content, and ploidy, and Smudgeplot to infer ploidy from heterozygous k-mer pairs (diploid AB vs triploid AAB vs tetraploid AABB). Covers choosing k via Merqury best_k.sh, the k-mer-coverage vs sequencing-coverage confusion, reading het/repeat/contamination/organelle peaks, why noisy ONT must not be used for counting, and how the estimate becomes the NG50 denominator, the Flye -g value, the hifiasm --hom-cov/purge setting, and the 1.5-2x-too-big haplotig sanity check. Use when starting any de novo assembly, deciding whether short reads can work, estimating genome size for an unknown organism, diagnosing ploidy, or sanity-checking an assembly's size against expectation.
2345. bio-genome-intervals-proximity-operations GPTomics/bioSkills · score 61/100 (grade D)
      Performs proximity operations on genomic intervals with bedtools (closest, window, flank, slop) and pybedtools - nearest-feature queries with signed/strand-aware distance, fixed-radius window searches, strand-aware promoter construction, and interval extension. Covers the closest -d/-D a/b/ref/-t/-k/-io/-iu/-id flags, the -D ref strand sign-flip, silent chromosome-end clipping in slop/flank, -t all tie double-counting, and the critical distinction between a geometry answer (nearest TSS) and a biology answer (which gene an element regulates). Use when assigning peaks or variants to genes, defining promoters from a gene model, building distance-to-TSS distributions, finding features within a window, or extending intervals - and when deciding whether nearest-gene is a fair prior (GWAS locus) or a trap (distal enhancer).
2346. bio-pathway-enrichment-visualization GPTomics/bioSkills · score 61/100 (grade D)
      Turns an enrichResult or gseaResult from clusterProfiler/enrichplot into a figure that collapses or shows gene-set redundancy, using dotplot, barplot, cnetplot, emapplot, treeplot, ridgeplot, gseaplot2, and upsetplot. Covers why a default top-20 GO dotplot is one biological theme drawn twenty times (the DAG/nesting guarantees redundant overlapping terms), so the figure is a modeling choice between SHOWING redundancy (pairwise_termsim -> emapplot/treeplot) and DELETING it (simplify/REVIGO); why cnetplot/emapplot/treeplot need pairwise_termsim first; why enrichplot ships no barplot for gseaResult (a bar cannot carry a signed NES); why GeneRatio is not fold enrichment; and why showCategory silently truncates. Use when plotting ORA or GSEA results, collapsing redundant GO terms visually, encoding a dotplot, or building a publication enrichment figure. Statistics come from go-enrichment and gsea; generic ggplot -> data-visualization/ggplot2-fundamentals.
2347. bio-spatial-transcriptomics-spatial-communication GPTomics/bioSkills · score 61/100 (grade D)
      Maps cell-cell communication and ligand-receptor co-expression in spatial transcriptomics (Visium, Xenium, MERFISH, CosMx, Slide-seq) with Squidpy ligrec, COMMOT, stLearn, CellChat-spatial, and NicheNet. Use when choosing a method by whether spatial distance is actually modeled (squidpy ligrec is space-blind cluster-permutation vs COMMOT optimal-transport is distance-aware vs stLearn neighborhood vs CellChat-spatial filter) and by secreted-vs-contact-dependent range; choosing the ligand-receptor database knowingly because it drives the result as much as the algorithm; guarding against segmentation-spillover circularity that fabricates short-range hits; treating every ligand-receptor score as a co-expression hypothesis on a confidence ladder, not validated signaling; correcting for thousands of pair-by-cell-type-pair permutation tests; and recognizing that a targeted imaging panel rarely contains the relevant ligands and receptors so a "no communication" call is uninformative.
2348. bio-structural-biology-geometric-analysis GPTomics/bioSkills · score 61/100 (grade D)
      Measures geometric properties of protein structures with Biopython Bio.PDB - interatomic distances, distance matrices, bond and dihedral angles (phi/psi/chi, Ramachandran), superposition and RMSD, center of mass, radius of gyration, and solvent accessible surface area (SASA). Use when deciding that RMSD depends on BOTH the superposition and the atom selection (a global all-atom RMSD is dominated by flexible loops and hinge motion and is NOT a cross-protein similarity metric); choosing the metric that matches the question (RMSD for same-molecule displacement, TM-score for same-fold, lDDT for superposition-free local model quality - the quantity pLDDT predicts); recognizing Superimposer needs an equal-length ordered atom-to-atom correspondence; and reporting SASA only alongside its probe radius (1.4A water, Shrake-Rupley) with a preference for relative SASA. Keywords RMSD, TM-score, lDDT, SASA, Shrake-Rupley, superposition, Kabsch, dihedral, Ramachandran, radius of gyration.
2349. board alirezarezvani/claude-skills · score 61/100 (grade D)
      Read, write, and browse the AgentHub message board for agent coordination. Use when the user runs /hub:board or asks to post, read, or inspect coordination messages between competing AgentHub agents.
2350. breakdown-epic-pm github/awesome-copilot · score 61/100 (grade D)
      Prompt for creating an Epic Product Requirements Document (PRD) for a new epic. This PRD will be used as input for generating a technical architecture specification.
2351. cross-eval alirezarezvani/claude-skills · score 61/100 (grade D)
      /c-level-agents:cross-eval [memo] — Multi-model consensus on a board memo or strategy brief. Claude + Codex + Gemini cross-review with graceful degradation. Use when a high-stakes memo needs an independent sanity check before the boardroom — e.g. a bet-the-company pivot or fundraise terms.
2352. decide alirezarezvani/claude-skills · score 61/100 (grade D)
      /c-level-agents:decide [memo] — Log a decision to two-layer memory via decision-logger. Approved memo becomes durable; raw transcripts kept for reference. Use when the founder has approved a boardroom memo and the decision must become durable company memory — e.g. right after /c-level-agents:boardroom concludes.
2353. earnings-preview anthropics/financial-services · score 61/100 (grade D)
      Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull/bear scenarios, and identify what will move the stock. Triggers on "earnings preview", "what to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".
2354. google-cloud-global-frontend-configuration google/skills · score 61/100 (grade D)
      Guides agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
2355. mini-context-graph github/awesome-copilot · score 61/100 (grade D)
      A persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch.
2356. prediction-market-oracle-research affaan-m/ECC · score 61/100 (grade D)
      Research prediction markets as data sources or oracle signals for products, agents, dashboards, and corporate decision intelligence. Use for source-grounded analysis of market-implied probabilities, caveats, and integration patterns without investment advice. Use when evaluating prediction markets as a data source or oracle signal for a product, agent, or dashboard.
2357. prediction-market-oracle-research affaan-m/everything-claude-code · score 61/100 (grade D)
      Research prediction markets as data sources or oracle signals for products, agents, dashboards, and corporate decision intelligence. Use for source-grounded analysis of market-implied probabilities, caveats, and integration patterns without investment advice. Use when evaluating prediction markets as a data source or oracle signal for a product, agent, or dashboard.
2358. product-decision-agent sickn33/antigravity-awesome-skills · score 61/100 (grade D)
      中文产品决策 Agent。用于需求优先级、Roadmap、增长、留存、运营、数据异常、A/B Test、项目延期和跨团队协作；先判断事实、阶段、核心阻塞与主导机制，再给出下一步、停止清单和切换条件。默认中文，不引用原文或讲历史。
2359. qdrant-model-migration github/awesome-copilot · score 61/100 (grade D)
      Guides embedding model migration in Qdrant without downtime. Use when someone asks 'how to switch embedding models', 'how to migrate vectors', 'how to update to a new model', 'zero-downtime model change', 'how to re-embed my data', or 'can I use two models at once'. Also use when upgrading model dimensions, switching providers, or A/B testing models.
2360. wiki-lint alirezarezvani/claude-skills · score 61/100 (grade D)
      Run a health check on the LLM Wiki vault — mechanical checks (orphans, broken links, stale pages, missing frontmatter, log gap, duplicates) plus semantic checks (contradictions, cross-reference gaps, concepts missing their own page). Outputs a markdown report with suggested actions. Usage /wiki-lint [--stale-days N] [--log-gap-days N]
2361. x402-express-wrapper sickn33/antigravity-awesome-skills · score 61/100 (grade D)
      Wrapper oficial de M2MCent (Node.js) para inyectar muros de pago x402 en APIs o servidores Model Context Protocol (MCP). Usar al construir nuevos servicios que requieran monetización máquina a máquina.
2362. bio-comparative-genomics-pangenome-analysis GPTomics/bioSkills · score 60/100 (grade D)
      Build and analyze pangenomes for prokaryotes (Panaroo, PPanGGOLiN, PEPPAN, GET_HOMOLOGUES, anvi'o pangenomics) and eukaryotes (Minigraph-Cactus, PGGB, vg pangenome graphs). Implement Tettelin core/accessory/cloud genome decomposition (Tettelin 2005), Heap's law open/closed pangenome modeling, gene presence/absence GWAS (Scoary, pyseer), pangenome graph variant calling (vg, PanGenie), and structural-variation graph indexing. Use when assembling species- or genus-level pan-gene catalogs, separating core from accessory/shell/cloud genes, testing gene-content associations with phenotypes, building pangenome graphs from haplotype-resolved assemblies, calling SVs from pangenome graphs, or selecting between bacterial-pangenome and eukaryotic-pangenome workflows.
2363. bio-copy-number-allele-specific-copy-number GPTomics/bioSkills · score 60/100 (grade D)
      Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and PureCN (tumor-only). Covers the purity-ploidy identifiability problem, the diploid-baseline (dipLogR) anchor, major/minor copy number, loss of heterozygosity, sunrise/contour fit diagnostics, and reconciliation of conflicting fits. Use when tumor analysis needs absolute copy number rather than relative log2, when estimating purity and ploidy, calling LOH or copy-neutral LOH, resolving whole-genome doubling, running tumor-only allele-specific calling, or choosing among ASCAT, Sequenza, FACETS, and PureCN.
2364. bio-experimental-design-randomization-blocking GPTomics/bioSkills · score 60/100 (grade D)
      Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.
2365. bio-immunoinformatics-immunogenicity-scoring GPTomics/bioSkills · score 60/100 (grade D)
      Rank and prioritize neoantigen/epitope candidates by likely T-cell response using NeoFox feature annotation, PRIME2.0, BigMHC-IM, the Łuksza/Balachandran fitness model (agretopicity + foreignness), and pVACtools tiering. Encodes the field's hard truths that immunogenicity is the least-solved layer (dedicated scores ~AUROC 0.6-0.7, modest PPV), that scores are valid only for RANKING within one patient (never absolute go/no-go or cross-patient), that DAI has anchor-inflation and WT-denominator traps, and that stacking weak correlated scores into one number is a red flag. Use when ordering a candidate list for a vaccine. Binding lives in mhc-binding-prediction; calling in neoantigen-prediction.
2366. bio-long-read-sequencing-long-read-alignment GPTomics/bioSkills · score 60/100 (grade D)
      Aligns Oxford Nanopore and PacBio long reads (and assemblies) to a reference with minimap2 using the error-rate-matched preset (map-ont, lr:hq, map-hifi, map-pb, splice/splice:hq, asm5/10/20, ava), producing a sorted/indexed BAM for variant, SV, methylation, or isoform analysis. Covers why the preset rewrites the scoring/chaining model, why SV calling rides on supplementary not secondary alignments, carrying MM/ML methylation tags through with -y, the multi-part-index MAPQ trap, and when to swap in Winnowmap/VACmap/lra/pbmm2. Use when mapping ONT or PacBio reads, choosing a minimap2 preset by platform/chemistry, preparing input for Clair3/medaka/Sniffles/modkit, aligning into repeats/centromeres, or spliced-aligning cDNA/Iso-Seq.
2367. bio-structural-biology-modern-structure-prediction GPTomics/bioSkills · score 60/100 (grade D)
      Predicts protein and complex structures with deep-learning models (ESMFold, AlphaFold2/ColabFold, AlphaFold3, Chai-1, Boltz-1/2) and reconciles them with confidence metrics. Use when choosing a predictor by input and question rather than novelty (ESMFold single-chain, no-MSA, fast, metagenomic-scale vs AlphaFold3/Chai-1/Boltz for complexes, ligands, nucleic acids, ions, PTMs); recognizing that MSA depth is the dominant accuracy determinant so ESMFold trades accuracy for speed and degrades on orphan proteins; gating a complex on ipTM plus inter-chain PAE, not per-chain pLDDT; reading pLDDT as local confidence, PAE as inter-domain/inter-chain positioning, pTM as global fold; knowing a single prediction is one dominant conformer not an ensemble (no apo/holo, allosteric, or fold-switch states), that these are not variant-effect/ddG/affinity engines, and that a confident prediction is a hypothesis, not an experiment. Keywords ESMFold, AlphaFold3, Chai-1, Boltz-1, ColabFold, ipTM, PAE, pLDDT, MSA depth.
2368. claude-to-deerflow bytedance/deer-flow · score 60/100 (grade D)
      Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.
2369. continuous-agent-loop affaan-m/ECC · score 60/100 (grade D)
      Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls. Use when running an agent loop that must self-check, gate on evals, and recover from failures.
2370. continuous-agent-loop affaan-m/everything-claude-code · score 60/100 (grade D)
      Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls. Use when running an agent loop that must self-check, gate on evals, and recover from failures.
2371. cpo-review alirezarezvani/claude-skills · score 60/100 (grade D)
      /c-level-agents:cpo-review [plan] — JTBD-driven interrogation of product roadmap, PMF signal, and portfolio focus. Use when committing a quarter's roadmap, deciding whether to kill a feature, or claiming PMF without a retention curve.
2372. cs-financial-analyst alirezarezvani/claude-skills · score 60/100 (grade D)
      Financial Analyst agent for DCF valuation, financial modeling, budgeting, forecasting, and SaaS metrics (ARR, MRR, churn, CAC, LTV, NRR). Orchestrates finance skills. Spawn when users need financial analysis, valuation models, budget planning, ratio analysis, SaaS health checks, or unit economics projections.
2373. cs-onboard alirezarezvani/claude-skills · score 60/100 (grade D)
      Founder onboarding interview that captures company context across 7 dimensions. Invoke with /cs-onboard setup for initial interview or /cs-onboard update for quarterly refresh. Generates ~/.claude/company-context.md used by all C-suite advisor skills. Use when setting up the C-suite advisors for the first time, or when company context is missing or more than 90 days old — e.g. after a fundraise or pivot.
2374. Docker Hub Automation ComposioHQ/awesome-claude-skills · score 60/100 (grade D)
      Automate Docker Hub operations -- manage organizations, repositories, teams, members, and webhooks via the Composio MCP integration.
2375. freeze alirezarezvani/claude-skills · score 60/100 (grade D)
      /c-level-agents:freeze [decision] [days] — Lock a strategic decision for a cooldown period to prevent impulse reversal. Mirrors gstack's safety primitives for the business layer. Use when an irreversible decision was made under pressure — e.g. a layoff plan or multi-year contract — and deserves a cooling-off lock before execution.
2376. Gong Automation ComposioHQ/awesome-claude-skills · score 60/100 (grade D)
      Automate Gong conversation intelligence -- retrieve call recordings, transcripts, detailed analytics, speaker stats, and workspace data -- using natural language through the Composio MCP integration.
2377. Neon Automation ComposioHQ/awesome-claude-skills · score 60/100 (grade D)
      Automate Neon serverless Postgres operations -- manage projects, branches, databases, roles, and connection URIs via the Composio MCP integration.
2378. onboard alirezarezvani/claude-skills · score 60/100 (grade D)
      /cs-onboard — Founder interview that populates ~/.claude/company-context.md using the canonical 7-dimension cs-onboard schema. The first command to run when starting with c-level-agents. Use when setting up the virtual C-suite for a new company, or when advisors lack company context — e.g. before a first /c-level-agents:boardroom or after a fundraise changes the numbers.
2379. Snowflake Automation ComposioHQ/awesome-claude-skills · score 60/100 (grade D)
      Automate Snowflake data warehouse operations -- list databases, schemas, and tables, execute SQL statements, and manage data workflows via the Composio MCP integration.
2380. wiki-log alirezarezvani/claude-skills · score 60/100 (grade D)
      Show recent entries from the LLM Wiki log (wiki/log.md). Uses the standardized ## [YYYY-MM-DD] header format so grep + tail works. Usage /wiki-log [--last N] [--op ingest|query|lint|...]
2381. antithesis-skills-feedback antithesishq/antithesis-skills · score 59/100 (grade D)
      File a bug report or feedback on the Antithesis skills by opening a pre-filled GitHub issue URL (skill name, skill version, agent, short summary). Load when the user wants to report a problem with, or give feedback on, any Antithesis skill. Does not auto-submit — presents the URL for the user to review.
2382. Apollo Automation ComposioHQ/awesome-claude-skills · score 59/100 (grade D)
      Automate Apollo.io lead generation -- search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists -- using natural language through the Composio MCP integration.
2383. Attio Automation ComposioHQ/awesome-claude-skills · score 59/100 (grade D)
      Automate Attio CRM operations -- search records, query contacts and companies with advanced filters, manage notes, list attributes, and navigate your relationship data -- using natural language through the Composio MCP integration.
2384. bigquery-ai-ml google/skills · score 59/100 (grade D)
      Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.
2385. bio-comparative-genomics-ancestral-reconstruction GPTomics/bioSkills · score 59/100 (grade D)
      Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.
2386. bio-comparative-genomics-gene-tree-species-tree-reconciliation GPTomics/bioSkills · score 59/100 (grade D)
      Reconcile gene trees against a species tree under probabilistic models of duplication, transfer, and loss (DTL) using ALE (Szöllősi 2013 amalgamated likelihood), GeneRax (Morel 2020 ML reconciliation), AleRax (Morel 2024 co-estimation), Whale.jl (Bayesian DL+WGD), RANGER-DTL 2 parsimony, NOTUNG, ecceTERA, and Treerecs. Use when inferring ancestral gene-family content, distinguishing duplication from horizontal transfer from differential loss, rooting deep species trees from gene-content signals (STRIDE / Williams 2017 ALE-rooting), counting DTL events per branch, refining noisy gene trees against a species tree, modeling WGD events jointly with DTL, or producing publication-grade gene-family histories for phylogenomic / comparative analyses.
2387. bio-epidemiological-genomics-variant-surveillance GPTomics/bioSkills · score 59/100 (grade D)
      Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
2388. bio-population-genetics-population-structure GPTomics/bioSkills · score 59/100 (grade D)
      Infers and describes population structure with PCA (plink2 --pca, smartpca/EIGENSOFT, FlashPCA2), model-based clustering (ADMIXTURE, fastSTRUCTURE), FST estimators (Weir-Cockerham vs Hudson), and f-statistics (f3/f4/D via AdmixTools/admixr), plus Python plotting of PCs and Q barplots. Every output is a model-conditioned description of variance, not truth: PCs conflate ancestry with LD/inversions/relatedness/batch, ADMIXTURE Q-values are panel- and K-dependent artifacts, and CV-minimum K is a guide not the true population count. FST must combine SNPs as a ratio of averages (sum numerators / sum denominators), never an average of per-SNP FST; negative per-SNP FST is normal and must not be clamped. f3/f4/D need a block jackknife or the significance is fake. Use when running PCA, ADMIXTURE, FST, or f-statistics on QC'd genotypes. For QC and KING relatedness see plink-basics; for LD pruning see linkage-disequilibrium; for array-based Python pipelines see scikit-allel-analysis.
2389. bio-structural-biology-alphafold-predictions GPTomics/bioSkills · score 59/100 (grade D)
      Retrieves and interprets AlphaFold Protein Structure Database (AFDB) models by UniProt accession, reading pLDDT and PAE confidence correctly. Use when treating pLDDT as PER-RESIDUE confidence (not global accuracy) and recognizing a long low-pLDDT stretch as an intrinsically disordered region rather than a modeling error; reading PAE to segment confident domains and judge inter-domain/relative-position confidence that high mean pLDDT cannot certify; recognizing a static AFDB model carries NO ligands, ions, cofactors, PTMs, quaternary assembly, or alternative conformations (pLDDT sits in the B-factor column with opposite polarity to thermal motion); and deciding an AFDB entry vs re-running prediction. Keywords AlphaFold DB, pLDDT, PAE, B-factor column, intrinsic disorder, UniProt, Foldseek.
2390. bio-structural-biology-structure-validation GPTomics/bioSkills · score 59/100 (grade D)
      Judges whether a macromolecular model (or a region of it) is reliable enough to build on, using resolution, R-free, B-factors, MolProbity geometry, and predicted-model confidence with Bio.PDB. Use when deciding if a structure or a specific region is trustworthy before docking/mechanism/measurement; reading resolution, R-work vs R-free and the R-free-minus-R-work overfitting gap; sanity-checking per-residue and mean B-factors; flagging clashscore, Ramachandran and rotamer outliers and cis non-proline peptides; validating a PREDICTED (AlphaFold/ESMFold) model via pLDDT bands and PAE before docking or molecular replacement; and interpreting cryo-EM global-vs-local resolution (FSC 0.143 half-map vs 0.5 map-model) or an NMR ensemble spread. Keywords validation, resolution, R-free, B-factor, MolProbity, clashscore, Ramachandran, rotamer, pLDDT, PAE, wwPDB, cryo-EM local resolution.
2391. bio-systems-biology-flux-balance-analysis GPTomics/bioSkills · score 59/100 (grade D)
      Performs flux balance analysis (FBA), flux variability analysis (FVA), parsimonious FBA (pFBA), loopless FBA, flux sampling, and production envelopes on genome-scale metabolic models with COBRApy, solving the biomass-maximization linear program under a defined medium. Use when predicting growth rate on a carbon source, computing flux ranges and alternative optima (FVA), setting exchange bounds and minimal media, distinguishing a real growth phenotype from an under-constrained model, sampling the flux solution space, or choosing between FBA, pFBA, loopless FBA, and sampling for a flux distribution.
2392. brief alirezarezvani/claude-skills · score 59/100 (grade D)
      /c-level-agents:brief [topic] — Generate a one-page strategy brief from an office-hours intake. First step in the strategic sprint pipeline. Use when a strategic question needs to be framed before boardroom deliberation — e.g. locking options, assumptions, and success criteria for a pricing change or a market-entry decision.
2393. cs-growth-strategist alirezarezvani/claude-skills · score 59/100 (grade D)
      Growth Strategist agent for revenue operations, sales engineering, customer success, and business development. Orchestrates business-growth skills. Spawn when users need pipeline analysis, churn prevention, expansion scoring, sales demos, or proposal writing.
2394. cs-wiki-ingestor alirezarezvani/claude-skills · score 59/100 (grade D)
      Dispatched sub-agent that ingests a new source into an LLM Wiki vault. Reads the source, proposes TL;DR and key claims, identifies which entity/concept/synthesis pages will be touched, flags contradictions with existing pages, and — after user confirmation — writes the source summary, updates cross-references across 5-15 pages, regenerates the index, and appends a standardized log entry. Spawn when the user says "ingest this", "add this paper/article/book to the wiki", or drops a file into raw/.
2395. enterprise-agent-ops affaan-m/ECC · score 59/100 (grade D)
      Operational controls for long-lived or cloud-hosted agent systems — runtime lifecycle (start, pause, stop, restart), observability (logs, metrics, traces), least-privilege safety scopes and kill switches, and rollout/rollback change management with audit logs and success/cost metrics. Use when running production agent fleets on PM2, systemd, or containers that need monitoring, incident response, or deployment gates.
2396. enterprise-agent-ops affaan-m/everything-claude-code · score 59/100 (grade D)
      Operational controls for long-lived or cloud-hosted agent systems — runtime lifecycle (start, pause, stop, restart), observability (logs, metrics, traces), least-privilege safety scopes and kill switches, and rollout/rollback change management with audit logs and success/cost metrics. Use when running production agent fleets on PM2, systemd, or containers that need monitoring, incident response, or deployment gates.
2397. founder-mode alirezarezvani/claude-skills · score 59/100 (grade D)
      /c-level-agents:founder-mode [question] — Auto-routes any founder question to the right C-role advisor or to /c-level-agents:boardroom for multi-role topics. The single-command entry point. Use when a founder asks any strategic question without knowing which advisor or command fits — e.g. 'runway pressure' routes to the CFO, 'gross retention dropped' routes to the CCO.
2398. model-update anthropics/financial-services · score 59/100 (grade D)
      Update financial models with new data — quarterly earnings, management guidance, macro changes, or revised assumptions. Adjusts estimates, recalculates valuation, and flags material changes. Use after earnings, guidance updates, or when assumptions need refreshing. Triggers on "update model", "plug earnings", "refresh estimates", "update numbers for [company]", "new guidance", or "revise estimates".
2399. orch-build-mvp affaan-m/ECC · score 59/100 (grade D)
      Orchestrate bootstrapping a working MVP from a design or spec document — ingest the SDD/PRD, plan thin vertical slices, scaffold the first end-to-end slice, then drive a generator-evaluator build loop with review and gated feat commits. Use when a design or spec document must become a running MVP through planned vertical slices.
2400. orch-build-mvp affaan-m/everything-claude-code · score 59/100 (grade D)
      Orchestrate bootstrapping a working MVP from a design or spec document — ingest the SDD/PRD, plan thin vertical slices, scaffold the first end-to-end slice, then drive a generator-evaluator build loop with review and gated feat commits. Use when a design or spec document must become a running MVP through planned vertical slices.
2401. returns-analysis anthropics/financial-services · score 59/100 (grade D)
      Build quick IRR/MOIC sensitivity tables for PE deal evaluation. Models returns across entry multiple, leverage, exit multiple, growth, and hold period scenarios. Use when sizing up a deal, stress-testing assumptions, or preparing IC returns exhibits. Triggers on "returns analysis", "IRR sensitivity", "MOIC table", "what's the return at", "model the returns", or "back of the envelope".
2402. wiki-ingest alirezarezvani/claude-skills · score 59/100 (grade D)
      Ingest a source file from raw/ into the LLM Wiki — read, discuss, write summary page, update cross-references across 5-15 pages, regenerate index, append to log. Usage /wiki-ingest <path-to-source>
2403. 4x4 davidondrej/skills · score 58/100 (grade D)
      Pull 16 fast decisions out of the user with 4 sets of 4 open questions, then present an implementation plan. Only for risky changes, large product decisions, or large refactors. Run when the user types /4x4. Agents may suggest it in one line but never start it on their own.
2404. bio-causal-genomics-heritability-partitioning GPTomics/bioSkills · score 58/100 (grade D)
      Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.
2405. bio-epidemiological-genomics-phylodynamics GPTomics/bioSkills · score 58/100 (grade D)
      Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.
2406. bio-imaging-mass-cytometry-differential-analysis GPTomics/bioSkills · score 58/100 (grade D)
      Compare cell-type composition and spatial features across conditions in IMC/MIBI cohorts with the patient as the experimental unit, covering pseudoreplication, per-patient aggregation, mixed models, compositional (Dirichlet/scCODA) differential abundance, diffcyt, per-image-to-patient spatial differential testing (SpaceANOVA), batch covariates, and FDR. Use when testing whether a cell type or spatial niche differs between groups, avoiding cell-level pseudoreplication, choosing a differential-abundance method, or correctly powering an IMC cohort comparison.
2407. company-valuation himself65/finance-skills · score 58/100 (grade D)
      Estimate a public company's intrinsic value with DCF, relative (peer multiple), and sum-of-the-parts (SOTP) methods, then blend them into an implied share price with upside/downside vs the market price, a WACC and terminal-growth sensitivity grid, and bull/base/bear scenarios. Use this skill whenever the user asks what a company or ticker is worth: fair value, intrinsic value, implied share price, a price target from fundamentals, whether it is overvalued or undervalued, building a DCF (WACC, terminal value, discounted cash flow), EV/EBITDA or P/E based targets, peer comparison valuation, or SOTP and conglomerate discounts. Run the model rather than answering valuation questions from memory.
2408. cs-wiki-librarian alirezarezvani/claude-skills · score 58/100 (grade D)
      Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back into the wiki as a new comparison or synthesis page. Spawn when the user asks a substantive question the wiki might answer, says "what does the wiki say about X", "compare A and B across my sources", or wants to explore a topic.
2409. customer-journey Illyism/seo-skills · score 58/100 (grade D)
      Map how customers discover, evaluate, and choose a product across Google, AI chatbots (ChatGPT, Claude, Perplexity), and social platforms, using the 5-stage awareness journey. Use when the user asks about search intent, AI SEO prompts, discoverability, buyer journeys, awareness stages, or what content to create for a brand, website, or keyword list.
2410. Kommo Automation ComposioHQ/awesome-claude-skills · score 58/100 (grade D)
      Automate Kommo CRM operations -- manage leads, pipelines, pipeline stages, tasks, and custom fields -- using natural language through the Composio MCP integration.
2411. Lemon Squeezy Automation ComposioHQ/awesome-claude-skills · score 58/100 (grade D)
      Automate Lemon Squeezy store management -- products, orders, subscriptions, customers, discounts, and checkout tracking -- using natural language through the Composio MCP integration.
2412. merger-model anthropics/financial-services · score 58/100 (grade D)
      Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms. Triggers on "merger model", "accretion dilution", "M&A model", "pro forma EPS", "merger consequences", or "deal impact analysis".
2413. nanoclaw-repl affaan-m/ECC · score 58/100 (grade D)
      Operate and extend NanoClaw, ECC's zero-dependency session-aware REPL, with persistent markdown-backed sessions and slash commands for model switching, skill loading, session branching, cross-session search, history compaction, and export. Use when running or extending scripts/claw.js, or when resuming, branching, compacting, searching, or exporting a NanoClaw session.
2414. nanoclaw-repl affaan-m/everything-claude-code · score 58/100 (grade D)
      Operate and extend NanoClaw, ECC's zero-dependency session-aware REPL, with persistent markdown-backed sessions and slash commands for model switching, skill loading, session branching, cross-session search, history compaction, and export. Use when running or extending scripts/claw.js, or when resuming, branching, compacting, searching, or exporting a NanoClaw session.
2415. New Relic Automation ComposioHQ/awesome-claude-skills · score 58/100 (grade D)
      Automate New Relic observability workflows -- manage alert policies, notification channels, alert conditions, and monitor applications and browser apps via the Composio MCP integration.
2416. wiki-query alirezarezvani/claude-skills · score 58/100 (grade D)
      Query the LLM Wiki — reads index.md first, drills into 3-10 relevant pages, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back as a new comparison or synthesis page. Usage /wiki-query "<question>
2417. bio-clinical-biostatistics-bayesian-trials GPTomics/bioSkills · score 57/100 (grade D)
      Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.
2418. bio-structural-biology-structure-navigation GPTomics/bioSkills · score 57/100 (grade D)
      Navigate the Bio.PDB SMCRA hierarchy (Structure-Model-Chain-Residue-Atom) safely, surfacing the heterogeneity it hides by default. Use when deciding how to handle altloc/DisorderedAtom conformers before a distance or RMSD, indexing residues insertion-code-safe with the full (hetflag, resseq, icode) tuple, choosing the ATOM/observed vs SEQRES/canonical vs UniProt sequence, selecting the right Model for an NMR ensemble, filtering waters/hetero/metals correctly, and reconciling auth vs label numbering. Keywords SMCRA, altloc, DisorderedAtom, insertion code, SEQRES, PPBuilder, auth_seq_id.
2419. Capsule CRM Automation ComposioHQ/awesome-claude-skills · score 57/100 (grade D)
      Automate Capsule CRM operations -- manage contacts (parties), run structured filter queries, track tasks and projects, log entries, and handle organizations -- using natural language through the Composio MCP integration.
2420. caveman-stats JuliusBrussee/caveman · score 57/100 (grade D)
      Show recorded output and cache-read token usage and mode attribution for the current Claude Code session, or locate the host's native usage report. Trigger: /caveman-stats.
2421. dbt-model-index warpdotdev/oz-skills · score 57/100 (grade D)
      Provide a lookup index of dbt models (BigQuery tables) to guide query writing against a data warehouse. Use when you need to query, analyze, or look up data in a dbt-powered data warehouse, or when resolving a vague data question into the right BigQuery tables to query.
2422. llm-cost-optimizer alirezarezvani/claude-skills · score 57/100 (grade D)
      Use proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize token usage', 'which model should I use', 'LLM spend is out of control', 'implement prompt caching', 'we're about to launch an AI feature', 'build me an AI endpoint'. Don't wait for an explicit cost complaint -- if someone is building an AI feature, designing an LLM endpoint, or choosing between models, cost architecture belongs in the conversation. Apply immediately when any of these are true: a system prompt appears that exceeds a few hundred tokens, all requests are hitting the same model, max_tokens is not set, or no per-feature cost logging exists. NOT for RAG pipeline design (use rag-architect). NOT for improving prompt quality or effectiveness (use senior-prompt-engineer).
2423. openclaw-persona-forge affaan-m/ECC · score 57/100 (grade D)
      为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡， 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill，可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于：微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词：龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。 Use when creating, designing, or customizing an OpenClaw lobster persona — identity, SOUL.md, name, or avatar prompt.
2424. openclaw-persona-forge affaan-m/everything-claude-code · score 57/100 (grade D)
      为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡， 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill，可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于：微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词：龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。 Use when creating, designing, or customizing an OpenClaw lobster persona — identity, SOUL.md, name, or avatar prompt.
2425. bio-ecological-genomics-biodiversity-metrics GPTomics/bioSkills · score 56/100 (grade D)
      Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-analysis).
2426. chief-of-staff mattpocock/skills · score 56/100 (grade D)
      Pursue a long-running goal in a single session by co-ordinating subagents.
2427. datanalysis-credit-risk github/awesome-copilot · score 56/100 (grade D)
      Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.
2428. internal-comms ComposioHQ/awesome-claude-skills · score 56/100 (grade D)
      A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
2429. internal-comms anthropics/skills · score 56/100 (grade D)
      A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
2430. office-hours alirezarezvani/claude-skills · score 56/100 (grade D)
      /c-level-agents:office-hours [topic] — YC-style 6-question founder interrogation before any advice. Forces clarity on problem, customer, distribution, defensibility, capital, and founder fit. Use when a founder question is too vague to route — e.g. 'should we grow faster?' — or before drafting a strategy brief.
2431. rating-prompt-strategy Eronred/aso-skills · score 56/100 (grade D)
      When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, see aso-audit.
2432. wiki-init alirezarezvani/claude-skills · score 56/100 (grade D)
      Bootstrap a fresh LLM Wiki vault with the three-layer structure, schema files, and starter templates. Usage /wiki-init <path> --topic "<topic>" [--tool all|claude-code|codex|cursor|antigravity]
2433. cs-aeo alirezarezvani/claude-skills · score 55/100 (grade D)
      Answer Engine Optimization (AEO) specialist agent. Use when content needs to be optimized for citation by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) rather than for traditional search rankings. Orchestrates the aeo skill — runs E-E-A-T audit, generates optimization variants in conservative/balanced/aggressive modes, and maintains a citation tracking ledger. Industry-aware (8 industries with calibrated thresholds). Distinguishes AEO from SEO and refuses to optimize for one channel at the expense of the other. Voice — pragmatic content strategist; respects existing SEO investments; insists on real first-person evidence over fabricated authority signals.
2434. cs-backend-review alirezarezvani/claude-skills · score 55/100 (grade D)
      Backend engineering review — walks the 7 Matt Pocock forcing questions (read/write ratio + QPS, tenancy, sync vs async, data sensitivity, pattern, RPO/RTO, SLO), picks the language + pattern profile, forks into specialists (api-design-reviewer, database-designer, migration-architect, slo-architect). Invokes the cs-backend-engineer agent with context fork.
2435. playwright-explore-website github/awesome-copilot · score 55/100 (grade D)
      Website exploration for testing using Playwright MCP
2436. post-mortem alirezarezvani/claude-skills · score 55/100 (grade D)
      /c-level-agents:post-mortem [decision] — Honest retrospective on an executed decision, scored against original assumptions and dissent. Closes the strategic sprint loop. Use when a decision hits its 90-day review checkpoint or its kill criteria trigger — e.g. scoring last quarter's pricing change against its pre-committed success metrics.
2437. bio-temporal-genomics-trajectory-modeling GPTomics/bioSkills · score 54/100 (grade D)
      Models continuous temporal trajectories from BULK or time-resolved omics where the x-axis is measured experimental time: penalized GAMs (mgcv) for smooth trends and changepoint detection (segmented, ruptures) for abrupt regime shifts. Use when deciding between a smooth GAM and a changepoint model; choosing the GAM distribution (nb() plus a library-size offset for raw counts vs Gaussian on vst/log-CPM); setting the basis-dimension ceiling k below the number of timepoints and letting REML pick wiggliness; handling residual autocorrelation across timepoints with corAR1/bam(rho=); testing whether two conditions' trajectories diverge with an ordered-factor difference smooth; and choosing a changepoint search/cost/penalty (Pelt/Binseg, l2/rbf). Not for single-cell pseudotime (see single-cell/trajectory-inference).
2438. boost-prompt github/awesome-copilot · score 54/100 (grade D)
      Interactive prompt refinement workflow: interrogates scope, deliverables, constraints; copies final markdown to clipboard; never writes code. Requires the Joyride extension.
2439. captions-overlay heygen-com/hyperframes · score 54/100 (grade D)
      Overlay doctrine for captions in HyperFrames videos — the caption MODEL (drop / rail / embed) and the rule that captions are an OVERLAY composited on top of the film, never a reserved bottom band you shift content up to avoid. Load when adding captions/subtitles to a talking-head or launch video, when deciding whether a phrase should be dropped, ride the verbatim rail, or be promoted to a scarce embedded climax, when laying out a composition that will carry captions (do NOT reserve a keep-out band), or when centering a composition on the true frame center under captions. Applies ON TOP of the `/hyperframes` skill's references/captions.md.
2440. cs-frontend-review alirezarezvani/claude-skills · score 54/100 (grade D)
      Frontend engineering review — walks the 7 Matt Pocock forcing questions (device, LCP target, rendering, bundle budget, SEO vs auth, design system, WCAG), picks the framework + rendering profile, forks into specialists (a11y-audit, performance-profiler, epic-design). Invokes the cs-frontend-engineer agent with context fork.
2441. cs-fullstack-review alirezarezvani/claude-skills · score 53/100 (grade D)
      Fullstack engineering review — walks the 7 Matt Pocock forcing questions, picks the profile, forks into POWERFUL specialists (api-design-reviewer, database-designer, slo-architect). Invokes the cs-fullstack-engineer agent with context fork.
2442. playwright-automation-fill-in-form github/awesome-copilot · score 53/100 (grade D)
      Automate filling in a form using Playwright MCP
2443. structured-autonomy-implement github/awesome-copilot · score 53/100 (grade D)
      Structured Autonomy Implementation Prompt
2444. claude-handoff mattpocock/skills · score 52/100 (grade D)
      Hand the current conversation off to a fresh background agent that picks up the work immediately.
2445. qdrant-search-quality github/awesome-copilot · score 52/100 (grade D)
      Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?'. Also use when search quality degrades after quantization, model change, or data growth.
2446. RingCentral Automation ComposioHQ/awesome-claude-skills · score 52/100 (grade D)
      RingCentral automation via Rube MCP -- toolkit not currently available in Composio; no RING_CENTRAL_ tools found
2447. Zoho Desk Automation ComposioHQ/awesome-claude-skills · score 52/100 (grade D)
      Zoho Desk automation via Rube MCP -- toolkit not currently available in Composio; no ZOHO_DESK_ tools found
2448. handoff mattpocock/skills · score 51/100 (grade D)
      Compact the current conversation into a handoff document for another agent to pick up.
2449. azure-role-selector github/awesome-copilot · score 50/100 (grade D)
      When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.
2450. research mattpocock/skills · score 50/100 (grade D)
      Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
2451. template-skill ComposioHQ/awesome-claude-skills · score 49/100 (grade F)
      Replace with description of the skill and when Claude should use it.
2452. better-prompt davidondrej/skills · score 48/100 (grade F)
      Rewrite a prompt into a deeper version of the same task, the way a top professional would approach it. Use only when explicitly invoked with /better-prompt.
2453. remember-interactive-programming github/awesome-copilot · score 48/100 (grade F)
      A micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.
2454. template-skill anthropics/skills · score 48/100 (grade F)
      Replace with description of the skill and when Claude should use it.
2455. decisions davidondrej/skills · score 47/100 (grade F)
      Ask the agent to list all choices it made during the current work that it is not confident of. Manual-only; the user must ask for it by name.
2456. Finance Lead alirezarezvani/claude-skills · score 46/100 (grade F)
      Startup CFO who builds models that survive contact with reality. Handles fundraising, unit economics, pricing, burn rate, and board reporting. Speaks fluent spreadsheet but translates to English for founders who'd rather build product. Use when a money question needs a model, not a vibe — e.g., building an 18-month runway plan with three scenarios, or pressure-testing unit economics and pricing before a fundraise. (For DCF and SaaS-metrics tooling, see cs-financial-analyst.)