Testing Skills

Test automation and QA. This page lists all 1503 Testing 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 Testing.

code-review luongnv89/skills · score 95/100 (grade A)
Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup. Pass mode:review|perf|clean|cleanup or infer. Don't use for writing features or generating tests (use test-coverage).
init-idd luongnv89/idd · score 95/100 (grade A)
Generate a .idd.yml by auto-detecting a repo's stack, test runner, and size. Use to init, setup, or configure IDD Stack, or set up IDD. Don't use for editing an existing .idd.yml, creating issues (use /issue-creator), or plain git/npm init.
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.
cleanup-project luongnv89/skills · score 93/100 (grade A)
Prepare a git repo before new work: review uncommitted changes, fix .gitignore, delete merged branches, end on clean main, or inspect one branch before deciding. Don't use for dead code, commit-and-push, releases, LICENSE files, or git how-tos.
devops-pipeline luongnv89/skills · score 93/100 (grade A)
Configure pre-commit hooks and lean GitHub Actions for shift-left quality assurance. Use when adding or auditing CI/CD to maximize local test coverage and minimize CI cost. Skip for Terraform/K8s, deployment pipelines, or non-GitHub CI providers.
github-pages-publish luongnv89/skills · score 93/100 (grade A)
Publish or update a static site (gh-pages) on GitHub Pages via GitHub Actions in any repo: text or pre-built HTML in, workflow set up, live URL verified. Don't use for CI test pipelines, framework/SSG builds, or Netlify/Vercel hosting.
test-coverage luongnv89/skills · score 93/100 (grade A)
Generate unit tests for untested branches and edge cases. Use when coverage is low, CI flags gaps, or a release needs hardening. Not for integration/E2E suites, framework migrations, or fixing production bugs.
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.
user-test luongnv89/skills · score 93/100 (grade A)
Test an app, API or CLI like a real user: launch it, try every feature or named ones, log bugs, perf and UX issues, auto-fix simple ones, report. Don't use for unit tests, E2E suite code, or design audits.
codebase-modernizer luongnv89/skills · score 92/100 (grade A)
Audit a stale, inherited, or messy codebase — deps, bugs, security, tests, CI, docs, UI/UX — then emit a phased, testable modernization plan. Read-only: plans upgrades, never applies them. Not for single-PR review, PRD-to-tasks, or UX-only audits.
landing-page-generator luongnv89/skills · score 92/100 (grade A)
Write landing pages (PAS, AIDA, StoryBrand) from a brief or README, as HTML with privacy, terms, changelog, setup pages. Use for sales copy, hero sections, CTAs, README rewrites. Don't use for blogs, release notes, project docs, or coding mockups.
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.
nextflow K-Dense-AI/claude-scientific-skills · score 91/100 (grade A)
Builds, runs, and debugs Nextflow DSL2 pipelines and nf-core workflows. Use for Nextflow, nf-core, .nf files, nextflow.config, processes/channels/operators, samplesheets, nf-test, modules/subworkflows, container and executor configuration, HPC/SLURM or cloud deployment, and failed or resumed pipeline runs.
break-ai-fix-loops sickn33/antigravity-awesome-skills · score 90/100 (grade A)
Stop ineffective AI coding repair loops with stable failure fingerprints, a three-attempt budget, real-path proof, negative controls, and tested rollback.
weaviate sickn33/antigravity-awesome-skills · score 90/100 (grade A)
Search, query, inspect, create, and import data into Weaviate vector database collections using bundled adapted scripts and references.
wjttc-builder sickn33/antigravity-awesome-skills · score 90/100 (grade A)
PLAN and GENERATE WJTTC (Championship-Grade) test suites for any project. Analyzes the codebase, classifies components across the WJTTC five tiers (Brake · Engine · Aero · Tyre · Pit), writes a tiered test plan, and scaffolds executable test files.
archify tt-a1i/archify · score 89/100 (grade B)
Create validated architecture, workflow, sequence, data-flow, lifecycle/state, ERD, class, tree, timeline, and waterfall diagrams as explorable standalone HTML with dark/light themes, motion and image/SVG/WebM export. Accept requirements or Mermaid; inspect repository evidence for code-backed diagrams. Use when visualizing systems, API calls, pipelines, schemas, histories, timings, or everyday steps, parts, relationships and states. Also turn an answer into a one-page explainer, with the conclusion first, structured panels, native diagrams and charts, when the user asks for a page, an explainer or an answer to share (做成一页, 用页面讲), or proactively when the user's rules opt in with an [archify explainer: ...] line. Not for dashboards.
cucumber-skill sickn33/antigravity-awesome-skills · score 89/100 (grade B)
Generates Cucumber BDD tests with Gherkin feature files and step definitions in Java, JavaScript, or Ruby. Use when user mentions \"Cucumber\", \"Gherkin\", \"Feature/Scenario\", \"Given/When/Then\", \"BDD\".
gtm-product-led-growth github/awesome-copilot · score 89/100 (grade B)
Build self-serve acquisition and expansion motions. Use when deciding PLG vs sales-led, optimizing activation, driving freemium conversion, building growth equations, or recognizing when product complexity demands human touch. Includes the parallel test where sales-led won 10x on revenue.
spec-driven-development sickn33/antigravity-awesome-skills · score 89/100 (grade B)
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.
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.
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.
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.
github-actions sickn33/antigravity-awesome-skills · score 88/100 (grade B)
Build, test, and deploy applications using GitHub Actions workflows.
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.
newman-cicd-integration sickn33/antigravity-awesome-skills · score 88/100 (grade B)
Generate ready-to-use CI/CD pipeline configurations that install and run Newman for automated API testing.
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.
smartui-skill sickn33/antigravity-awesome-skills · score 88/100 (grade B)
Generates SmartUI visual regression test configurations for screenshot comparison on TestMu AI cloud. Framework-agnostic — works with Playwright, Selenium, Cypress, Puppeteer. Use when user mentions \"SmartUI\", \"visual regression\", \"screenshot comparison\", \"visual testing\".
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.
huggingface-tool-builder sickn33/antigravity-awesome-skills · score 87/100 (grade B)
Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated.
logic-explain sickn33/antigravity-awesome-skills · score 87/100 (grade B)
Explain what a specific piece of code actually does for a given input by producing a step-by-step execution trace (interprocedural, with name resolution and type transitions).
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.
self-improver Affitor/affiliate-skills · score 87/100 (grade B)
Review affiliate campaign results and improve strategy. Triggers on: "review my results", "what went wrong", "how to improve conversions", "analyze my campaign", "affiliate retrospective", "why am I not converting", "improve my strategy", "what should I change", "campaign review", "optimize my approach", "learn from my results", "post-mortem on my campaign".
api-designer sickn33/antigravity-awesome-skills · score 86/100 (grade B)
Generates complete, production-ready REST API endpoint specifications for any system or domain the user describes.
dast-scanning sickn33/antigravity-awesome-skills · score 86/100 (grade B)
Perform dynamic application security testing with OWASP ZAP, Burp Suite,
eas-workflows sickn33/antigravity-awesome-skills · score 86/100 (grade B)
Use when writing or reviewing Expo EAS workflow YAML: inspect current schema and job syntax, validate configuration, and separate draft edits from launching builds or submissions.
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.
fluidsim K-Dense-AI/claude-scientific-skills · score 86/100 (grade B)
Plans, configures, inspects, restarts, and analyzes bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.
glycoengineering K-Dense-AI/claude-scientific-skills · score 86/100 (grade B)
Analyzes and engineers protein glycosylation by scanning canonical N-glycosylation sequons, describing S/T-rich regions, checking curated glycan evidence, and preparing NetNGlyc, NetOGlyc and GlycoSHIELD workflows. Use for glycoprotein engineering, antibody Fc glycosylation, glycan shielding, and site-specific glycoproteomics interpretation.
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.
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.
papers-skill sickn33/antigravity-awesome-skills · score 86/100 (grade B)
Skill for academic research workflows: search Semantic Scholar (200M+ papers), inspect citations, download arXiv PDFs, and extract PDF text. Bundles a self-contained Python CLI.
pptx-deck-creation sickn33/antigravity-awesome-skills · score 86/100 (grade B)
Create editable, production-ready PPTX decks with narrative planning, explicit layout specs, asset guidance, and quality checks.
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.
swift-testing-pro twostraws/Swift-Testing-Agent-Skill · score 86/100 (grade B)
Writes, reviews, and improves Swift Testing code using modern APIs and best practices. Use when reading, writing, or reviewing projects that use Swift Testing.
testdriver-e2e-testing sickn33/antigravity-awesome-skills · score 86/100 (grade B)
Build E2E tests with TestDriver.ai, the AI code reviewer that runs every pull request in a real desktop sandbox, finds bugs, and builds regression tests
ab-test-generator Affitor/affiliate-skills · score 85/100 (grade B)
Generate A/B test variants for affiliate content. Triggers on: "create A/B test", "test my headline", "optimize my CTA", "generate variants", "split test ideas", "improve click-through rate", "test my landing page copy", "headline alternatives", "CTA variations", "which version is better", "optimize conversions", "test my email subject line", "compare approaches".
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.
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.
browser-bridge sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Inspect, control, and automate tasks in your real Microsoft Edge or Google Chrome browser via Chrome DevTools Protocol (CDP) with bilingual UI, native tab grouping, and self-healing daemon.
five-axis-code-review sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Five-axis code review checklist (correctness, security, readability, performance, test coverage) producing actionable comments instead of style nitpicks. Use when the user asks to review code, a diff, or a pull request.
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.
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.
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.
performance-optimization sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
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.
watch-igaming sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Reviews a video link or local screen recording from transcript and scene-change frames matched by timecode, then returns a review, QA table, UX audit, comparison or minutes.
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.
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.
appium-skill sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Generates production-grade Appium mobile automation scripts for Android and iOS in Java, Python, or JavaScript. Supports real device and emulator testing locally and on TestMu AI cloud with 100+ real devices.
atlas-contract sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Goal-integrity skill. Use for backend/API/persistence, preserve/do-not-change, tests/validation, mocks, rework, multi-part requests. Emits Goal Contracts, Deviation Notices, Phase Checks, Final Audits. Skip for Q&A or trivial edits.
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.
cypress-skill sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Generates production-grade Cypress E2E and component tests in JavaScript or TypeScript. Supports local execution and TestMu AI cloud. Use when the user asks to write Cypress tests, set up Cypress, test with cy commands, or mentions \"Cypress\", \"cy.visit\", \"cy.get\", \"cy.intercept\".
geo-platform-optimizer sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Platform-specific AI search optimization — audit and optimize for Google
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.
idea-refine sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one.
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.
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.
osint-investigation affaan-m/ECC · score 84/100 (grade B)
Sparse-clue OSINT investigation methodology for extracting overlooked leads, connecting fragmented evidence, and testing explanations across sources. Use for multi-step CTF challenges, image/video geolocation, event reconstruction, public-account and entity verification, artifact interpretation, infrastructure research, or stalled investigations.
osint-investigation affaan-m/everything-claude-code · score 84/100 (grade B)
Sparse-clue OSINT investigation methodology for extracting overlooked leads, connecting fragmented evidence, and testing explanations across sources. Use for multi-step CTF challenges, image/video geolocation, event reconstruction, public-account and entity verification, artifact interpretation, infrastructure research, or stalled investigations.
planning-and-task-breakdown sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
postman-openapi-converter sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Convert OpenAPI 3.x or Swagger 2.0 specs (YAML or JSON) into complete, import-ready Postman Collection v2.1 JSON files.
qiskit sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Build and transpile Qiskit circuits, test local simulators and prepare authorized hardware workloads with Sampler/Estimator primitives.
scientific-writing K-Dense-AI/claude-scientific-skills · score 84/100 (grade B)
Drafts, revises, and audits scientific manuscripts or reports with explicit evidence provenance, reporting-guideline coverage, authorship accountability, confidentiality controls, and local consistency checks. Use for manuscript sections, references, declarations, tables, figures, or submission preparation when scientific accuracy and traceability matter.
simpy K-Dense-AI/claude-scientific-skills · score 84/100 (grade B)
Builds, inspects, tests, and analyzes bounded process-based discrete-event simulations with SimPy. Use for event scheduling, resource queues, interrupts, monitoring, independent replications, warm-up, and reproducible output analysis.
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.
supercov sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Measure line, branch and MC/DC coverage of a project's existing tests with the supercov CLI, then write small, focused tests for the code no test reaches.
tdd sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
traderspy-trading-signals sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Fetch and explain TraderSpy's AI crypto futures signals: entry, take-profit ladder, stop, triggers, status against the live price, and how recent signals resolved. Use for \"latest signals\".
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.
ai-code-generation-guardrails sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Use when reviewing AI-generated code before merge or execution: plan AST/security checks, isolated behavior tests and evidence, with language-specific coverage limits.
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.
cantera K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
Runs Cantera homogeneous chemical reactors and evaluates ignition delay with mechanism provenance, conservation checks, and numerical refinement. Use for combustion kinetics, closed adiabatic ideal-gas constant-volume or constant-pressure ignition, temperature histories, or mechanism-specific ignition-delay comparisons.
cis-benchmarks sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Audit and remediate CIS benchmark violations.
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.
flowkit K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
Analyzes flow cytometry data with FlowKit, including spillover compensation, logicle and biexponential transforms, hierarchical gating, GatingML strategies, and supported FlowJo 10 workspaces. Use for reproducible gate counts, population percentages, gated fluorescence summaries, or reproducing a FlowJo analysis in Python. For FCS metadata inspection or file-format repair alone, use FlowIO.
gha-security-review sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Review GitHub Actions workflows for exploitable vulnerabilities with concrete attack paths and harmless proof-of-concept sketches. Require explicit authorization for active testing.
google-calendar-automation sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Plan and perform authorized Google Calendar workflows through an existing authenticated integration; inspect events, draft changes and verify results.
gtm-0-to-1-launch github/awesome-copilot · score 83/100 (grade B)
Launch new products from idea to first customers. Use when launching products, finding early adopters, building launch week playbooks, diagnosing why adoption stalls, or learning that press coverage does not equal growth. Includes the three-layer diagnosis, the 2-week experiment cycle, and the launch that got 50K impressions and 12 signups.
gtm-positioning-strategy github/awesome-copilot · score 83/100 (grade B)
Find and own a defensible market position. Use when messaging sounds like competitors, conversion is weak despite awareness, repositioning a product, or testing positioning claims. Includes Crawl-Walk-Run rollout methodology and the word change that improved enterprise deal progression.
hypothesis-generation K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
Formulates evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Used when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.
jest-skill sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generates Jest unit and integration tests in JavaScript or TypeScript. Covers mocking, snapshots, async testing, and React component testing. Use when user mentions \"Jest\", \"describe/it/expect\", \"jest.mock\", \"toMatchSnapshot\".
junit-5-skill sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generates production-grade JUnit 5 unit and integration tests in Java. Covers assertions, parameterized tests, lifecycle hooks, mocking with Mockito, and nested tests. Use when user mentions \"JUnit\", \"JUnit 5\", \"@Test\", \"assertEquals\", \"Assertions\", \"Java unit test\".
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.
omero-integration K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
Inspects and automates microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs. Use this skill for scoped OMERO inventory, metadata export, import/export planning, or reviewed write workflows.
openapi-spec-generator sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generate complete, production-ready OpenAPI 3.x and Swagger 2.0 specifications from natural language descriptions, code, or partial specs.
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.
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.'
proprietary-data-generator Affitor/affiliate-skills · score 83/100 (grade B)
Create original surveys, benchmarks, and aggregated data nobody else has. Automate data collection for content moats. Triggers on: "create original data", "proprietary data", "survey design", "benchmark study", "original research", "data-driven content", "create a survey", "industry benchmark", "aggregated data", "unique data", "first-party data", "data moat", "generate research data", "create a study", "original statistics", "data nobody else has", "competitive data advantage".
pytest-skill sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generates production-grade pytest tests in Python with fixtures, parametrize, markers, mocking, and conftest patterns. Use when user mentions \"pytest\", \"conftest\", \"@pytest.fixture\", \"@pytest.mark\", \"Python test\".
robot-framework-skill sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generates Robot Framework tests in keyword-driven syntax with Python. Supports SeleniumLibrary, RequestsLibrary, and custom keywords. Use when user mentions \"Robot Framework\", \"*** Test Cases ***\", \"SeleniumLibrary\", \".robot file\".
selenium-skill sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generates production-grade Selenium WebDriver automation scripts and tests in Java, Python, JavaScript, C#, Ruby, or PHP. Supports local execution and TestMu AI cloud with 3000+ browser/OS combinations.
tdd-workflows-tdd-red sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Generate failing tests for the TDD red phase to define expected behavior and edge cases.
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.
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.
api-contract-testing sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Design and review API contract tests across providers and consumers. Use for schema changes, compatibility regressions and client integration failures.
ci-cd-and-automation sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
e2e-testing-patterns sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Build reliable, fast, and maintainable end-to-end test suites that provide confidence to ship code quickly and catch regressions before users do.
executive-mentor alirezarezvani/claude-skills · score 82/100 (grade B)
Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for brutal board meetings, dissects decisions with no good options, and forces honest post-mortems. Use when you need someone to find the holes before the board does, make a decision you've been avoiding, or understand what actually went wrong.
geo-prospect sickn33/antigravity-awesome-skills · score 82/100 (grade B)
CRM-lite for managing GEO agency prospects and clients.
glasser sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Search, inspect, and run third-party data APIs through one CLI when the environment has no suitable integration.
histolab K-Dense-AI/claude-scientific-skills · score 82/100 (grade B)
Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset preparation. For multiplexed imaging or deep learning inference pipelines, use pathml.
hyperexecute-skill sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Operates HyperExecute end-to-end for TestMu AI/LambdaTest cloud test execution: analyze projects, create YAML, validate locally, run CLI jobs, debug failures, and wire CI.
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.
laravel-development-workflow sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Build and fix existing Laravel applications through root-cause diagnosis, repository-native implementation, regression coverage, and risk-based verification.
mageck K-Dense-AI/claude-scientific-skills · score 82/100 (grade B)
Analyzes pooled CRISPR screen FASTQ reads and guide-count matrices with MAGeCK, validates guide libraries and contrasts, measures replicate and library QC, and produces gene hit rankings with effect sizes and FDR. Use for new knockout, CRISPRi, or CRISPRa screen analysis, enrichment or depletion contrasts, and MAGeCK count/test workflows; existing public dependency-score lookup belongs to DepMap.
matlab K-Dense-AI/claude-scientific-skills · score 82/100 (grade B)
Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
mirrord sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Run a local process inside a live Kubernetes cluster's network, env and traffic with mirrord, so changes are tested against real services without deploying.
post sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Make share-post image sets that look native: Xiaohongshu carousels, X images, covers, App Store poster layouts, real screenshots and faithful app-UI mocks. Use for 图文, 配图, 组图, 封面, 分享帖.
prd github/awesome-copilot · score 82/100 (grade B)
Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.
public-relations sickn33/antigravity-awesome-skills · score 82/100 (grade B)
When the user wants help with public relations, earned media, press coverage, journalist outreach, or media strategy (not pull requests).
sast-scanning sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Perform static application security testing with tools like Semgrep,
semgrep-rule-variant-creator sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Creates language variants of existing Semgrep rules. Use when porting a Semgrep rule to specified target languages. Takes an existing rule and target languages as input, produces independent rule+test directories for each language.
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.
test-framework-migration-skill sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Migrates and converts test automation scripts between Selenium, Playwright, Puppeteer, and Cypress.
test-gap-audit github/awesome-copilot · score 82/100 (grade B)
Run a read-only audit for missing, weak, stale, or mis-scoped test coverage. If the user does not name a scope, audit the full repository and identify important code paths, routes, features, services, workflows, and contracts that lack proper tests. If the user names a feature, PR, branch, route, workflow, service, bug fix, API, security-sensitive path, or risky code change, focus only on that specific scope. Use when the user asks what tests are missing, whether coverage is enough, what regression tests to add, or how to prove a change is safe. This is not a general bug audit and not a security review; it evaluates whether behavior is covered by tests.
vibers-code-review sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Human review workflow for AI-generated GitHub projects with spec-based feedback, security review, and follow-up PRs from the Vibers service.
ab-test-setup sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Use when designing an A/B or split test: define the hypothesis, control and variants, estimate sample size, verify tracking, and predeclare metrics and stopping rules.
ad-creative sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.
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.
analytical-method-validation K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
Plans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.
browser-extension-launch sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Builds, tests, packages, and prepares Chrome extensions for store launch from a plain-language idea; use for new extensions, fixes, releases, and submission recovery.
chaos-engineering alirezarezvani/claude-skills · score 81/100 (grade B)
Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question. Ships experiment designer, blast-radius calculator, and postmortem generator (all stdlib Python), 4 references on chaos principles + experiment design + attack taxonomy + tooling landscape, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (common chaos targets).
codebase-design sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
comprehensive-review-pr-enhance sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Generate structured PR descriptions from diffs, add review checklists, risk assessments, and test coverage summaries. Use when the user says "write a PR description", "improve this PR", "summarize my changes", "PR review", "pull request", or asks to document a diff for reviewers.
debugging-code sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Interactively debug source code — set breakpoints, step through execution line by line, inspect live variable state, evaluate expressions against the running program, and navigate the call stack to trace root causes.
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.
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.
gget K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
Queries 20+ bioinformatics resources through CLI/Python. Supports quick lookups of gene info, BLAST/BLAT, viral sequence downloads, PDB/mmCIF structures, G2P residue annotations, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, and 8cube mouse specificity/expression data. Best for interactive exploration and simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
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.
i-have-adhd ayghri/i-have-adhd · score 81/100 (grade B)
Shape output for a reader with ADHD: lead with the next action, number multi-step work, restate state across turns, suppress tangents, give specific time estimates, make wins visible. Invoke with /i-have-adhd; stays on until "stop adhd mode".
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.
linux-hardening sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Apply CIS benchmarks and secure Linux servers.
liuguang-banlan-ui sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Builds two parameterized UI modes—流光溢彩白 (iridescent white) and 五彩斑斓黑 (colorful black)—with OKLCH, WebGL/CSS fallback, vision gating, screenshot QA, and total/per-color intensity reports. Use when a UI request names either mode or needs measured color parameters.
marine-carbonate-chemistry K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
Solves seawater carbonate chemistry with PyCO2SYS for chemical oceanography, ocean acidification, and marine carbon-cycle research. Use for paired total alkalinity, dissolved inorganic carbon, pH, or seawater pCO2/fCO2 measurements; carbonate speciation; aragonite and calcite saturation; Revelle factors; lab-to-in-situ temperature and pressure corrections; and measurement uncertainty propagation. Applies to carbonate-system calculations, not general aqueous speciation or air-sea gas-flux estimation.
marketing-mindset sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Use when a user asks how to win first customers, whether doing X will produce Y, how to write an ad or judge a marketing test — a marketer's decision framework, not a tactic library.
model-supply-chain-security sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Secure the AI model supply chain with artifact signing, provenance attestation,
nextjs-seo-indexing sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Fix SEO indexing issues, crawl budget problems, and Search Console coverage errors for Next.js apps. Covers canonical tags, noindex audits, sitemap health, static rendering, and internal linking.
purple-cow-audit Affitor/affiliate-skills · score 81/100 (grade B)
Score product remarkability 1-10 to decide if it's worth promoting. Seth Godin's Purple Cow test. Triggers on: "is this product worth promoting", "should I promote", "product audit", "purple cow", "remarkable product", "is it remarkable", "rate this product", "product quality check", "worth my reputation", "product evaluation", "would I recommend without commission", "product remarkability score", "evaluate this affiliate product", "quality gate for promotion".
pydeseq2 K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
Performs bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.
pydicom K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
Reads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
recon-scope-triage sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Triage ASM/recon output for ownership before testing
redis-cli sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Redis command-line interface (redis-cli) reference and usage guide. Use this skill whenever the user mentions redis-cli, Redis CLI, or any task involving querying, inspecting, debugging, or managing Redis from the command line.
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.
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.
squirrel sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.
terraform-skill antonbabenko/terraform-skill · score 81/100 (grade B)
Use when writing, reviewing, or debugging Terraform/OpenTofu modules, tests, CI, scans, or state ops - diagnoses failure mode (identity churn, secrets, blast radius, CI drift, state corruption) with version-aware guards.
traderspy-market-screener sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Scan the most-traded crypto futures pairs for up to 3 technical conditions in one TraderSpy call, compare coins, and backtest what followed a condition. Use for \"which coins are oversold\".
trending-content-scout Affitor/affiliate-skills · score 81/100 (grade B)
Scan social platforms for top-performing content by engagement before you create anything. Use this skill when the user wants to see what content is winning in a niche, find viral content patterns, research what's working on YouTube/TikTok/X/Reddit, benchmark engagement, discover content gaps, or says "what content is working for [topic]", "show me top performing content about [keyword]", "what's trending in [niche]", "find viral content about [product]", "content research for [keyword]", "what gets views in [niche]", "engagement analysis for [topic]", "scout the competition", "what videos are getting the most views about [keyword]", "social listening for [topic]", "trending content in [niche]", "top content analysis", "what hooks work for [keyword]", "content intelligence", "find winning formats".
vitest-skill sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Generates Vitest tests in JavaScript/TypeScript with Vite-native speed. Jest-compatible API with ESM support and HMR. Use when user mentions "Vitest", "vi.mock", "vitest.config". Triggers on: "Vitest", "vi.mock", "vi.fn", "Vite test", "vitest config".
webdriverio-skill sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Generates WebdriverIO (WDIO) automation tests in JavaScript or TypeScript. Supports local and TestMu AI cloud. Use when user mentions "WebdriverIO", "WDIO", "wdio.conf", "browser.url", "$", "$$". Triggers on: "WebdriverIO", "WDIO", "wdio", "browser.$".
writing-plans sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Use when you have a spec or requirements for a multi-step task, before touching code
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.
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.
ai-loop sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
ask-human-expert sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Ask real executives and domain experts a question through Instant Expert for a written answer or short call: practitioner knowledge, customer discovery. Free test mode; live sends need approval.
azure-microsoft-playwright-testing-ts sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Run Playwright tests at scale with cloud-hosted browsers and integrated Azure portal reporting.
azure-resource-manager-playwright-dotnet sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Azure Resource Manager SDK for Microsoft Playwright Testing in .NET.
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.
ci-fix warpdotdev/oz-skills · score 80/100 (grade B)
Diagnose and fix GitHub Actions CI failures. Inspects workflow runs and logs, identifies root causes, implements minimal fixes, and pushes to a fix branch. Use when CI is failing, red, broken, or needs diagnosis.
cli-creator openai/skills · score 80/100 (grade B)
Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read/write commands, return stable JSON, manage auth, and pair with a companion skill.
conductor-new-track sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Create a new track with specification and phased implementation plan
content-creator sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Draft and review audience-specific content using supplied brand examples, local text diagnostics, and adaptable channel templates.
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.
dataverse-python-usecase-builder github/awesome-copilot · score 80/100 (grade B)
Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations
docs-generator sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Generate technical deliverables from completed analysis: reverse-engineering reports, penetration-test reports, CTF write-ups, and signature-analysis documentation with evidence-backed structure.
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.
fictiv K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Operates Fictiv (app.fictiv.com), the on-demand manufacturing platform, end to end in the user's browser. Covers uploading CAD parts, configuring process, material, finish, threads, tolerances and inspections, getting instant or manual quotes, reading and fixing DFM feedback, choosing lead time and region, checking out and paying (card or PO), tracking orders, reordering, and troubleshooting. Applies when the user mentions Fictiv, wants a part CNC machined, 3D printed, sheet-metal fabricated, urethane cast, injection or compression molded, or die cast through an online service, asks to "get a quote" or "order parts" for a STEP/SLDPRT/STL file, wants to check a Fictiv quote or order status, or has a problem with a Fictiv upload, DFM warning, price or checkout. Also applies when the user wants custom parts manufactured and has a Fictiv account, even if Fictiv is not named.
github-actions-debugger sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Specialized skill for diagnosing, analyzing, and fixing failing GitHub Actions workflows by parsing run logs and pipeline definitions.
grill-with-docs alirezarezvani/claude-skills · score 80/100 (grade B)
Docs-anchored grilling session — challenges a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), and updates those files inline as terminology and decisions crystallise. Use when user wants to stress-test a plan against documented domain language, or mentions "grill with docs".
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
idor-testing sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Provide systematic methodologies for identifying and exploiting Insecure Direct Object Reference (IDOR) vulnerabilities in web applications.
network-101 sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Configure and test common network services (HTTP, HTTPS, SNMP, SMB) for penetration testing lab environments. Enable hands-on practice with service enumeration, log analysis, and security testing against properly configured target systems.
nmrglue K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Processes calibrated one-dimensional complex NMR free-induction decays with nmrglue into phased spectra, peak candidates, and signed integration regions. Use for raw 1D NMR processing, ppm-axis verification, apodization, Fourier transformation, manual phasing, baseline correction, or reproducible spectral integration.
obsidian-markdown sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax. Use when working with .md files in Obsidian, or when the user mentions wikilinks, callouts, frontmatter, tags, embeds, or Obsidian notes.
opentrons-integration K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Authors, reviews, migrates, simulates, and troubleshoots official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots. Use for robot-specific liquid handling, deck and labware setup, pipettes, modules, runtime parameters, liquid classes, and Opentrons App analysis. Use pylabrobot instead when one workflow must support multiple robot vendors.
pathway-enrichment K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Performs pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".
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.
pytdc K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Provides Therapeutics Data Commons workflows through PyTDC for registry discovery, dataset access, task-aware splits, evaluator metrics, benchmark groups, and bounded molecular-oracle scoring. Use when working with TDC therapeutic ML datasets or benchmarks.
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'.
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.
sbom-supply-chain sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Generate, sign, and verify SBOMs and provenance attestations to secure
scrum-master alirezarezvani/claude-skills · score 80/100 (grade B)
Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports, and improvement-velocity trends for high-performing Scrum teams.
shodan-reconnaissance sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Provide systematic methodologies for leveraging Shodan as a reconnaissance tool during penetration testing engagements.
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.
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.
systematic-debugging sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
test-driven-development obra/superpowers · score 80/100 (grade B)
Use when implementing any feature or bugfix, before writing implementation code
test-driven-development sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Use a failing behavioral test to guide a feature or bug fix, then implement and refactor with relevant regression checks.
test-guard sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Review generated or changed test code against universal testing rules before it ships or is presented for approval.
uniprot-database sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
what-if-oracle K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Supports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.
ab-test-setup alirezarezvani/claude-skills · score 79/100 (grade C)
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.
ab-testing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program.
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.
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".
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.
ask-questions-if-underspecified sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Clarify requirements before implementing. Use when serious doubts arise.
autoresearch github/awesome-copilot · score 79/100 (grade C)
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy''s autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
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.
backend-security-coder sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Expert in secure backend coding practices specializing in input validation, authentication, and API security. Use PROACTIVELY for backend security implementations or security code reviews.
bash-scripting sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Bash scripting workflow for creating production-ready shell scripts with defensive patterns, error handling, and testing.
brooks-sweep sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution.
browser-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Build reliable browser checks using observed UI state, semantic locators, bounded waits, isolated test data and explicit outcome verification.
calibrate-first sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Measure a dataset's detection floor before reading any trading-signal result, pre-register every test, and report too-small-to-see as UNDECIDABLE, not 'no effect'.
case-review sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Quality-gate review of a reverse-engineering or assessment case package: scope readiness, Evidence-to-Finding-to-Path traceability, work-item coverage, timeline consistency, and artifact hashes.
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.
cloud-penetration-testing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Conduct comprehensive security assessments of cloud infrastructure across Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP).
code-showcase-testing-patterns sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Jest testing patterns, factory functions, mocking strategies, and TDD workflow. Use when writing unit tests, creating test factories, or following TDD red-green-refactor cycle.
cold-email sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Write B2B cold emails and follow-up sequences that earn replies. Use when creating outbound prospecting emails, SDR outreach, personalized opening lines, subject lines, CTAs, and multi-touch follow-up sequences.
content-research-brief Affitor/affiliate-skills · score 79/100 (grade C)
Research trending topics, collect source articles, and generate a structured research brief for content creation. Stop writing from thin air — write from real sources. Use this skill when the user wants to research a topic before writing, collect sources for an article, create a research-backed content brief, or says "research [topic] for me", "find sources about [keyword]", "content brief for [topic]", "what's the latest on [product]", "research before writing", "collect articles about [keyword]", "trending news about [topic]", "gather sources for my article", "brief me on [topic]", "what are people saying about [product]", "news roundup for [keyword]", "research brief", "source collection", "content research", "prep research for writing".
csharp-pro sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Write modern C# code with advanced features like records, pattern matching, and async/await. Use for version-compatible .NET implementation and evidence-based testing/performance review.
ctr-predictor sickn33/antigravity-awesome-skills · score 79/100 (grade C)
CTR Predictor. Use when working with impressions and an explicitly supplied CTR assumption or historical benchmark.
cypress-flake-fixer github/awesome-copilot · score 79/100 (grade C)
Find and fix flake-prone anti-patterns in an existing Cypress suite, and APIs removed in Cypress 12 to 16. Bundles a zero-dependency scanner for fixed cy.wait() delays, assigned command return values, async/await, force: true, chaining after actions, one-shot expect() inside .then(), conditional testing, and removed APIs such as Cypress.env(), cy.exec(), cy.server()/cy.route(). Use when asked to fix flaky Cypress tests, remove cy.wait, stabilize or harden a Cypress suite, audit Cypress specs, debug "detached from the DOM" errors, or prepare an upgrade to Cypress 15 or 16.
debugging-and-error-recovery sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
design-system nextlevelbuilder/ui-ux-pro-max-skill · score 79/100 (grade C)
Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.
fsi-compliance-checker sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Maps code, architecture, and infrastructure changes to specific control IDs in PCI-DSS v4.0.1 and MAS TRM (Singapore financial regulator), producing an audit-traceable findings report with per-control remediation.
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.
get-available-resources K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Detects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.
github-actions-templates sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Production-ready GitHub Actions workflow patterns for testing, building, and deploying applications.
guest-posting-opportunity-finder sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Guest Posting Opportunity Finder. Use when working with topic, audience and optional prospect list.
http-status-code-tester sickn33/antigravity-awesome-skills · score 79/100 (grade C)
HTTP Status Code Tester. Use when working with one or more HTTP(S) URLs.
hunt-nextjs sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Hunt Next.js specific vulnerabilities
k6-load-testing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Comprehensive k6 load testing skill for API, browser, and scalability testing. Write realistic load scenarios, analyze results, and integrate with CI/CD.
linkedin-content-generator sickn33/antigravity-awesome-skills · score 79/100 (grade C)
AI-powered LinkedIn content suite: generate posts, carousels, newsletters, and 30-day calendars with niche-specific SEO rules and a feedback-based personal memory system.
matchms K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Processes, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
mobile-friendly-test sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Mobile-Friendly Test. Use when working with accessible page or supplied screenshots and HTML.
ncats-arax K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.
pathogen-variant-surveillance K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.
privilege-escalation-methods sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Provide comprehensive techniques for escalating privileges from a low-privileged user to root/administrator access on compromised Linux and Windows systems. Essential for penetration testing post-exploitation phase and red team operations.
pymoo K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Solves and validates single-, multi-, and many-objective optimization with pymoo, including NSGA-II, NSGA-III, MOEA/D, constraints, Pareto approximations, reference directions, and ZDT/DTLZ benchmarks for engineering and research problems.
pysam K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Provides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.
quarkus-verification affaan-m/ECC · score 79/100 (grade C)
Verification loop for Quarkus projects: build, static analysis (Checkstyle, PMD, SpotBugs), tests with JaCoCo coverage, OWASP dependency and container security scans, GraalVM native compilation, health checks, and config validation. Use when verifying a Quarkus service before a PR, after major refactoring or dependency upgrades, or pre-deploy.
quarkus-verification affaan-m/everything-claude-code · score 79/100 (grade C)
Verification loop for Quarkus projects: build, static analysis (Checkstyle, PMD, SpotBugs), tests with JaCoCo coverage, OWASP dependency and container security scans, GraalVM native compilation, health checks, and config validation. Use when verifying a Quarkus service before a PR, after major refactoring or dependency upgrades, or pre-deploy.
robots-txt-validator sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Robots.txt Validator. Use when working with robots.txt text, crawler and URLs to test.
screenshots sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Generate marketing screenshots of your app using Playwright. Use when the user wants to create screenshots for Product Hunt, social media, landing pages, or documentation.
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.
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.
slo-architect alirezarezvani/claude-skills · score 79/100 (grade C)
Use when defining, reviewing, or operating SLOs/SLIs/error budgets. Triggers on "define an SLO", "what should our SLO be", "error budget", "burn rate", "SLI", "service level objective", "Google SRE workbook", "multi-window burn-rate alert", or any reliability-target question. Ships SLO designer, error-budget calculator with multi-window burn-rate thresholds, and SLO reviewer that catches the common bugs (target too aggressive, window too short, conflicting SLOs, no SLI definition). 4 references on SLO principles + SLI design + error budget math + composition with feature-flags-architect/chaos-engineering/kubernetes-operator. NOT a generic observability skill — specifically the SLO discipline.
ssh-penetration-testing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Conduct comprehensive SSH security assessments including enumeration, credential attacks, vulnerability exploitation, tunneling techniques, and post-exploitation activities. This skill covers the complete methodology for testing SSH service security.
testng-skill sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Generates TestNG tests in Java with groups, data providers, parallel execution, XML suite configuration, and listeners. Use when user mentions "TestNG", "@DataProvider", "testng.xml", "groups". Triggers on: "TestNG", "@DataProvider", "testng.xml", "TestNG suite", "parallel tests Java".
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.
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.
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.
vibecode-production-qa-validator sickn33/antigravity-awesome-skills · score 79/100 (grade C)
13-phase production QA for fullstack Next.js apps: build verification, SEO tags, OG images, favicon, route regression, API auth, page speed, lazy load, vulnerability scan, UI/UX cards, error boundaries, database, secure rendering, and cleanup.
web-security-testing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Web application security testing workflow for OWASP Top 10 vulnerabilities including injection, XSS, authentication flaws, and access control issues.
wordpress-penetration-testing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Assess WordPress installations for common vulnerabilities and installed core/plugin REST permission boundaries.
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.
android-ui-journey-testing sickn33/antigravity-awesome-skills · score 78/100 (grade C)
XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.
api-fuzzing-bug-bounty sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
api-security sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Authorized security assessment of REST, GraphQL, WebSocket, and SOAP APIs: discovery, authentication and authorization flaws (BOLA/IDOR, JWT/OAuth), rate-limit testing, and a structured multi-phase methodology.
asc-xcode-build rudrankriyam/app-store-connect-cli-skills · score 78/100 (grade C)
Build, archive, export, and manage Xcode version/build numbers with asc, including portable iOS compilation and packaging. Use when creating an IPA or PKG for App Store Connect, TestFlight, or registered-device release testing.
awt-e2e-testing sickn33/antigravity-awesome-skills · score 78/100 (grade C)
AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g
baoyu-cover-image JimLiu/baoyu-skills · score 78/100 (grade C)
Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
build-evidence-map github/awesome-copilot · score 78/100 (grade C)
Build an auditable evidence map for a contested technical choice, research synthesis, proposal review, or consequential decision. Use when Copilot must preserve supporting, contradicting, qualifying, and missing evidence with exact source regions instead of collapsing disagreement into prose.
clinical-research alirezarezvani/claude-skills · score 78/100 (grade C)
Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (ISO 13485, EU MDR, FDA 510(k)/PMA/QSR), not the study design.
code-review-ai-ai-review sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Review pull requests with source inspection, available static analysis and evidence-backed AI assistance; report actionable bugs, security risks and unverified coverage.
commit sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Prepare or create commits using Sentry-style message conventions when the repository requests them; inspect staged scope and honor its protected branch workflow.
crossframe-debate sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Use when CrossFrame Suite routes explicit Chinese proposition testing, debate analysis, hidden-premise review, rebuttal design, or withdrawal condition checks.
debugger sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Debugging specialist for errors, test failures, and unexpected
deep-scrape davidondrej/skills · score 78/100 (grade C)
Build sourced JSON dossiers on people, companies, or topics with DeepAPI. Use for profiles, prospects, vendor due diligence, or customer research across sources; use deep-research for recommendations.
deterministic-design sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Measure rendered UI layout with reproducible spatial metrics and a separately assessed usability review; distinguish measurements from subjective judgments and user tests.
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.
doc-coauthoring Galaxy-Dawn/claude-scholar · score 78/100 (grade C)
This skill should be used when the user asks to co-author documentation, draft a proposal, write a technical spec, create a decision doc or RFC, or structure a substantial document through iterative collaboration and reader testing.
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.
ethical-hacking-methodology sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Master the complete penetration testing lifecycle from reconnaissance through reporting. This skill covers the five stages of ethical hacking methodology, essential tools, attack techniques, and professional reporting for authorized security assessments.
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.
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.
exploratory-data-analysis K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.
file-organizer sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Organize files and folders by inspecting their contents, proposing a structure, and reviewing duplicates before authorized changes.
flowio K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Reads, inspects, and writes Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO. Use for low-level FCS metadata and channel inspection, NumPy event extraction, multi-dataset files, table export, and FCS 3.1 creation; use FlowKit for compensation, cytometry transforms, gating, or FlowJo workspaces.
frontend-design-direction affaan-m/ECC · score 78/100 (grade C)
Set an ECC-specific frontend design direction for production UI work. Use when building or improving websites, dashboards, applications, components, landing pages, visual tools, or any web UI that needs stronger product-specific design judgment.
frontend-design-direction affaan-m/everything-claude-code · score 78/100 (grade C)
Set an ECC-specific frontend design direction for production UI work. Use when building or improving websites, dashboards, applications, components, landing pages, visual tools, or any web UI that needs stronger product-specific design judgment.
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.
gitlab-ci-patterns sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Comprehensive GitLab CI/CD pipeline patterns for automated testing, building, and deployment.
google-cloud-filestore-nfs-browser google/skills · score 78/100 (grade C)
Inspects, searches, and reads files and POSIX metadata on Filestore (NFS) instances on Google Cloud without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.
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.
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.
iso-standards-readiness K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Prepares and structurally reviews readiness evidence for ISO management-system and laboratory-competence standards - ISO 13485 medical device QMS, ISO 14971 device risk management, ISO/IEC 17025 testing and calibration laboratories, and ISO 15189 medical laboratories. Use when organizing declared scope, controlled documents, risk-management files, scope of accreditation, traceability, CAPA, external-provider controls, or bounded local evidence manifests, and when separating ISO certification from laboratory accreditation, FDA QMSR inspection, CLIA certification, MDSAP, and EU MDR/IVDR evidence boundaries. Not for legal applicability, compliance, certification, or accreditation decisions; contains no clause text.
literature-review K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Conducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.
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.
longbridge-content sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Latest news articles, regulatory filings, community discussion topics for listed stocks, and SEC EDGAR filing analysis (10-K/10-Q/8-K/proxy/Form 4) via Longbridge.
master-agreement-generator affaan-m/ECC · score 78/100 (grade C)
Generate review drafts of counterparty master agreements from one template plus a JSON spec, with role-selected clauses and a Schedule A workflow limited to the executed agreement's notice authority. Use when you need reproducible drafting and separately reviewed execution preparation.
master-agreement-generator affaan-m/everything-claude-code · score 78/100 (grade C)
Generate review drafts of counterparty master agreements from one template plus a JSON spec, with role-selected clauses and a Schedule A workflow limited to the executed agreement's notice authority. Use when you need reproducible drafting and separately reviewed execution preparation.
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.
mobile-reverse sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Authorized Android/iOS application reverse engineering and security testing: APK/IPA analysis, runtime instrumentation (Frida/Objection), SSL-pinning and jailbreak/root-detection bypass, per OWASP MASTG.
nwb-conversion K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Converts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel two-photon TIFF imaging plus timestamped behavioral position CSV; this skill does not perform spike sorting or claim tested support for arbitrary acquisition formats.
onekgpd K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Queries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region, which individuals are homozygous-reference at a position, which variants exist in the dataset or carried by specified individuals in a gene or region, the relatedness between two specified individuals. Variants are returned with 1000 Genomes allele frequencies (AF), gnomAD v4.1 exome and genome AF, AlphaMissense score, and HGVSp annotations.
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.
pentest-checklist sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Provide a comprehensive checklist for planning, executing, and following up on penetration tests. Ensure thorough preparation, proper scoping, and effective remediation of discovered vulnerabilities.
performance-testing-review-ai-review sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Review performance-sensitive code changes with reproducible baselines, workload metrics, static analysis and evidence-backed findings.
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.
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.
primer-design K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Designs and audits PCR and RT-qPCR primers with Primer3, explicit thermodynamic conditions, reference-based off-target amplification searches, and traceable sequence coordinates. Use for designing primer pairs, checking existing primers, exon-junction or isoform-specific assays, variant masking, cloning tails, multiplex compatibility, and interpreting Primer-BLAST results. Includes bounded local in-silico PCR and BLAST screening; distinguishes computational candidates from experimentally validated assays.
pw-init alirezarezvani/claude-skills · score 78/100 (grade C)
Set up Playwright in a project. Use when user says "set up playwright", "add e2e tests", "configure playwright", "testing setup", "init playwright", or "add test infrastructure".
pyopenms K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Processes mass spectrometry data with pyOpenMS. Supports proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.
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.
returns-reverse-logistics affaan-m/ECC · score 78/100 (grade C)
Codified expertise for returns authorization, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management. Informed by returns operations managers with 15+ years experience. Includes grading frameworks, disposition economics, fraud pattern recognition, and vendor recovery processes. Use when handling product returns, reverse logistics, refund decisions, return fraud detection, or warranty claims.
returns-reverse-logistics affaan-m/everything-claude-code · score 78/100 (grade C)
Codified expertise for returns authorization, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management. Informed by returns operations managers with 15+ years experience. Includes grading frameworks, disposition economics, fraud pattern recognition, and vendor recovery processes. Use when handling product returns, reverse logistics, refund decisions, return fraud detection, or warranty claims.
returns-reverse-logistics sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Codified expertise for returns authorisation, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management.
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.
search-specialist sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Research questions with focused web searches, primary-source verification, and explicit evidence gaps.
smtp-penetration-testing sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Conduct comprehensive security assessments of SMTP (Simple Mail Transfer Protocol) servers to identify vulnerabilities including open relays, user enumeration, weak authentication, and misconfiguration.
spec-driven-workflow alirezarezvani/claude-skills · score 78/100 (grade C)
Use when the user asks to write specs before code, define acceptance criteria, plan features before implementation, generate tests from specifications, or follow spec-first development practices.
sqlmap-database-pentesting sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Provide systematic methodologies for automated SQL injection detection and exploitation using SQLMap.
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.
temporal-python-testing sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.
test-value tt-a1i/archify · score 78/100 (grade C)
Improve test value and feedback cost when auditing slow, flaky, redundant or brittle tests; choosing tests during implementation; or reviewing test changes before a commit or PR. Keep ordinary implementation and pre-commit use scoped to the affected behavior, not a repository-wide audit.
testrail alirezarezvani/claude-skills · score 78/100 (grade C)
Sync tests with TestRail. Use when user mentions "testrail", "test management", "test cases", "test run", "sync test cases", "push results to testrail", or "import from testrail".
to-issues sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Break a plan, spec, or PRD into independently-grabbable issues on the project issue tracker using tracer-bullet vertical slices.
uncertainty-and-units K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Tracks physical units and propagates measurement uncertainty in scientific calculations using pint and uncertainties. Use for unit conversion and dimensional checking, GUM uncertainty budgets, Type A and Type B evaluation, coverage factors and expanded uncertainty, Monte Carlo propagation, significant-figure and plus-minus reporting, error propagation through curve fits, CODATA constants, auditing Python code for stripped units or broken uncertainty propagation, and order-of-magnitude plausibility checks using dimensionless groups (Reynolds, Peclet, Damkohler, Knudsen, Biot, Womersley), characteristic scales such as diffusion time or Debye length, and observed magnitude ranges. Trigger on "is this number physically reasonable", "sanity check these units", "what regime is this flow in", or a result that looks off by orders of magnitude.
understand-project-yylo sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Inspect the current product architecture, dependencies, and validation
windows-hardening sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Harden Windows servers per security baselines and CIS benchmarks. Configure
windows-privilege-escalation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Provide systematic methodologies for discovering and exploiting privilege escalation vulnerabilities on Windows systems during penetration testing engagements.
wjttc-tester sickn33/antigravity-awesome-skills · score 78/100 (grade C)
F1-inspired test EXECUTOR + reporter. Runs a test plan, finds and reproduces bugs, audits suite signal integrity, then files a WJTTC report (Brake/Engine/Aero/Tyre/Pit) with a tier verdict.
agent-squad sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Main agent orchestrator that coordinates a specialized squad of agents
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.
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.
angular-developer affaan-m/ECC · score 77/100 (grade C)
Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.
angular-developer affaan-m/everything-claude-code · score 77/100 (grade C)
Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.
antithesis-research antithesishq/antithesis-skills · score 77/100 (grade C)
Analyze a codebase to figure out how it should be tested with Antithesis: map the system, identify failure-prone areas and testable properties, and produce the research artifacts needed for workload and environment planning.
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.
api-security-testing sickn33/antigravity-awesome-skills · score 77/100 (grade C)
API security testing workflow for REST and GraphQL APIs covering authentication, authorization, rate limiting, input validation, and security best practices.
api-test-suite-builder alirezarezvani/claude-skills · score 77/100 (grade C)
Use when the user asks to generate API tests, create integration test suites, test REST endpoints, or build contract tests.
application-design-center-design-deploy google/skills · score 77/100 (grade C)
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.
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.
benchmark-methodology affaan-m/ECC · score 77/100 (grade C)
Score a scoped competitor set into comparable profile cards: nine weighted dimensions (positioning, voice, visual craft, offer packaging, evidence, enterprise-readiness, thought leadership, pricing, client tension) with 1-5 evidence-anchored rubrics and a tension 2x2 plot. Use when benchmarking or scoring competitors, building a competitive comparison matrix, or grading rival positioning before assembling the report; runs after competitive-platform-analysis and before competitive-report-structure.
benchmark-methodology affaan-m/everything-claude-code · score 77/100 (grade C)
Score a scoped competitor set into comparable profile cards: nine weighted dimensions (positioning, voice, visual craft, offer packaging, evidence, enterprise-readiness, thought leadership, pricing, client tension) with 1-5 evidence-anchored rubrics and a tension 2x2 plot. Use when benchmarking or scoring competitors, building a competitive comparison matrix, or grading rival positioning before assembling the report; runs after competitive-platform-analysis and before competitive-report-structure.
benchmark-optimization-loop affaan-m/ECC · score 77/100 (grade C)
Convert 'make it faster' requests into a bounded measured optimization loop — baseline first, generate one-hypothesis variants, benchmark each against a correctness gate, and promote the fastest safe variant with reproducible commands. Use when asked to speed something up, try many variants, run recursive optimization, benchmark latency/throughput/cost, or pick the best implementation by repeated measured tests.
benchmark-optimization-loop affaan-m/everything-claude-code · score 77/100 (grade C)
Convert 'make it faster' requests into a bounded measured optimization loop — baseline first, generate one-hypothesis variants, benchmark each against a correctness gate, and promote the fastest safe variant with reproducible commands. Use when asked to speed something up, try many variants, run recursive optimization, benchmark latency/throughput/cost, or pick the best implementation by repeated measured tests.
brand-kit-print-collateral sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Print collateral spec: item, finished/trim size and artwork size including bleed, bleed, colour mode, stock and GSM, finish, safe margin, print method, quantity and unit cost. Use for cards and letterhead.
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.
brooks-test sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Review test-suite quality using established testing literature; identify brittleness, mock abuse, unclear fixtures, weak assertions, slow feedback, and maintenance risks.
browserstack alirezarezvani/claude-skills · score 77/100 (grade C)
Run tests on BrowserStack. Use when user mentions "browserstack", "cross-browser", "cloud testing", "browser matrix", "test on safari", "test on firefox", or "browser compatibility".
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.
code-showcase-systematic-debugging sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.
cpp-testing affaan-m/ECC · score 77/100 (grade C)
Use only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.
cpp-testing affaan-m/everything-claude-code · score 77/100 (grade C)
Use only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.
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.
dependency-upgrade sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Master major dependency version upgrades, compatibility analysis, staged upgrade strategies, and comprehensive testing approaches.
doc-coauthoring sickn33/antigravity-awesome-skills · score 77/100 (grade C)
This skill provides a structured workflow for guiding users through collaborative document creation. Act as an active guide, walking users through three stages: Context Gathering, Refinement & Structure, and Reader Testing.
edr-bypass-re sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Review EDR telemetry and known defense-evasion classes using offline evidence and controlled defensive coverage assessments.
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.
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.
finishing-a-development-branch sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
frontend-mobile-security-xss-scan sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Inspect frontend code for XSS injection points, unsafe DOM manipulation, and missing sanitization.
gh-review-requests sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Fetch unread GitHub notifications for open PRs where review is requested from a specified team or opened by a team member. Use when asked to "find PRs I need to review", "show my review requests", "what needs my review", "fetch GitHub review requests", or "check team review queue".
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.
hatch-pet openai/skills · score 77/100 (grade C)
Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.
hunt-aspnet sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Hunt ASP.NET-specific surface
hunt-fintech-graphql sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Hunt fintech-specific GraphQL vulnerabilities
hunt-laravel sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Hunt Laravel specific vulnerabilities
infographic-generator Affitor/affiliate-skills · score 77/100 (grade C)
Generate branded infographic specifications from any content or data. Outputs structured layout, copy, data visualization, and color scheme — ready to render as HTML/CSS, Satori, Canva, or any design tool. Use this skill when the user wants an infographic, data visual, social media image, comparison chart, stat card, or says "create an infographic for [content]", "make a visual for my LinkedIn post", "design an image for [topic]", "stat graphic for [data]", "comparison infographic", "branded image", "social media graphic", "infographic for [blog post]", "data visualization", "visual content", "image for my post", "LinkedIn carousel image", "feature comparison chart", "pricing table image".
kotlin-testing affaan-m/ECC · score 77/100 (grade C)
Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices. Use when writing Kotlin tests with Kotest or MockK, or testing coroutines and checking coverage.
kotlin-testing affaan-m/everything-claude-code · score 77/100 (grade C)
Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices. Use when writing Kotlin tests with Kotest or MockK, or testing coroutines and checking coverage.
logistics-exception-management affaan-m/ECC · score 77/100 (grade C)
Codified freight-exception handling expertise for shipment delays, damages, losses, shortages, and carrier disputes, with escalation protocols, carrier-specific behaviors by mode, claims procedures, and eat-the-cost vs fight-the-claim judgment frameworks. Use when handling shipping exceptions, freight claims, delivery issues, or carrier disputes.
logistics-exception-management affaan-m/everything-claude-code · score 77/100 (grade C)
Codified freight-exception handling expertise for shipment delays, damages, losses, shortages, and carrier disputes, with escalation protocols, carrier-specific behaviors by mode, claims procedures, and eat-the-cost vs fight-the-claim judgment frameworks. Use when handling shipping exceptions, freight claims, delivery issues, or carrier disputes.
logo-image-design sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Brand asset register: asset type, format, dimensions and aspect ratio, colour mode, background variant, clear space, approved and prohibited uses, rights owner and licence. Use for brand control.
mailtrap-testing-with-sandbox sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Capture outbound email in Mailtrap Email Sandbox for development, staging, CI, HTML inspection, spam checks, and fake inbox tests.
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.
networkx K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.
openapi-to-application-code github/awesome-copilot · score 77/100 (grade C)
Generate a complete, production-ready application from an OpenAPI specification
penetration-testing sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Perform basic penetration testing and security assessments.
performance-optimization addyosmani/agent-skills · score 77/100 (grade C)
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
polars-bio K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Performs genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data. Use for coordinate-aware genomic joins, read-depth analysis, lazy bioinformatics I/O, SQL queries or migration from bioframe.
posix-shell-pro sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Expert in strict POSIX sh scripting for maximum portability across Unix-like systems. Specializes in shell scripts that run on any POSIX-compliant shell (dash, ash, sh, bash --posix).
rdkit K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
rebase-current-branch github/awesome-copilot · score 77/100 (grade C)
Rebase the currently checked out feature branch onto the latest upstream default branch. Use when asked to update a branch with main or master, rebase the current branch onto the default branch, or sync a feature branch before review. Detects whether the repository uses main or master and guides safe conflict handling.
red-team-tools sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Implement proven methodologies and tool workflows from top security researchers for effective reconnaissance, vulnerability discovery, and bug bounty hunting. Automate common tasks while maintaining thorough coverage of attack surfaces.
research-grants K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Supports research proposal preparation and review for NSF, NIH, DOE, DARPA, and Taiwan NSTC, including opportunity-specific requirements, aims, review criteria, budgets, broader impacts, forms, and resubmissions. Use for investigator-authored grant development, compliance matrices, and proposal critiques.
research-ops-skills alirezarezvani/claude-skills · score 77/100 (grade C)
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
revenue-operations alirezarezvani/claude-skills · score 77/100 (grade C)
Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.
rust-testing affaan-m/ECC · score 77/100 (grade C)
Rust testing patterns including unit tests, integration tests, async testing, property-based testing, mocking, and coverage. Follows TDD methodology. Use when writing Rust tests — unit, integration, async, property-based, or coverage.
rust-testing affaan-m/everything-claude-code · score 77/100 (grade C)
Rust testing patterns including unit tests, integration tests, async testing, property-based testing, mocking, and coverage. Follows TDD methodology. Use when writing Rust tests — unit, integration, async, property-based, or coverage.
sast-configuration sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Static Application Security Testing (SAST) tool setup, configuration, and custom rule creation for comprehensive security scanning across multiple programming languages.
scientific-schematics K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Generates scientific diagram drafts using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.7 Flash for quality review. Refines when the review requests improvement, with at most two generations. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
screen-adverse-media sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Screen a person or organisation for adverse media coverage, PEP status, and sanctions exposure — corroboration-gated, returns "review" never "guilty". Use when the user asks to screen someone before onboarding, partnership, or investment; for AML/CTF flows; or for ongoing counterparty monitoring.
spring-boot-testing github/awesome-copilot · score 77/100 (grade C)
Expert Spring Boot 4 testing specialist that selects the best Spring Boot testing techniques for your situation with Junit 6 and AssertJ.
systematic-debugging obra/superpowers · score 77/100 (grade C)
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
test-audit garrytan/gstack · score 77/100 (grade C)
Find low-value or duplicate tests and the test-only code they keep alive. (gstack)
unit-test-vue-pinia github/awesome-copilot · score 77/100 (grade C)
Write and review unit tests for Vue 3 + TypeScript + Vitest + Pinia codebases. Use when creating or updating tests for components, composables, and stores; mocking Pinia with createTestingPinia; applying Vue Test Utils patterns; and enforcing black-box assertions over implementation details.
unit-testing-test-generate sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Generate comprehensive, maintainable unit tests across languages with strong coverage and edge case focus.
venue-templates K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Prepares journal manuscripts, conference papers, research posters, and grant documents using venue-specific formatting guidance and bundled LaTeX scaffolds. Supports selecting an official template, checking current page or anonymity rules, adapting academic writing to a venue, or inspecting a submission PDF.
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.
web3-testing sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Master comprehensive testing strategies for smart contracts using Hardhat, Foundry, and advanced testing patterns.
webapp-testing github/awesome-copilot · score 77/100 (grade C)
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
ad-creative alirezarezvani/claude-skills · score 76/100 (grade C)
When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.
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
antithesis-debug antithesishq/antithesis-skills · score 76/100 (grade C)
Run a bash script inside an Antithesis run at a chosen moment with `snouty runs exec`, from the terminal and without a browser. Use it for scripted forensics on a run: process and container inspection, on-disk evidence, gdb attach, and general debugging. Covers command usage, the live-session requirement, common workflows and errors, and how virtual time and perturbation limit what a debugger can see.
antithesis-setup antithesishq/antithesis-skills · score 76/100 (grade C)
Scaffold the Antithesis harness with docker-compose: initialize the working directory, write Dockerfiles and docker-compose.yaml with build directives, and prepare to submit your first Antithesis test run. If the desired setup is Kubernetes, defer to the antithesis-setup-k8s skill.
arize-dataset github/awesome-copilot · score 76/100 (grade C)
Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.
asc-in-app-events rudrankriyam/app-store-connect-cli-skills · score 76/100 (grade C)
Create and localize App Store in-app events, upload event media, and submit or recover event review submissions with asc. Use when managing in-app events, event card or details page assets, or event-specific submission errors.
asc-ppp-pricing rudrankriyam/app-store-connect-cli-skills · score 76/100 (grade C)
Set territory-specific pricing for subscriptions and in-app purchases using current asc setup, pricing summary, price import, and price schedule commands. Use when adjusting prices by country or implementing localized PPP strategies.
aws-penetration-testing sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
azure-logic-apps-standard-cli github/awesome-copilot · score 76/100 (grade C)
Create, inspect, validate, test, run, debug, package, and deploy Azure Logic Apps Standard projects using the Azure CLI logicapp extension. Use for Standard workflow authoring, optional workspaces, connector discovery, identity-based connections, local runtimes, native workflow tests, and approved cloud lifecycle operations. Not for Consumption-only workflow development.
burp-suite-testing sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Execute comprehensive web application security testing using Burp Suite's integrated toolset, including HTTP traffic interception and modification, request analysis and replay, automated vulnerability scanning, and manual testing workflows.
c4-code sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Expert C4 Code-level documentation specialist. Analyzes code directories to create comprehensive C4 code-level documentation including function signatures, arguments, dependencies, and code structure.
c4-component sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Expert C4 Component-level documentation specialist. Synthesizes C4 Code-level documentation into Component-level architecture, defining component boundaries, interfaces, and relationships.
code-documentation-code-explain sickn33/antigravity-awesome-skills · score 76/100 (grade C)
You are a code education expert specializing in explaining complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Transform difficult concepts into understandable explanations for developers at all levels.
cross-platform-contract-propagation-audit sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Use when auditing whether a field, enum, flag, or API contract propagates consistently across storage, services, clients, analytics, and tests.
data-engineering-data-pipeline sickn33/antigravity-awesome-skills · score 76/100 (grade C)
You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.
deployment-validation-config-validate sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Validate application configurations with schemas, configuration tests, and checks for security and environment consistency.
dotnet-architect sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Expert .NET backend architect specializing in C#, ASP.NET Core, Entity Framework, Dapper, and enterprise application patterns.
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.
eu-ai-act-specialist alirezarezvani/claude-skills · score 76/100 (grade C)
EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and deadlines? Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations. Cites Articles + Annexes for every output. NOT executive AI strategy (see chief-ai-officer-advisor). NOT a legal substitute.
firmware-analyst sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Expert firmware analyst specializing in embedded systems, IoT security, and hardware reverse engineering.
fix alirezarezvani/claude-skills · score 76/100 (grade C)
Fix failing or flaky Playwright tests. Use when user says "fix test", "flaky test", "test failing", "debug test", "test broken", "test passes sometimes", or "intermittent failure".
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
frontend-security-coder sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Expert in secure frontend coding practices specializing in XSS prevention, output sanitization, and client-side security patterns.
fsharp-testing affaan-m/ECC · score 76/100 (grade C)
F# testing patterns with xUnit, FsUnit, Unquote, FsCheck property-based testing, integration tests, and test organization best practices. Use when writing F# tests with xUnit, FsUnit, Unquote, or FsCheck.
fsharp-testing affaan-m/everything-claude-code · score 76/100 (grade C)
F# testing patterns with xUnit, FsUnit, Unquote, FsCheck property-based testing, integration tests, and test organization best practices. Use when writing F# tests with xUnit, FsUnit, Unquote, or FsCheck.
gh-fix-ci openai/skills · score 76/100 (grade C)
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
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.
hunt-springboot sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Hunt Spring Boot specific vulnerabilities
java-debugging github/awesome-copilot · score 76/100 (grade C)
Debug Java applications systematically: JDWP remote debugging, jdb, VS Code and IntelliJ attach, debugging Maven/Gradle tests, Spring Boot and Quarkus dev mode, containers, breakpoints/logpoints, and reading stack traces. Use when the user needs to find the cause of a Java bug, exception, wrong behavior, or failing test, or asks how to attach a debugger.
kubernetes-operator alirezarezvani/claude-skills · score 76/100 (grade C)
Use when building a Kubernetes Operator — custom controllers that reconcile CRD state. Triggers on "build an operator", "CRD design", "reconcile loop", "controller-runtime", "kubebuilder", "operator-sdk", "metacontroller", "KOPF", "operator capability levels", or "custom resource". Ships CRD validator, reconcile-loop linter, and OperatorHub capability auditor (all stdlib Python), 4 references on the operator pattern + CRD design + reconcile patterns + tooling landscape, and a /operator-audit slash command. NOT a generic k8s skill — specifically the Operator pattern.
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.
pentest-commands sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Provide a comprehensive command reference for penetration testing tools including network scanning, exploitation, password cracking, and web application testing. Enable quick command lookup during security assessments.
performance-engineer sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Diagnose performance bottlenecks using profiling, traces, load tests, and observability; verify latency and capacity improvements.
planning-and-task-breakdown addyosmani/agent-skills · score 76/100 (grade C)
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
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).
relsa-severity-assessment K-Dense-AI/claude-scientific-skills · score 76/100 (grade C)
Supports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.
sales-engineer alirezarezvani/claude-skills · score 76/100 (grade C)
Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'.
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?'
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.
security-pen-testing alirezarezvani/claude-skills · score 76/100 (grade C)
Use when the user asks to perform security audits, penetration testing, vulnerability scanning, OWASP Top 10 checks, or offensive security assessments. Covers static analysis, dependency scanning, secret detection, API security testing, and pen test report generation.
seo-plan sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Strategic SEO planning for new or existing websites. Industry-specific templates, competitive analysis, content strategy, and implementation roadmap. Use when user says "SEO plan", "SEO strategy", "content strategy", "site architecture", or "SEO roadmap".
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.
social-proof-architect sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Select and place genuine testimonials, case studies, and other proof when an audience needs evidence at specific trust barriers.
statistical-analyst alirezarezvani/claude-skills · score 76/100 (grade C)
Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes. Use when you need to validate whether observed differences are real, size an experiment correctly before launch, or interpret test results with confidence.
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.
tdd-guide alirezarezvani/claude-skills · score 76/100 (grade C)
Test-driven development skill for writing unit tests, generating test fixtures and mocks, analyzing coverage gaps, and guiding red-green-refactor workflows across Jest, Pytest, JUnit, Vitest, and Mocha. Use when the user asks to write tests, improve test coverage, practice TDD, generate mocks or stubs, or mentions testing frameworks like Jest, pytest, or JUnit.
verification-loop Galaxy-Dawn/claude-scholar · score 76/100 (grade C)
This skill should be used when the user asks to "verify code", "run verification", "check quality", "validate changes", or before creating a PR. Provides comprehensive verification including build, type check, lint, tests, security scan, and diff review.
webapp-testing sickn33/antigravity-awesome-skills · score 76/100 (grade C)
To test local web applications, write native Python Playwright scripts.
webapp-testing warpdotdev/oz-skills · score 76/100 (grade C)
Test local web applications with Playwright. Use when asked to verify frontend functionality, debug UI behavior, capture browser screenshots, or inspect browser logs.
writing-plans obra/superpowers · score 76/100 (grade C)
Use when you have a spec or requirements for a multi-step task, before touching code
youtube-full alirezarezvani/claude-skills · score 76/100 (grade C)
Use when the user needs YouTube transcripts, video search, channel browsing, playlist extraction, or content monitoring. Trigger phrases: 'get the transcript for', 'search YouTube for', 'what are the latest videos on', 'list this playlist', 'monitor this channel', or any request involving a YouTube URL, video ID, or @handle. Do NOT use for downloading video or audio files, YouTube engagement data (likes, comments), or private/age-restricted videos.
ad-campaign-analyzer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.
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.
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.
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.
antithesis-review-inputs antithesishq/antithesis-skills · score 75/100 (grade C)
Review a workload's input generation for state space exploration: how well it uses randomness to drive the system under test into diverse regions of behavior.
api-documentation sickn33/antigravity-awesome-skills · score 75/100 (grade C)
API documentation workflow for generating OpenAPI specs, creating developer guides, and maintaining comprehensive API documentation.
api-testing-observability-api-mock sickn33/antigravity-awesome-skills · score 75/100 (grade C)
You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
arrowspace sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Spectral vector search using graph Laplacian eigenstructure. Use when cosine/L2 similarity misses latent structure in your embeddings.
asc-ad-hoc-distribution rudrankriyam/app-store-connect-cli-skills · score 75/100 (grade C)
Prepare, publish, resume, and verify private iOS release-testing installs with asc distribute. Use when distributing an IPA to registered devices outside TestFlight, reconciling ad hoc profiles, publishing through caller-owned S3-compatible storage, or diagnosing a resumable private distribution run.
baoyu-url-to-markdown JimLiu/baoyu-skills · score 75/100 (grade C)
Fetch any URL and convert to markdown using baoyu-fetch CLI (Chrome CDP with site-specific adapters). Built-in adapters for X/Twitter, YouTube transcripts, Hacker News threads, and generic pages via Defuddle. Handles login/CAPTCHA via interaction wait modes. Use when user wants to save a webpage as markdown.
bats-testing-patterns sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Master Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities.
bio-scaffold-analysis GPTomics/bioSkills · score 75/100 (grade C)
Analyzes chemical libraries by scaffold using Bemis-Murcko scaffolds, generic frameworks, cyclic skeletons, matched molecular pair (MMP) analysis via mmpdb, R-group decomposition, Free-Wilson analysis, scaffold hopping, and chemotype-aware ML train/test splits. Use when identifying chemotype clusters in a library, deriving SAR transformation rules, decomposing series into R-groups, performing scaffold-balanced QSAR splits, or planning analog campaigns.
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.
bugcrowd-reporting sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Bugcrowd-specific reporting tactics complementing report-writing
candidate-talent-pool sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Candidate and prospect pool: contact details, experience, skills, consent status and date, referral source and last contact. Use for talent pipelines and re-engagement.
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
cloud-architect sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert cloud architect specializing in AWS/Azure/GCP multi-cloud infrastructure design, advanced IaC (Terraform/OpenTofu/CDK), FinOps cost optimization, and modern architectural patterns.
codebase-cleanup-deps-audit sickn33/antigravity-awesome-skills · score 75/100 (grade C)
You are a dependency security expert specializing in vulnerability scanning, license compliance, and supply chain security. Analyze project dependencies for known vulnerabilities, licensing issues, outdated packages, and provide actionable remediation strategies.
content-marketer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Elite content marketing strategist specializing in AI-powered content creation, omnichannel distribution, SEO optimization, and data-driven performance marketing.
coverage alirezarezvani/claude-skills · score 75/100 (grade C)
Analyze test coverage gaps. Use when user says "test coverage", "what's not tested", "coverage gaps", "missing tests", "coverage report", or "what needs testing".
customer-support sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Elite AI-powered customer support specialist mastering conversational AI, automated ticketing, sentiment analysis, and omnichannel support experiences.
dependency-management-deps-audit sickn33/antigravity-awesome-skills · score 75/100 (grade C)
You are a dependency security expert specializing in vulnerability scanning, license compliance, and supply chain security. Analyze project dependencies for known vulnerabilities, licensing issues, outdated packages, and provide actionable remediation strategies.
design-it sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Routes frontend design tasks to 48 specific UI styles. Triggers for websites, app screens, or UI components requesting a specific aesthetic.
devops-troubleshooter sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability.
dossier alirezarezvani/claude-skills · score 75/100 (grade C)
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica) as workhorses; optional BYOK MCPs enhance coverage. Use when the user asks for background research, diligence, or meeting prep on a specific entity (e.g., 'prep me for a meeting with [person/company]', 'due diligence on [company]'). Honors sensitivity exclusions for journalism + personal-vetting contexts.
dx-optimizer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Developer Experience specialist. Improves tooling, setup, and workflows. Use for requested project setup or measured development friction; respect existing team conventions.
epic-design alirezarezvani/claude-skills · score 75/100 (grade C)
Build immersive, cinematic 2.5D interactive websites using scroll storytelling, parallax depth, text animations, and premium scroll effects — no WebGL required. Use this skill for any web design task: landing pages, product sites, hero sections, scroll animations, parallax, sticky sections, section overlaps, floating products between sections, clip-path reveals, text that flies in from sides, words that light up on scroll, curtain drops, iris opens, card stacks, bleed typography, and any site that should feel cinematic or premium. Trigger on phrases like "make it feel alive", "Apple-style animation", "sections that overlap", "product rises between sections", "immersive", "scrollytelling", or any scroll-driven visual effect. Covers 45+ techniques across 8 categories. Always inspects, judges, and plans assets before coding. Use aggressively for ANY web design task.
experiment-designer alirezarezvani/claude-skills · score 75/100 (grade C)
Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.
figma-implement-design openai/skills · score 75/100 (grade C)
Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions "implement design", "generate code", "implement component", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.
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
fp-react sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Practical patterns for using fp-ts with React - hooks, state, forms, data fetching. Includes version-specific React examples; verify framework/client boundaries.
gcp-cloud-run sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Specialized skill for building production-ready serverless
generate alirezarezvani/claude-skills · score 75/100 (grade C)
Generate Playwright tests. Use when user says "write tests", "generate tests", "add tests for", "test this component", "e2e test", "create test for", "test this page", or "test this feature".
gke-compute-classes google/skills · score 75/100 (grade C)
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto Provisioning configuration or general GKE cluster creation.
go-playwright sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert capability for robust, stealthy, and efficient browser automation using Playwright Go.
godot-4-migration sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Specialized guide for migrating Godot 3.x projects to Godot 4 (GDScript 2.0), covering syntax changes, Tweens, and exports.
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.
html-injection-testing sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Identify and exploit HTML injection vulnerabilities that allow attackers to inject malicious HTML content into web applications. This vulnerability enables attackers to modify page appearance, create phishing pages, and steal user credentials through injected forms.
incident-responder sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert SRE incident responder specializing in rapid problem resolution, modern observability, and comprehensive incident management.
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.
interview-coach sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Full job search coaching system — JD decoding, resume, storybank, mock interviews, transcript analysis, comp negotiation. Coaching guide with an optional separately installed command package and scoped state.
ios-qa garrytan/gstack · score 75/100 (grade C)
Live-device iOS QA for SwiftUI apps. (gstack)
itil-expert sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert advisor for ITIL 4 and ITIL 5 (2026 digital product paradigm), specialized in AI-native governance, sustainability, and value co-creation.
java-coding-standards affaan-m/ECC · score 75/100 (grade C)
Java coding standards for Spring Boot and Quarkus services: naming, immutability, Optional usage, streams, exceptions, generics, CDI, reactive patterns, and project layout. Automatically applies framework-specific conventions. Use when writing or reviewing Java in a Spring Boot or Quarkus service.
java-coding-standards affaan-m/everything-claude-code · score 75/100 (grade C)
Java coding standards for Spring Boot and Quarkus services: naming, immutability, Optional usage, streams, exceptions, generics, CDI, reactive patterns, and project layout. Automatically applies framework-specific conventions. Use when writing or reviewing Java in a Spring Boot or Quarkus service.
java-testcontainers github/awesome-copilot · score 75/100 (grade C)
Write reliable integration tests in plain Java with Testcontainers 2.x: JUnit Jupiter lifecycle, singleton containers, reuse, generic containers, wait strategies, networks, init scripts, Docker Compose, CI and Docker/Podman setup. Use when adding or fixing Testcontainers tests, or migrating from 1.x. Framework-neutral.
landing-page-generator alirezarezvani/claude-skills · score 75/100 (grade C)
Generates high-converting landing pages as complete Next.js/React (TSX) components with Tailwind CSS. Creates hero sections, feature grids, pricing tables, FAQ accordions, testimonial blocks, and CTA sections using proven copy frameworks (PAS, AIDA, BAB). Outputs SEO meta tags, structured data, and performance-optimised code targeting Core Web Vitals (LCP under 1s, CLS under 0.1). Use when the user asks to create a landing page, marketing page, homepage, single-page site, lead capture page, campaign page, promo page, or conversion-optimised web page — or when they want to A/B test landing page variants or replace a static page with one designed to convert.
laravel-verification affaan-m/ECC · score 75/100 (grade C)
Verification loop for Laravel projects: env checks, linting, static analysis, tests with coverage, security scans, and deployment readiness. Use when verifying a Laravel project before merge or deploy — lint, static analysis, tests, coverage, security.
laravel-verification affaan-m/everything-claude-code · score 75/100 (grade C)
Verification loop for Laravel projects: env checks, linting, static analysis, tests with coverage, security scans, and deployment readiness. Use when verifying a Laravel project before merge or deploy — lint, static analysis, tests, coverage, security.
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.
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.
malware-analyst sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert malware analyst specializing in defensive malware research, threat intelligence, and incident response. Masters sandbox analysis, behavioral analysis, and malware family identification.
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.
odoo-automated-tests sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Write and run Odoo automated tests using TransactionCase, HttpCase, and browser tour tests. Covers test data setup, mocking, and CI integration.
playwright openai/skills · score 75/100 (grade C)
Use when the task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script.
playwright-skill sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Write and run scoped Playwright browser automation, responsive checks, screenshots and login-flow tests with a local Node executor.
product-research alirezarezvani/claude-skills · score 75/100 (grade C)
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
qa-only garrytan/gstack · score 75/100 (grade C)
Report browser/API/CLI/job/worker/webhook bugs. (gstack)
reverse-browser-automation sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Automate browsers (Playwright) and Windows desktop applications (UI automation) for reverse-engineering evidence collection, UI-driven workflows, and network observation during analysis.
reverse-engineer sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Expert reverse engineer specializing in binary analysis, disassembly, decompilation, and software analysis. Masters IDA Pro, Ghidra, radare2, x64dbg, and modern RE toolchains.
ruby-pro sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Write idiomatic Ruby code with metaprogramming, Rails patterns, and performance optimization. Specializes in Ruby on Rails, gem development, and testing frameworks.
saas-pricing-strategist sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Design, optimize, and test pricing strategies for SaaS products using
salary-benchmarking sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Salary benchmark register: role, department and grade against market and internal minimum, median and maximum. Use for compensation review.
security-audit sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Comprehensive security auditing workflow covering web application testing, API security, penetration testing, vulnerability scanning, and security hardening.
security-compliance-compliance-check sickn33/antigravity-awesome-skills · score 75/100 (grade C)
You are a compliance expert specializing in regulatory requirements for software systems including GDPR, HIPAA, SOC2, PCI-DSS, and other industry standards. Perform comprehensive compliance audits and provide implementation guidance for achieving and maintaining compliance.
senior-backend alirezarezvani/claude-skills · score 75/100 (grade C)
Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Covers Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.
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.
spec-driven-development addyosmani/agent-skills · score 75/100 (grade C)
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when drafting a PRD or requirements document with objectives and scope, or when requirements are unclear, ambiguous, or only exist as a vague idea. Use when a single requirement spans several independently testable capabilities and needs decomposing into a capability map of modules before specifying.
swift-testing-expert AvdLee/Swift-Testing-Agent-Skill · score 75/100 (grade C)
Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.
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.
testing-patterns sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Jest testing patterns, factory functions, mocking strategies, and TDD workflow. Use when writing unit tests, creating test factories, or following TDD red-green-refactor cycle.
testing-qa sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Comprehensive testing and QA workflow covering unit testing, integration testing, E2E testing, browser automation, and quality assurance.
threejs-qa-release majidmanzarpour/threejs-game-skills · score 75/100 (grade C)
Verify and release Three.js browser games: playtest QA, automated bot playtests, mobile and responsive checks, production builds, static-hosting base paths, debug gating, bundle review, screenshots, visual regression baselines, canvas-pixel inspection with measured metrics, and release risk reports.
tinystruct-patterns affaan-m/ECC · score 75/100 (grade C)
Expert guidance for developing with the tinystruct Java framework. Use when working on the tinystruct codebase or any project built on tinystruct — including generating the bin/dispatcher and bin/dispatcher.cmd launcher scripts when a project lacks them, creating Application classes, @Action-mapped routes, unit tests, ActionRegistry, HTTP/CLI dual-mode handling, the built-in HTTP server, the event system, JSON with Builder/Builders, database persistence with AbstractData, POJO generation, Server-Sent Events (SSE), file uploads, and outbound HTTP networking.
tinystruct-patterns affaan-m/everything-claude-code · score 75/100 (grade C)
Expert guidance for developing with the tinystruct Java framework. Use when working on the tinystruct codebase or any project built on tinystruct — including generating the bin/dispatcher and bin/dispatcher.cmd launcher scripts when a project lacks them, creating Application classes, @Action-mapped routes, unit tests, ActionRegistry, HTTP/CLI dual-mode handling, the built-in HTTP server, the event system, JSON with Builder/Builders, database persistence with AbstractData, POJO generation, Server-Sent Events (SSE), file uploads, and outbound HTTP networking.
top-web-vulnerabilities sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Provide an illustrative, overlapping reference for common web application vulnerability patterns organized by category. This skill enables systematic vulnerability identification, impact assessment, and remediation guidance across the full spectrum of web security threats.
typespec-create-api-plugin github/awesome-copilot · score 75/100 (grade C)
Generate a TypeSpec API plugin with REST operations, authentication, and Adaptive Cards for Microsoft 365 Copilot
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.
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.
ux-researcher-designer alirezarezvani/claude-skills · score 75/100 (grade C)
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs.
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.
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).
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.
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.
antithesis-triage antithesishq/antithesis-skills · score 74/100 (grade C)
Triage Antithesis test reports to understand what happened in a run: look up runs, check status, investigate failed properties (assertions), view metadata, download logs, search events across all timelines, inspect findings, and examine environmental details. Load after a run completes or when investigating a failure.
apple-hig-expert alirezarezvani/claude-skills · score 74/100 (grade C)
Audits and designs iOS/macOS/watchOS/visionOS interfaces against the Apple Human Interface Guidelines, including the Liquid Glass design language (announced WWDC25, shipped with iOS 26/macOS Tahoe, Sept 2025). Use when reviewing an Apple-platform mockup or app for HIG compliance, checking contrast or tap-target sizes, or designing native-feeling Apple UI (e.g., 'audit my iOS app against the HIG', 'is this text readable on Liquid Glass?').
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.
arm-cortex-expert sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).
baoyu-electron-extract JimLiu/baoyu-skills · score 74/100 (grade C)
Extracts resources and JavaScript from any installed Electron app (`.asar` bundle), restoring original sources from `.js.map` files when available or formatting minified code with Prettier otherwise. Use when user wants to "extract Electron app", "decompile Electron", "get the source code of <app>", "inspect app.asar", "看 Electron 应用源码", "提取 .asar", or asks how a desktop Electron app is built. Skips `node_modules` and supports both macOS and Windows.
bio-clinical-databases-clinvar-lookup GPTomics/bioSkills · score 74/100 (grade C)
Queries ClinVar for variant pathogenicity classifications, ClinGen VCEP curations, and somatic-vs-germline interpretations via REST API, weekly VCF, or bulk XML. Use when determining clinical significance, triangulating conflicting interpretations, or aggregating evidence against the ACMG/AMP framework with ClinGen SVI specifications.
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.
bio-ribo-seq-ribosome-periodicity GPTomics/bioSkills · score 74/100 (grade C)
Validate Ribo-seq library quality by measuring 3-nucleotide periodicity and calibrating read-length-specific P-site offsets. Use when checking whether footprints capture genuine translation, determining P-site offsets for downstream ORF/TE/stalling analysis, or deciding which read lengths to keep.
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.
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.
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.
brownfield-retrospective affaan-m/ECC · score 74/100 (grade C)
Run the ECC engineering process retroactively against an existing project slice. Audit current state, reconstruct past decisions, produce a four-axis gap register (thinking, coding practice, missing features, technology selection), then execute fixes forward through the plan-TDD-review pipeline. Use when adopting ECC mid-project, taking over an inherited codebase, or asking what was missed and what would have been built differently from day one.
brownfield-retrospective affaan-m/everything-claude-code · score 74/100 (grade C)
Run the ECC engineering process retroactively against an existing project slice. Audit current state, reconstruct past decisions, produce a four-axis gap register (thinking, coding practice, missing features, technology selection), then execute fixes forward through the plan-TDD-review pipeline. Use when adopting ECC mid-project, taking over an inherited codebase, or asking what was missed and what would have been built differently from day one.
bug-reproduction-brief github/awesome-copilot · score 74/100 (grade C)
Turn a vague, intermittent, or environment-specific bug report into a minimal evidence-backed reproduction before proposing a fix.
bullmq-specialist sickn33/antigravity-awesome-skills · score 74/100 (grade C)
BullMQ expert for Redis-backed job queues, background processing,
c4-context sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Expert C4 Context-level documentation specialist. Creates high-level system context diagrams, documents personas, user journeys, system features, and external dependencies.
ci-cd-and-automation addyosmani/agent-skills · score 74/100 (grade C)
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
code-refactoring-refactor-clean sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are a code refactoring expert specializing in clean code principles, SOLID design patterns, and modern software engineering best practices. Analyze and refactor the provided code to improve its quality, maintainability, and performance.
code-reviewer sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Elite code review expert specializing in modern AI-powered code
code-simplifier sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Use when asked to "simplify code", "clean up code", "refactor for clarity", "improve readability", or review recently modified code for elegance. Focuses on project-specific best practices.
codebase-cleanup-refactor-clean sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are a code refactoring expert specializing in clean code principles, SOLID design patterns, and modern software engineering best practices. Analyze and refactor the provided code to improve its quality, maintainability, and performance.
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.
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
contract-first affaan-m/ECC · score 74/100 (grade C)
Coordinate frontend/backend or service-to-service work through one authoritative machine-checkable contract (OpenAPI, AsyncAPI, Protocol Buffers, or JSON Schema), with generated consumer types and contract-verified integration. Use when parallel consumer and provider work must evolve an API or event schema without field drift, mock/production shape mismatch, or one side silently redefining the interface.
contract-first affaan-m/everything-claude-code · score 74/100 (grade C)
Coordinate frontend/backend or service-to-service work through one authoritative machine-checkable contract (OpenAPI, AsyncAPI, Protocol Buffers, or JSON Schema), with generated consumer types and contract-verified integration. Use when parallel consumer and provider work must evolve an API or event schema without field drift, mock/production shape mismatch, or one side silently redefining the interface.
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.
copy-editing sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are an expert copy editor specializing in marketing and conversion copy. Your goal is to systematically improve existing copy through focused editing passes while preserving the core message.
create-github-action-workflow-specification github/awesome-copilot · score 74/100 (grade C)
Create a formal specification for an existing GitHub Actions CI/CD workflow, optimized for AI consumption and workflow maintenance.
csharp-mstest github/awesome-copilot · score 74/100 (grade C)
Get best practices for MSTest 3.x/4.x unit testing, including modern assertion APIs and data-driven tests
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.
database-admin sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Expert database administrator specializing in modern cloud databases, automation, and reliability engineering.
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.
debugging-toolkit-smart-debug sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Diagnose failures from reproduction steps, traces, logs and code; test hypotheses and verify a scoped fix without inventing production evidence.
defi-yield-strategy-allocator sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Multi-vault automated yield strategy allocation register: APY benchmarks, impermanent loss risk tiers, and rebalancing triggers.
define-goal openai/skills · score 74/100 (grade C)
Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.
design-review garrytan/gstack · score 74/100 (grade C)
Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. (gstack)
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.
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.
django-pro sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Master Django 5.x with async views, DRF, Celery, and Django Channels. Build scalable web applications with proper architecture, testing, and deployment.
django-verification affaan-m/ECC · score 74/100 (grade C)
Run the full Django verification loop — environment check, mypy/ruff/black linting, migration safety, pytest with coverage targets, pip-audit and bandit security scans, settings and logging review, and diff review — producing a phased pass/fail report before release or PR. Use when preparing a Django pull request, validating migrations or coverage, or running pre-deploy readiness checks.
django-verification affaan-m/everything-claude-code · score 74/100 (grade C)
Run the full Django verification loop — environment check, mypy/ruff/black linting, migration safety, pytest with coverage targets, pip-audit and bandit security scans, settings and logging review, and diff review — producing a phased pass/fail report before release or PR. Use when preparing a Django pull request, validating migrations or coverage, or running pre-deploy readiness checks.
doubt-driven-development addyosmani/agent-skills · score 74/100 (grade C)
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
e2e-testing sickn33/antigravity-awesome-skills · score 74/100 (grade C)
End-to-end testing workflow with Playwright for browser automation, visual regression, cross-browser testing, and CI/CD integration.
error-diagnostics-smart-debug sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Diagnose failures from reproduction steps, traces, logs and code; test hypotheses and verify a scoped fix without inventing production evidence.
flutter-dev MiniMax-AI/skills · score 74/100 (grade C)
Flutter cross-platform development guide covering widget patterns, Riverpod/Bloc state management, GoRouter navigation, performance optimization, and platform-specific implementations. Includes const optimization, responsive layouts, testing strategies, and DevTools profiling. Use when: building Flutter apps, implementing state management (Riverpod/Bloc), setting up GoRouter navigation, creating custom widgets, optimizing performance, writing widget tests, cross-platform development.
framework-migration-deps-upgrade sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are a dependency management expert specializing in safe, incremental upgrades of project dependencies. Plan and execute dependency updates with minimal risk, proper testing, and clear migration paths.
geo-technical sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Technical SEO audit with GEO-specific checks — crawlability, indexability,
golang-testing affaan-m/ECC · score 74/100 (grade C)
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices. Use when writing Go tests — table-driven cases, subtests, benchmarks, fuzzing, or coverage.
golang-testing affaan-m/everything-claude-code · score 74/100 (grade C)
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices. Use when writing Go tests — table-driven cases, subtests, benchmarks, fuzzing, or coverage.
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.
grilling sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Interview the user relentlessly about a plan or design. Use when the user wants to stress-test a plan before building, or uses any 'grill' trigger phrases.
healthcare-eval-harness affaan-m/ECC · score 74/100 (grade C)
Patient safety evaluation harness for healthcare application deployments. Automated test suites for CDSS accuracy, PHI exposure, clinical workflow integrity, and integration compliance. Blocks deployments on safety failures. Use when a healthcare deployment must be gated on patient-safety tests for CDSS accuracy, PHI exposure, and workflow integrity.
healthcare-eval-harness affaan-m/everything-claude-code · score 74/100 (grade C)
Patient safety evaluation harness for healthcare application deployments. Automated test suites for CDSS accuracy, PHI exposure, clinical workflow integrity, and integration compliance. Blocks deployments on safety failures. Use when a healthcare deployment must be gated on patient-safety tests for CDSS accuracy, PHI exposure, and workflow integrity.
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.
hunt-nodejs sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Hunt Node.js specific vulnerabilities
ios-sync garrytan/gstack · score 74/100 (grade C)
Regenerate the iOS debug bridge against the latest upstream gstack templates. (gstack)
java-pro sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Master Java 21+ with modern features like virtual threads, pattern matching, and Spring Boot 3.x. Expert in the latest Java ecosystem including GraalVM, Project Loom, and cloud-native patterns.
kotlin-coroutines-expert sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Expert patterns for Kotlin Coroutines and Flow, covering structured concurrency, error handling, and testing.
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.
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.
linux-shell-scripting sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Provide production-ready shell script templates for common Linux system administration tasks including backups, monitoring, user management, log analysis, and automation. These scripts serve as building blocks for security operations and penetration testing environments.
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.
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.
managed-airflow-migrations google/skills · score 74/100 (grade C)
Provides guidance for migrating Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers migration to Airflow 2.11.1 (MSAA Gen 2 and 3) and Airflow 3 (MSAA Gen 3), including environment inspection, GCS download/upload and scanning patterns for breaking changes. Use when migrating the DAG code to newer Airflow version. Don't use when checking DAG run failures unrelated to code migration.
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.
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.
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.
migrate-to-rust google/skills · score 74/100 (grade C)
Clones, analyzes, plans, and migrates legacy codebases (C++, Fortran, Java, Python, C, Shell) from a GitHub URL or local directory to a modern, high-performance, deterministic, 100% Safe Rust architecture, tracking live telemetry across every task bucket, test failure/fix cycle, and Profile-Guided Optimization (PGO) stage, and producing a first-person AI storytelling report and interactive HTML infographic. Use when migrating a GitHub repository or local codebase to Rust, porting legacy C++, Fortran, Python, or Java workloads to memory-safe Rust, designing Struct-of-Arrays (SoA) or SIMD Rust architectures, or optimizing Rust ports with LLVM PGO. Don't use for unrelated non-Rust refactoring or single-line syntax questions.
nestjs-expert sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are an expert in Nest.js with deep knowledge of enterprise-grade Node.js application architecture, dependency injection patterns, decorators, middleware, guards, interceptors, pipes, testing strategies, database integration, and authentication systems.
odoo-l10n-compliance sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Country-specific Odoo localization: tax configuration, e-invoicing (CFDI, FatturaPA, SAF-T), fiscal reporting, and country chart of accounts setup.
oo-component-documentation github/awesome-copilot · score 74/100 (grade C)
Create or update standardized object-oriented component documentation using a shared template plus mode-specific guidance for new and existing docs.
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.
patent alirezarezvani/claude-skills · score 74/100 (grade C)
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
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
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).
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.
python-development sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint (Alias for python-development-python-scaffold)
python-development-python-scaffold sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint
quarkus-native-and-container github/awesome-copilot · score 74/100 (grade C)
Build Quarkus native executables (Mandrel/GraalVM), fix native failures with reflection registration, test the native binary, and produce container images and Kubernetes/OpenShift manifests. Use for native, Docker, Jib or Kubernetes work in a Quarkus project.
quarkus-tdd affaan-m/ECC · score 74/100 (grade C)
Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.
quarkus-tdd affaan-m/everything-claude-code · score 74/100 (grade C)
Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.
red-team-engagement briiirussell/cybersecurity-skills · score 74/100 (grade C)
Plan, scope, and execute an authorized red-team engagement — distinct from a penetration test. Covers engagement methodology, assumed-breach scenarios, ATT&CK emulation plans, rules of engagement, deconfliction with the blue team, post-engagement debriefs, and the program-level work that makes red teams actually improve defenses. Use when the user mentions 'red team,' 'red team engagement,' 'red teaming,' 'adversary emulation,' 'ATT&CK emulation,' 'assumed breach,' 'purple team exercise,' 'tabletop with technical execution,' 'red team scope,' 'rules of engagement,' 'red team RoE,' 'deconfliction,' 'red team debrief,' or wants to design or run a red-team engagement against systems with authorization.
roslyn-analyzers github/awesome-copilot · score 74/100 (grade C)
Build, review, debug, package, and test Roslyn diagnostic analyzers, code fix providers, and incremental source generators. Use for DiagnosticAnalyzer, CodeFixProvider, IIncrementalGenerator, IOperation analysis, Microsoft.CodeAnalysis dependency pinning, Roslyn test harnesses, C#/VB tests, and analyzer NuGet packaging.
scanning-tools sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Master essential security scanning tools for network discovery, vulnerability assessment, web application testing, wireless security, and compliance validation. This skill covers tool selection, configuration, and practical usage across different scanning categories.
security-auditor sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Expert security auditor specializing in DevSecOps, comprehensive cybersecurity, and compliance frameworks.
semantic-kernel github/awesome-copilot · score 74/100 (grade C)
Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.
ship garrytan/gstack · score 74/100 (grade C)
Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. (gstack)
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.
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.
slack-qa-investigate warpdotdev/oz-skills · score 74/100 (grade C)
Investigate and answer repository questions in read-only mode. Use when asked for research-backed answers that require codebase and documentation investigation without making file changes.
social-content alirezarezvani/claude-skills · score 74/100 (grade C)
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.
sql-injection-testing sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Execute comprehensive SQL injection vulnerability assessments on web applications to identify database security flaws, demonstrate exploitation techniques, and validate input sanitization mechanisms.
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.
swiftui-ui-patterns Dimillian/Skills · score 74/100 (grade C)
Best practices and example-driven guidance for building SwiftUI views and components, including navigation hierarchies, custom view modifiers, and responsive layouts with stacks and grids. Use when creating or refactoring SwiftUI UI, designing tab architecture with TabView, composing screens with VStack/HStack, managing @State or @Binding, building declarative iOS interfaces, or needing component-specific patterns and examples.
systems-programming-rust-project sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are a Rust project architecture expert specializing in scaffolding production-ready Rust applications. Generate complete project structures with cargo tooling, proper module organization, testing
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.
test-driven-development addyosmani/agent-skills · score 74/100 (grade C)
Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality. Use when asked to add tests to a function, fix a bug in it or change its behavior, even when the code is pasted inline and the request does not mention tests.
typed-service-contracts google-labs-code/design.md · score 74/100 (grade C)
Architecture standard for building robust, type-safe TypeScript services using the "Spec and Handler" pattern. Use when building CLIs, libraries, or complex business logic.
ui-from-screenshot sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Turn a screenshot or mockup into matching UI with the project's own components, then compare the result side by side with the image and fix the differences.
ui-screenshots github/awesome-copilot · score 74/100 (grade C)
Capture screenshots of web apps during development using Playwright and PIL. Supports full-page captures, interactive states, and an iterate-on-crop workflow that avoids slow re-screenshots.
ui-to-vue affaan-m/ECC · score 74/100 (grade C)
Use when the user has UI screenshots or design exports that need batch conversion into Vue 3 components, especially with Vant, Element Plus, or Ant Design Vue.
ui-to-vue affaan-m/everything-claude-code · score 74/100 (grade C)
Use when the user has UI screenshots or design exports that need batch conversion into Vue 3 components, especially with Vant, Element Plus, or Ant Design Vue.
ui-visual-validator sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Rigorous visual validation expert specializing in UI testing, design system compliance, and accessibility verification.
update-llms github/awesome-copilot · score 74/100 (grade C)
Update the llms.txt file in the root folder to reflect changes in documentation or specifications following the llms.txt specification at https://llmstxt.org/
webapp-testing Galaxy-Dawn/claude-scholar · score 74/100 (grade C)
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
wiki-qa sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Answer repository questions grounded entirely in source code evidence. Use when user asks a question about the codebase, user wants to understand a specific file, function, or component, or user asks \"how does X work\" or \"where is Y defined\".
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.
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.
aeon K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
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.
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.
antithesis-feature-workload antithesishq/antithesis-skills · score 73/100 (grade C)
Design and build an Antithesis workload for a specific feature: analyze the feature, discover its testable properties, build a self-driving workload that runs locally and in Antithesis, and iterate until the feature's behaviors are exercised and its invariants are checked.
app-store-changelog Dimillian/Skills · score 73/100 (grade C)
Create user-facing App Store release notes by collecting and summarizing all user-impacting changes since the last git tag (or a specified ref). Use when asked to generate a comprehensive release changelog, App Store "What's New" text, or release notes based on git history or tags.
aws-serverless sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Specialized skill for building production-ready serverless
backend-architect sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert backend architect specializing in scalable API design, microservices architecture, and distributed systems.
benchmark-models garrytan/gstack · score 73/100 (grade C)
Cross-model benchmark for gstack skills. (gstack)
bio-bam-statistics GPTomics/bioSkills · score 73/100 (grade C)
Generate alignment statistics using samtools flagstat, stats, depth, coverage, and mosdepth. Use when assessing alignment quality, calculating coverage, or generating QC reports.
bio-methylation-based-detection GPTomics/bioSkills · score 73/100 (grade C)
Detects cancer and infers tissue-of-origin from cfDNA methylation by choosing conversion chemistry (bisulfite vs EM-seq vs TAPS vs cfMeDIP), calling read-level methylation haplotypes rather than averaged beta values, and deconvolving a hematopoietic-dominated cfDNA mixture against a methylation atlas via NNLS/quadratic programming. Encodes the GRAIL/CCGA thesis that thousands of tissue-specific markers make methylation outperform sparse mutations for multi-cancer early detection (MCED) and localization, and that single concordantly-methylated fragments give ppm-level sensitivity. Uses MethylDackel for extraction (mbias-then-extract), MEDIPS/QSEA for enrichment data, scipy.optimize.nnls for deconvolution. Use when building an MCED or methylation-MRD assay, picking a conversion chemistry for low-input plasma, or deconvolving tissue-of-origin from cfDNA.
bio-pathway-reactome GPTomics/bioSkills · score 73/100 (grade C)
Tests a gene list or ranked gene vector for over-representation or coordinated shifts in Reactome's curated, peer-reviewed, reaction-level pathways using ReactomePA's enrichPathway (ORA) and gsePathway (GSEA), reading the local reactome.db so a run is reproducible given the Bioconductor release. Covers why Reactome's atomic unit is the REACTION and pathways are nested containers so a parent and child enrich on the same genes and double-count one signal, why only human is curated and every other species is orthology-inferred, why enrichPathway has NO keyType argument and returns nothing unless genes are ENTREZ (bitr first), and why viewPathway draws a LOCAL reaction network from a pathway NAME. Use when reaction-level granularity, peer-reviewed curation, or an offline-reproducible database is wanted; for comparative multi-sample or multi-omics analysis use ReactomeGSA. The DE list comes from differential-expression; plots from enrichment-visualization.
browser-use davidondrej/skills · score 73/100 (grade C)
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work.
channel-economics alirezarezvani/claude-skills · score 73/100 (grade C)
Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation, and the diminishing-returns inflection (e.g., 'which channel actually makes money — direct or partner?').
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.
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.
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).
context-manager sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems.
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.
create-llms github/awesome-copilot · score 73/100 (grade C)
Create an llms.txt file from scratch based on repository structure following the llms.txt specification at https://llmstxt.org/
create-specification github/awesome-copilot · score 73/100 (grade C)
Create a new specification file for the solution, optimized for Generative AI consumption.
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.
data-quality-frameworks sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
deal-desk alirezarezvani/claude-skills · score 73/100 (grade C)
Use when reviewing a specific inbound deal before close — when sales has asked for a discount that exceeds AE authority, when the customer has redlined the MSA, when per-deal economics (margin after discount, multi-year payment shape, indemnity exposure) need to be quantified, or when discount approval needs to be routed to a named human approver (Sales Director, VP Sales, CFO, CRO, General Counsel). Covers deal review, discount approval routing, per-deal margin scoring, deal exception handling, MSA redline triage, contract landmine detection (uncapped indemnity, MFN, perpetual license-back, missing DPA), and named-approver chain assembly. NEVER auto-approves — every output is a numeric scorecard plus a routing recommendation to a named human.
deployment-engineer sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert deployment engineer specializing in modern CI/CD pipelines, GitOps workflows, and advanced deployment automation.
design nextlevelbuilder/ui-ux-pro-max-skill · score 73/100 (grade C)
Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini, Atlas Cloud, or MuAPI AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations (Chart.js), banner design (22 styles, social/ads/web/print), icon design (15 styles, SVG, Gemini 3.1 Pro), social photos (HTML→screenshot, multi-platform). Actions: design logo, create CIP, generate mockups, build slides, design banner, generate icon, create social photos, social media images, brand identity, design system. Platforms: Facebook, Twitter, LinkedIn, YouTube, Instagram, Pinterest, TikTok, Threads, Google Ads.
doc-coauthoring anthropics/skills · score 73/100 (grade C)
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
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.
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.
earnings-analysis anthropics/financial-services · score 73/100 (grade C)
Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage. Fast-turnaround format focusing on beat/miss analysis, key metrics, updated estimates, and revised thesis. Includes 1-3 summary tables and 8-12 charts. Use when user requests "earnings update", "quarterly update", "earnings analysis", "Q1/Q2/Q3/Q4 results", or post-earnings report.
employment-contract-templates sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Templates and patterns for creating draft employment documentation for jurisdiction-specific legal review including contracts, offer letters, and HR policies.
experimental-design K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
Designs experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.
expo-ui-jetpack-compose sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Build Android-native Expo SDK 55 UI with Jetpack Compose views/modifiers, Host sizing and platform-specific integration.
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.
ffuf-web-fuzzing sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert guidance for ffuf web fuzzing during penetration testing, including authenticated fuzzing with raw requests, auto-calibration, and result analysis
firebase-basics google/skills · score 73/100 (grade C)
Provides foundational Firebase CLI setup, CLI installation, version checks (`firebase-tools@latest --version`), CLI login (including --no-localhost), project creation, project selection (`firebase use`), and app config file downloads (`google-services.json`, `GoogleService-Info.plist`). Use ONLY for CLI login, project creation/switching, or downloading app config files. Don't use for Firebase Hosting deploy, Firestore, Auth, App Hosting, Data Connect, Crashlytics, or Remote Config.
focused-fix alirezarezvani/claude-skills · score 73/100 (grade C)
Use when the user asks to fix, debug, or make a specific feature/module/area work end-to-end. Triggers: 'make X work', 'fix the Y feature', 'the Z module is broken', 'focus on [area]'. Not for quick single-bug fixes — this is for systematic deep-dive repair across all files and dependencies.
fp-ts-react sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Practical patterns for using fp-ts with React - hooks, state, forms, data fetching. Use when building React apps with functional programming patterns. Includes version-specific React patterns requiring project verification.
framework-migration-code-migrate sickn33/antigravity-awesome-skills · score 73/100 (grade C)
You are a code migration expert specializing in transitioning codebases between frameworks, languages, versions, and platforms. Generate comprehensive migration plans, automated migration scripts, and
git-pr-workflows-onboard sickn33/antigravity-awesome-skills · score 73/100 (grade C)
You are an **expert onboarding specialist and knowledge transfer architect** with deep experience in remote-first organizations, technical team integration, and accelerated learning methodologies. You
google-cloud-networking-observability google/skills · score 73/100 (grade C)
Investigates Google Cloud networking issues by analyzing GCP logs, metrics, and diagnostics. Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.
google-cloud-recipe-foundation-builder google/skills · score 73/100 (grade C)
Deploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-recipe-onboarding or product-specific skills instead).
grill-me alirezarezvani/claude-skills · score 73/100 (grade C)
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
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.
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.
hipaa-compliance affaan-m/ECC · score 73/100 (grade C)
HIPAA-specific entrypoint for healthcare privacy and security work. Use when a task is explicitly framed around HIPAA, PHI handling, covered entities, BAAs, breach posture, or US healthcare compliance requirements.
hipaa-compliance affaan-m/everything-claude-code · score 73/100 (grade C)
HIPAA-specific entrypoint for healthcare privacy and security work. Use when a task is explicitly framed around HIPAA, PHI handling, covered entities, BAAs, breach posture, or US healthcare compliance requirements.
imagegen openai/skills · score 73/100 (grade C)
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.
incident-commander alirezarezvani/claude-skills · score 73/100 (grade C)
Comprehensive incident response framework from detection through resolution and post-incident review. Battle-tested SRE/DevOps practices: severity classification, timeline reconstruction, structured post-incident analysis. Use when declaring an incident, coordinating multi-team response during an outage, leading a post-mortem, or setting up on-call practices for a new service.
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.
iso42001-specialist alirezarezvani/claude-skills · score 73/100 (grade C)
ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see compliance-team-eu-ai-act).
it-manager-hospital sickn33/antigravity-awesome-skills · score 73/100 (grade C)
World-class Hospital IT Management Advisor specializing in clinical safety, digital maturity (HIMSS/ONA/JCI), and HIS/PEP ecosystems.
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.
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.
javascript-typescript-typescript-scaffold sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Scaffold TypeScript projects with build tooling, type checking, testing, and configuration.
latchshot-page-capture github/awesome-copilot · score 73/100 (grade C)
Use this skill when a user needs a screenshot, website thumbnail, full-page capture, or PDF of a public HTTP(S) webpage saved as a local artifact through Latchshot, including report, QA, archive, and social-preview workflows. Do not use it for private or authenticated pages, raw HTML, scraping or extraction, arbitrary browser actions, CAPTCHA or anti-bot bypass, or local-file capture.
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.
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.
mobile-security-coder sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert in secure mobile coding practices specializing in input validation, WebView security, and mobile-specific security patterns.
monorepo-navigator alirezarezvani/claude-skills · score 73/100 (grade C)
Navigate, manage, and optimize monorepos. Covers Turborepo, Nx, pnpm workspaces, and Lerna. Cross-package impact analysis, selective builds/tests on affected packages, remote caching, dependency graph visualization, and structured multi-repo to monorepo migrations. Use when setting up a new monorepo, optimizing CI for a large workspace, debugging cross-package dependency issues, or planning a multi-repo consolidation.
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
network-bgp-diagnostics affaan-m/ECC · score 73/100 (grade C)
Diagnostics-only BGP troubleshooting patterns for neighbor state, route exchange, prefix policy, AS path inspection, and safe evidence collection. Use when a BGP neighbor is down, routes are missing, or prefix policy and AS path need inspection.
network-bgp-diagnostics affaan-m/everything-claude-code · score 73/100 (grade C)
Diagnostics-only BGP troubleshooting patterns for neighbor state, route exchange, prefix policy, AS path inspection, and safe evidence collection. Use when a BGP neighbor is down, routes are missing, or prefix policy and AS path need inspection.
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
odoo-backup-strategy sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Complete Odoo backup and restore strategy: database dumps, filestore backup, automated scheduling, cloud storage upload, and tested restore procedures.
pentest-tools sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Operate 20+ penetration-testing tools (Nmap, Nuclei, SQLMap, FFUF, Hashcat, and more) through structured workflows with consistent output handling.
perl-testing affaan-m/ECC · score 73/100 (grade C)
Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology. Use when writing Perl tests with Test2::V0 or Test::More, or measuring coverage.
perl-testing affaan-m/everything-claude-code · score 73/100 (grade C)
Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology. Use when writing Perl tests with Test2::V0 or Test::More, or measuring coverage.
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.
playwright-interactive openai/skills · score 73/100 (grade C)
Persistent browser and Electron interaction through `js_repl` for fast iterative UI debugging.
poka-yoke github/awesome-copilot · score 73/100 (grade C)
Mistake-proof code so misuse cannot be expressed, rather than warning against it. Use when designing an interface, schema, or state machine and the user wants it hard to get wrong ("make invalid states unrepresentable", "so callers cannot screw it up", "type-safe API", "pit of success"); when auditing existing code for footguns ("what could bite us here", "what is easy to misuse", "poka-yoke this repo", "review this diff for ways to get it wrong"); or when a bug has recurred and the fix must close the class rather than the case ("make sure this never happens again", "this is the third time"). Especially for money, auth, permissions, deletion, migrations, and pipelines where failure is silent. Classifies every finding by what happens when the mistake occurs and how the device notices, which is what keeps it from collapsing into generic code review.
pw-review alirezarezvani/claude-skills · score 73/100 (grade C)
Review Playwright tests for quality. Use when user says "review tests", "check test quality", "audit tests", "improve tests", "test code review", or "playwright best practices check".
python-pro sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI.
python-testing affaan-m/ECC · score 73/100 (grade C)
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements. Use when writing pytest tests — fixtures, mocks, parametrization, or coverage.
python-testing affaan-m/everything-claude-code · score 73/100 (grade C)
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements. Use when writing pytest tests — fixtures, mocks, parametrization, or coverage.
python-testing-patterns sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
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.
quarkus-dev-services-and-testing github/awesome-copilot · score 73/100 (grade C)
Quarkus Dev Services and testing: zero-config containers, @QuarkusTest, @QuarkusIntegrationTest, test resources, RestAssured, @InjectMock, profiles and continuous testing. Use when writing or fixing tests in a Quarkus project.
receiving-code-review obra/superpowers · score 73/100 (grade C)
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
reviewing-oracle-to-postgres-migration github/awesome-copilot · score 73/100 (grade C)
Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting/collations, UNION ALL planner risks, materialized-view refresh requirements, timestamps, concurrent transactions, etc.). Use when planning a database migration, reviewing migration artifacts, or validating that integration tests cover Oracle/PostgreSQL differences.
scientific-writing sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Draft and revise scientific manuscripts with evidence-based structure, citation verification, reporting guidelines and venue-specific formatting.
screenshot openai/skills · score 73/100 (grade C)
Use when the user explicitly asks for a desktop or system screenshot (full screen, specific app or window, or a pixel region), or when tool-specific capture capabilities are unavailable and an OS-level capture is needed.
secops-detection-engineering google/skills · score 73/100 (grade C)
Author, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs, CVE disclosures, and Threat Detection Opportunities (TDOs) using synthetic UDM events and long-running coverage analysis. Don't use for alert triage (use secops-triage), deep forensic event reconstruction on infected hosts (use secops-investigate), or case management operations (use secops-cases).
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.
selector sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Select a specialized 100seotools skill from a plain-language SEO or project-documentation request. Use when the user needs help choosing the appropriate workflow.
seo-aeo-blog-writer sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Writes search-intent-led long-form articles with answer-first structure, FAQ coverage, internal links, and conversion paths for SEO and AEO.
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").
smoke-test bytedance/deer-flow · score 73/100 (grade C)
End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke test deployment", "verify installation", "test service availability", "end-to-end test", or similar.
springboot-verification affaan-m/ECC · score 73/100 (grade C)
Run the full Spring Boot verification loop — Maven or Gradle build, SpotBugs, PMD, and Checkstyle static analysis, unit and Testcontainers integration tests with JaCoCo coverage, OWASP dependency and secret scans, and diff review — producing a pass/fail readiness report. Use when preparing a Spring Boot pull request, validating coverage thresholds, or running pre-deploy verification.
springboot-verification affaan-m/everything-claude-code · score 73/100 (grade C)
Run the full Spring Boot verification loop — Maven or Gradle build, SpotBugs, PMD, and Checkstyle static analysis, unit and Testcontainers integration tests with JaCoCo coverage, OWASP dependency and secret scans, and diff review — producing a pass/fail readiness report. Use when preparing a Spring Boot pull request, validating coverage thresholds, or running pre-deploy verification.
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.
tdd-workflow affaan-m/ECC · score 73/100 (grade C)
Test-driven development workflow: write a failing test first, watch it fail, implement the smallest change to green, then refactor with 80%+ coverage across unit, integration, and E2E tests. Use when writing a new feature, fixing a bug, refactoring, or when told to write failing tests first.
tdd-workflow affaan-m/everything-claude-code · score 73/100 (grade C)
Test-driven development workflow: write a failing test first, watch it fail, implement the smallest change to green, then refactor with 80%+ coverage across unit, integration, and E2E tests. Use when writing a new feature, fixing a bug, refactoring, or when told to write failing tests first.
terraform-specialist sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert Terraform/OpenTofu specialist mastering advanced IaC automation, state management, and enterprise infrastructure patterns.
test-collaboration affaan-m/ECC · score 73/100 (grade C)
Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing test registry or TESTS.md. Use for test inventory, test gap analysis, unit/integration/contract/E2E/smoke classification, bug-to-test regression protection, consumer/provider contract testing, test-necessity review, and pre-delivery evidence review.
test-collaboration affaan-m/everything-claude-code · score 73/100 (grade C)
Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing test registry or TESTS.md. Use for test inventory, test gap analysis, unit/integration/contract/E2E/smoke classification, bug-to-test regression protection, consumer/provider contract testing, test-necessity review, and pre-delivery evidence review.
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
update-specification github/awesome-copilot · score 73/100 (grade C)
Update an existing specification file for the solution, optimized for Generative AI consumption based on new requirements or updates to any existing code.
webapp-testing ComposioHQ/awesome-claude-skills · score 73/100 (grade C)
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
webapp-testing anthropics/skills · score 73/100 (grade C)
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
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".
x-twitter-growth alirezarezvani/claude-skills · score 73/100 (grade C)
X/Twitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X/Twitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.
ab-test-store-listing Eronred/aso-skills · score 72/100 (grade C)
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see screenshot-optimization. For metadata optimization, see metadata-optimization.
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.
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.
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.
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.
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.
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.
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.
android_ui_verification sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Automated end-to-end UI testing and verification on an Android Emulator using ADB.
antithesis-workload antithesishq/antithesis-skills · score 72/100 (grade C)
Implement Antithesis workloads by turning the property catalog into SDK assertions and test commands, then refine coverage after triage.
aspnet-core openai/skills · score 72/100 (grade C)
Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.
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.
bio-crispr-screens-base-editing-analysis GPTomics/bioSkills · score 72/100 (grade C)
Analyzes base-editing screens for variant function. Covers library design (Hanna 2021 ClinVar-scale CBE screen benchmarked on BRCA1/2, Cuella-Martin 2021 DDR saturation), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end; 4-7 for ABE7.10), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic, variant annotation against ClinVar / COSMIC, and the Broad be-validation-pipeline. Use when designing a BE variant screen, choosing CBE vs ABE for a specific edit, interpreting bystander-confounded hits, distinguishing functional signal from indel artifact, integrating CRISPResso2 output with screen scoring, or deciding BE vs PE for SNV installation.
bio-proteomics-dia-analysis GPTomics/bioSkills · score 72/100 (grade C)
Analyzes data-independent acquisition (DIA) proteomics by scoring reconstructed fragment-chromatogram peak groups against a decoy null with DIA-NN (library-free directDIA, library-based, or deep-learning predicted-library routes), Spectronaut, OpenSWATH, and EncyclopeDIA. Frames the deliverable around q-value LEVEL (precursor/peptide/protein-group) and CONTEXT (run vs experiment-wide/global) rather than a bare "1% FDR", and around the duty-cycle-vs-selectivity acquisition tradeoff (window design, staggered demultiplexing, diaPASEF, narrow-window Astral). Use when identifying and quantifying proteins from DIA mass spectrometry runs and filtering DIA-NN report.parquet/matrix output. Building the spectral library itself is spectral-libraries; normalization and protein roll-up is quantification; statistical testing of the matrix is differential-abundance.
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.
bio-virtual-screening GPTomics/bioSkills · score 72/100 (grade C)
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
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.
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.
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.
browser-tools badlogic/pi-skills · score 72/100 (grade C)
Interactive browser automation via Chrome DevTools Protocol. Use when you need to interact with web pages, test frontends, or when user interaction with a visible browser is required.
bun-runtime affaan-m/ECC · score 72/100 (grade C)
Bun as runtime, package manager, bundler, and test runner. When to choose Bun vs Node, migration notes, and Vercel support.
bun-runtime affaan-m/everything-claude-code · score 72/100 (grade C)
Bun as runtime, package manager, bundler, and test runner. When to choose Bun vs Node, migration notes, and Vercel support.
c4-container sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Expert C4 Container-level documentation specialist.
consciousness-council K-Dense-AI/claude-scientific-skills · score 72/100 (grade C)
Structures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges. Simulates thinking archetypes, separates evidence from assumptions and values, and synthesizes a conditional recommendation. Use when the user requests a council, panel, devil's advocate analysis, "mind council", or deliberate comparison of perspectives on a difficult choice.
content-strategy alirezarezvani/claude-skills · score 72/100 (grade C)
When the user wants to plan a content strategy, decide what content to create, or figure out what topics to cover. Also use when the user mentions \"content strategy,\" \"what should I write about,\" \"content ideas,\" \"blog strategy,\" \"topic clusters,\" or \"content planning.\" For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit.
crossframe-org sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Use when CrossFrame Suite routes explicit Chinese analysis of teams, projects, organizations, responsibility chains, feedback write-back, repair, or retrospectives.
customer-billing-ops affaan-m/ECC · score 72/100 (grade C)
Operate customer billing workflows such as subscriptions, refunds, churn triage, billing-portal recovery, and plan analysis using connected billing tools like Stripe. Use when the user needs to help a customer, inspect subscription state, or manage revenue-impacting billing operations.
customer-billing-ops affaan-m/everything-claude-code · score 72/100 (grade C)
Operate customer billing workflows such as subscriptions, refunds, churn triage, billing-portal recovery, and plan analysis using connected billing tools like Stripe. Use when the user needs to help a customer, inspect subscription state, or manage revenue-impacting billing operations.
django-tdd affaan-m/ECC · score 72/100 (grade C)
Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs. Use when writing Django or DRF tests with pytest-django, or driving a Django feature test-first.
django-tdd affaan-m/everything-claude-code · score 72/100 (grade C)
Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs. Use when writing Django or DRF tests with pytest-django, or driving a Django feature test-first.
fda-qsr-audit-prep alirezarezvani/claude-skills · score 72/100 (grade C)
/compliance-os:fda-qsr-audit-prep [scope] — FDA 21 CFR 820 (QSR / QMSR) audit 6-question forcing interrogation. Post-Feb 2026 substantially harmonized with ISO 13485. Use before annual internal QSR audit, pre-FDA-inspection readiness, or Form 483 response.
firmware-pentest sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Firmware penetration testing following the OWASP FSTM nine-stage flow: extraction, EMBA automation, Firmadyne/QEMU emulation, AFL++ fuzzing, and hands-on exploitation in authorized labs.
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
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.
gke-cluster-autoscaler google/skills · score 72/100 (grade C)
Trigger on mention of GKE cluster autoscaler, node autoscaling, node pool auto-creation / node auto-provisioning. Provides guidance on enabling and optimizing cluster autoscaler, best practices, and troubleshooting issues such as nodes not scaling up or down, zonal stockouts, or capacity buffers. Do not use for ComputeClass-specific YAML generation or priority configuration (defer to gke-compute-classes skill).
gke-golden-path google/skills · score 72/100 (grade C)
Provides GKE golden path configuration defaults, production readiness checklists, and cluster default patterns. Use when designing GKE clusters, verifying GKE production readiness, or checking configurations against GKE defaults. Don't use for setting up workload autoscaling specifically (use gke-workload-scaling instead).
gke-upgrades google/skills · score 72/100 (grade C)
Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills instead).
google-cloud-filestore-autoscale google/skills · score 72/100 (grade C)
Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
hig-platforms sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Apple Human Interface Guidelines for platform-specific design.
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).
java-helidon github/awesome-copilot · score 72/100 (grade C)
Get best practices for developing applications with Helidon 4 (SE and MP). Use when working with Helidon SE or Helidon MP, HttpService routing, Helidon DB Client, MicroProfile Config, Helidon Security, or Helidon testing in Java 21+ projects.
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.
javascript-testing-patterns sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Comprehensive guide for implementing robust testing strategies in JavaScript/TypeScript applications using modern testing frameworks and best practices.
leiloeiro-ia sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Especialista em leiloes judiciais e extrajudiciais de imoveis. Analise juridica, pericial e de mercado integrada. Orquestra os 5 modulos especializados.
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.
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.
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.
migrate-to-shoehorn mattpocock/skills · score 72/100 (grade C)
Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.
mobile-audit briiirussell/cybersecurity-skills · score 72/100 (grade C)
Audit iOS and Android mobile applications against OWASP MASVS / MASTG — insecure storage, weak crypto, certificate pinning, deeplinks, IPC, jailbreak/root detection, reverse-engineering resistance. Use when the user mentions 'mobile security,' 'iOS security,' 'Android security,' 'mobile audit,' 'mobile pentest,' 'MASVS,' 'MASTG,' 'certificate pinning,' 'jailbreak detection,' 'root detection,' 'deeplink,' 'URL scheme,' 'app transport security,' 'keychain,' 'keystore,' 'mobile reverse engineering,' or has a mobile app to review.
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.
network-engineer sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Expert network engineer specializing in modern cloud networking, security architectures, and performance optimization.
notion-spec-to-implementation openai/skills · score 72/100 (grade C)
Turn Notion specs into implementation plans, tasks, and progress tracking; use when implementing PRDs/feature specs and creating Notion plans + tasks from them.
openapi-spec-generation sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contract compliance.
performance-profiler alirezarezvani/claude-skills · score 72/100 (grade C)
Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks, generates flamegraphs, analyzes bundle sizes, optimizes database queries, runs load tests with k6 and Artillery. Always measures before and after. Use when investigating a slow endpoint, planning a performance budget, or hunting a memory leak in production.
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.
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.
postmortem alirezarezvani/claude-skills · score 72/100 (grade C)
/em:postmortem — Honest analysis of what went wrong. Use after a failed launch, missed quarter, or bad hire to run a blameless 5-Whys retrospective with a change register — e.g. dissecting why the Q3 release slipped six weeks.
pulse alirezarezvani/claude-skills · score 72/100 (grade C)
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
qa garrytan/gstack · score 72/100 (grade C)
Fix browser/API/CLI/job/worker/webhook bugs. (gstack)
results-report Galaxy-Dawn/claude-scholar · score 72/100 (grade C)
This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first.
security-scanning-security-dependencies sickn33/antigravity-awesome-skills · score 72/100 (grade C)
You are a security expert specializing in dependency vulnerability analysis, SBOM generation, and supply chain security. Scan project dependencies across multiple ecosystems to identify vulnerabilities, assess risks, and provide automated remediation strategies.
security-scanning-security-sast sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Static Application Security Testing (SAST) for code vulnerability
senior-secops alirezarezvani/claude-skills · score 72/100 (grade C)
Senior SecOps engineer skill for application security, vulnerability management, compliance verification, and secure development practices. Runs SAST/DAST scans, generates CVE remediation plans, checks dependency vulnerabilities, creates security policies, enforces secure coding patterns, and automates compliance checks against SOC2, PCI-DSS, HIPAA, and GDPR. Use when conducting a security review or audit, responding to a CVE or security incident, hardening infrastructure, implementing authentication or secrets management, running penetration test prep, checking OWASP Top 10 exposure, or enforcing security controls in CI/CD pipelines.
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
spec-to-code-compliance sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Verifies code implements exactly what documentation specifies for blockchain audits. Use when comparing code against whitepapers, finding gaps between specs and implementation, or performing compliance checks for protocol implementations.
speckit-updater sickn33/antigravity-awesome-skills · score 72/100 (grade C)
SpecKit Safe Update
test-fixing sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Systematically identify and fix all failing tests using smart grouping strategies. Use when explicitly asks to fix tests (\"fix these tests\", \"make tests pass\"), reports test failures (\"tests are failing\", \"test suite is broken\"), or completes implementation and wants tests passing.
ui-demo affaan-m/ECC · score 72/100 (grade C)
Record polished UI demo videos using Playwright. Use when the user asks to create a demo, walkthrough, screen recording, or tutorial video of a web application. Produces WebM videos with visible cursor, natural pacing, and professional feel.
ui-demo affaan-m/everything-claude-code · score 72/100 (grade C)
Record polished UI demo videos using Playwright. Use when the user asks to create a demo, walkthrough, screen recording, or tutorial video of a web application. Produces WebM videos with visible cursor, natural pacing, and professional feel.
vuln-research briiirussell/cybersecurity-skills · score 72/100 (grade C)
Research a specific CVE or vulnerability disclosure end-to-end — what version is affected, is your code reachable, is there a public PoC, is there a patch, what's the exposure window, what's the mitigation if you can't patch immediately. Use when the user mentions 'CVE,' 'vulnerability research,' 'is this CVE relevant,' 'zero-day,' 'CISA KEV,' 'GitHub Security Advisory,' 'reachability analysis,' 'patch analysis,' 'exploit availability,' 'EPSS,' 'CVSS,' or 'should we drop everything and patch this.'
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.
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.
advogado-especialista sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Apoio a pesquisa juridica brasileira, organizacao de fatos e minutas, com verificacao em fontes oficiais e revisao profissional para casos concretos.
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.
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.
antithesis-setup-k8s antithesishq/antithesis-skills · score 71/100 (grade C)
Scaffold the Antithesis harness for customers running Kubernetes: Convert helm charts, kustomize templates, or raw Kubernetes manifests into a minimized set of manifests for Antithesis. Verify the Kubernetes manifests are in the correct shape with snouty validate and a local cluster deploy. Hands it off to antithesis-launch if the user wants to submit a run. At the end, the user is ready to run antithesis-workload to build tests. If the desired setup is docker-compose, defer to the antithesis-setup skill.
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.
application-integration-authoring google/skills · score 71/100 (grade C)
Builds, versions, publishes, tests, and executes Google Cloud Application Integration workflows through the REST API and Python discovery client, and promotes versions across environments. Use when listing integrations, downloading or uploading integration versions as JSON, configuring API triggers or config variables, publishing drafts, invoking integrations, or automating CI/CD promotion. Do not use for initial region provisioning and IAM setup (use application-integration-basics) or diagnosing failed runs and logs (use application-integration-troubleshooting).
architecture-patterns sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
aws-compliance-checker sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Automated compliance checking against CIS, PCI-DSS, HIPAA, and SOC 2 benchmarks
backtesting-frameworks sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
benchmark garrytan/gstack · score 71/100 (grade C)
Web performance regression detection. (gstack)
bio-alignment-indexing GPTomics/bioSkills · score 71/100 (grade C)
Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.
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.
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.
bio-pose-validation GPTomics/bioSkills · score 71/100 (grade C)
Validates docked / generated protein-ligand poses using PoseBusters physical-validity tests, strain energy quantification, geometric checks (planarity, vdW overlap, bond/angle distortion), and pose-energy reasonableness. Use when QC-ing docking results, comparing classical vs ML docking outputs, or filtering pose lists before SAR analysis.
bio-proteomics-spectral-libraries GPTomics/bioSkills · score 71/100 (grade C)
Builds and manages DIA spectral libraries as peptide query parameters (precursor m/z, a few fragment m/z plus relative intensities, normalized RT, optional CCS), covering experimental DDA, chromatogram, and in-silico predicted libraries via Koina-served Prosit, AlphaPeptDeep, MS2PIP, and DeepLC, with iRT/CiRT RT calibration, NCE tuning, format conversion (DIA-NN tsv/speclib/parquet, OpenSWATH pqp/TraML, Spectronaut, blib/dlib/elib), and library QC/merge. Use when generating, calibrating, converting, or merging a spectral library to drive a DIA search. Running the actual DIA search is dia-analysis; building from DDA identifications depends on peptide-identification; modified-peptide libraries route to ptm-analysis; quantifying the result is quantification.
bio-read-qc-rnaseq-qc GPTomics/bioSkills · score 71/100 (grade C)
Runs RNA-seq-specific post-alignment QC - strandedness inference, gene-body 5'-3' coverage, read distribution (exonic/intronic/intergenic), rRNA/globin/mitochondrial rate, transcript integrity (TIN), and saturation - with RSeQC, Qualimap, RNA-SeQC, and Picard. Use when validating RNA-seq libraries before quantification or differential expression, diagnosing degradation or gDNA contamination, or determining library strandedness. For raw-FASTQ QC use quality-reports; for UMI dedup use umi-processing.
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.
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.
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.
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).
change-impact affaan-m/ECC · score 71/100 (grade C)
Perform evidence-backed impact analysis before changing code, data, interfaces, or governance documents, then compare the planned impact with the actual diff after implementation. Covers call paths, data and schema, API contracts, tests, documentation, ADRs, deployment, migration, and rollback. Use for cross-module or high-risk changes, database migrations, authentication, public interfaces, blast-radius questions, pre-change checks, and post-implementation alignment.
change-impact affaan-m/everything-claude-code · score 71/100 (grade C)
Perform evidence-backed impact analysis before changing code, data, interfaces, or governance documents, then compare the planned impact with the actual diff after implementation. Covers call paths, data and schema, API contracts, tests, documentation, ADRs, deployment, migration, and rollback. Use for cross-module or high-risk changes, database migrations, authentication, public interfaces, blast-radius questions, pre-change checks, and post-implementation alignment.
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.
cicd-automation-workflow-automate sickn33/antigravity-awesome-skills · score 71/100 (grade C)
You are a workflow automation expert specializing in creating efficient CI/CD pipelines, GitHub Actions workflows, and automated development processes. Design and implement automation that reduces manual work, improves consistency, and accelerates delivery while maintaining quality and security.
code-documentation-doc-generate sickn33/antigravity-awesome-skills · score 71/100 (grade C)
You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user guides, and technical references using AI-powered analysis and industry best practices.
cold-email alirezarezvani/claude-skills · score 71/100 (grade C)
When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them. Use when the user mentions 'cold email,' 'cold outreach,' 'prospecting emails,' 'SDR emails,' 'sales emails,' 'first touch email,' 'follow-up sequence,' or 'email prospecting.' Also use when they share an email draft that sounds too sales-y and needs to be humanized. Distinct from email-sequence (lifecycle/nurture to opted-in subscribers) — this is unsolicited outreach to new prospects. NOT for lifecycle emails, newsletters, or drip campaigns (use email-sequence).
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.
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",...}).
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.
csharp-testing affaan-m/ECC · score 71/100 (grade C)
C# and .NET testing patterns with xUnit, FluentAssertions, mocking, integration tests, and test organization best practices. Use when writing or reviewing xUnit tests, mocks, or integration tests in a C# / .NET project.
csharp-testing affaan-m/everything-claude-code · score 71/100 (grade C)
C# and .NET testing patterns with xUnit, FluentAssertions, mocking, integration tests, and test organization best practices. Use when writing or reviewing xUnit tests, mocks, or integration tests in a C# / .NET project.
discord-bot-architect sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Specialized skill for building production-ready Discord bots.
distributed-debugging-debug-trace sickn33/antigravity-awesome-skills · score 71/100 (grade C)
You are a debugging expert specializing in setting up comprehensive debugging environments, distributed tracing, and diagnostic tools. Configure debugging workflows, implement tracing solutions, and establish troubleshooting practices for development and production environments.
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.
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.
documentation-generation-doc-generate sickn33/antigravity-awesome-skills · score 71/100 (grade C)
You are a documentation expert specializing in creating comprehensive, maintainable documentation from code. Generate API docs, architecture diagrams, user guides, and technical references using AI-powered analysis and industry best practices.
error-debugging-error-analysis sickn33/antigravity-awesome-skills · score 71/100 (grade C)
You are an expert error analysis specialist with deep expertise in debugging distributed systems, analyzing production incidents, and implementing comprehensive observability solutions.
finishing-a-development-branch obra/superpowers · score 71/100 (grade C)
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
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.
hybrid-cloud-architect sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Expert hybrid cloud architect specializing in complex multi-cloud solutions across AWS/Azure/GCP and private clouds (OpenStack/VMware).
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.
incident-response-smart-fix sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Investigate production issues, reproduce root causes, implement scoped fixes, and verify recovery using tests and observability.
ink google-labs-code/design.md · score 71/100 (grade C)
Ink terminal renderer for json-render that turns JSON specs into interactive terminal UIs. Use when working with @json-render/ink, building terminal UIs from JSON, creating terminal component catalogs, or rendering AI-generated specs in the terminal.
it-manager-pro sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Elite IT Management Advisor specializing in data-driven strategy, executive communication, and human-centric leadership for the 2026 digital era.
ito-training affaan-m/ECC · score 71/100 (grade C)
Inspect the availability of ML training on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed training manifest. Use after ito-compute has booked GPU nodes and the user wants pre-training, fine-tuning, or RL on that metal. ECC implements no training stack of its own.
ito-training affaan-m/everything-claude-code · score 71/100 (grade C)
Inspect the availability of ML training on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed training manifest. Use after ito-compute has booked GPU nodes and the user wants pre-training, fine-tuning, or RL on that metal. ECC implements no training stack of its own.
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.
kotlin-ktor-patterns affaan-m/ECC · score 71/100 (grade C)
Ktor server patterns including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing. Use when building a Ktor server — routing, plugins, auth, DI, serialization, or tests.
kotlin-ktor-patterns affaan-m/everything-claude-code · score 71/100 (grade C)
Ktor server patterns including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing. Use when building a Ktor server — routing, plugins, auth, DI, serialization, or tests.
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.
leiloeiro-mercado sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Analise de mercado imobiliario para leiloes. Liquidez, desagio tipico, ROI, estrategias de saida (flip/reforma/renda), Selic 2025 e benchmark CDI/FII.
leiloeiro-risco sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Analise de risco em leiloes de imoveis. Score 40 pontos, riscos juridicos/financeiros/operacionais, stress test 4 cenarios e ROI ponderado por risco.
logistics-exception-management sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Triage freight delays, damage, shortages, loss and carrier disputes; prepare evidence, recovery options and communications with jurisdiction-specific review.
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.
messages-ops affaan-m/ECC · score 71/100 (grade C)
Evidence-first live messaging workflow for ECC. Use when the user wants to read texts or DMs, recover a recent one-time code, inspect a thread before replying, or prove which message source was actually checked.
messages-ops affaan-m/everything-claude-code · score 71/100 (grade C)
Evidence-first live messaging workflow for ECC. Use when the user wants to read texts or DMs, recover a recent one-time code, inspect a thread before replying, or prove which message source was actually checked.
migrate alirezarezvani/claude-skills · score 71/100 (grade C)
Migrate from Cypress or Selenium to Playwright. Use when user mentions "cypress", "selenium", "migrate tests", "convert tests", "switch to playwright", "move from cypress", or "replace selenium".
nerdzao-elite-gemini-high sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Modo Elite Coder + UX Pixel-Perfect otimizado especificamente para Gemini 3.1 Pro High. Workflow completo com foco em qualidade máxima e eficiência de tokens.
nexrad-mosaic-construction sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Construct a quality-aware NEXRAD multi-radar mosaic from aligned single-site products with explicit coverage, beam geometry, quality weighting, overlap resolution, and provenance.
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.
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.
pester-should-migration github/awesome-copilot · score 71/100 (grade C)
Experimental (preview) Pester skill for migrating classic Should -Be (v5) assertion syntax to the new Should-* (v6) assertions (note the hyphen, no space), e.g. `Should -Be` -> `Should-Be`, `Should -Not -Be` -> `Should-NotBe`. Tracks Pester 6, which is still a release candidate, so this guidance may change; verified against Pester 6.0.0-rc2. Use when converting Pester v5 assertions to Pester v6 Should-* operators, modernizing a Pester test suite, or when a user asks to migrate, convert, or rewrite `Should -...` calls in .Tests.ps1 / PowerShell files.
product-discovery alirezarezvani/claude-skills · score 71/100 (grade C)
Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources.
react-testing affaan-m/ECC · score 71/100 (grade C)
React component testing with React Testing Library, Vitest/Jest, MSW for network mocking, accessibility assertions with axe, and the decision boundary between component tests and Playwright/Cypress end-to-end runs. Use when writing or fixing tests for React components, hooks, or pages.
react-testing affaan-m/everything-claude-code · score 71/100 (grade C)
React component testing with React Testing Library, Vitest/Jest, MSW for network mocking, accessibility assertions with axe, and the decision boundary between component tests and Playwright/Cypress end-to-end runs. Use when writing or fixing tests for React components, hooks, or pages.
report alirezarezvani/claude-skills · score 71/100 (grade C)
Generate test report. Use when user says "test report", "results summary", "test status", "show results", "test dashboard", or "how did tests go".
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.
roast alirezarezvani/claude-skills · score 71/100 (grade C)
Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, "convene the panel", get a brutal second opinion before building something, or says "/roast". Spins up a 5-angle panel (Critic, Champion, Analyst, Investigator, Customer) that attacks the idea from every angle, then a Judge returns one GO / RESHAPE / KILL verdict with the cheapest test to de-risk it.
scoutqa-test github/awesome-copilot · score 71/100 (grade C)
This skill should be used when the user asks to "test this website", "run exploratory testing", "check for accessibility issues", "verify the login flow works", "find bugs on this page", or requests automated QA testing. Triggers on web application testing scenarios including smoke tests, accessibility audits, e-commerce flows, and user flow validation using ScoutQA CLI. Use this skill proactively after implementing web application features to verify they work correctly.
screen-reader-testing sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Practical guide to testing web applications with screen readers for comprehensive accessibility validation.
security-best-practices openai/skills · score 71/100 (grade C)
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
senior-qa alirezarezvani/claude-skills · score 71/100 (grade C)
Generates unit tests, integration tests, and E2E tests for React/Next.js applications. Scans components to create Jest + React Testing Library test stubs, analyzes Istanbul/LCOV coverage reports to surface gaps, scaffolds Playwright test files from Next.js routes, mocks API calls with MSW, creates test fixtures, and configures test runners. Use when the user asks to "generate tests", "write unit tests", "analyze test coverage", "scaffold E2E tests", "set up Playwright", "configure Jest", "implement testing patterns", or "improve test quality".
sentry openai/skills · score 71/100 (grade C)
Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry CLI; perform read-only queries using the `sentry` command.
setup-pre-commit mattpocock/skills · score 71/100 (grade C)
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
spec garrytan/gstack · score 71/100 (grade C)
Turn vague intent into a precise, executable spec in five phases. (gstack)
tdd alirezarezvani/claude-skills · score 71/100 (grade C)
Run a red-green-refactor TDD workflow — generate failing tests first, implement to green, then check coverage gaps. Usage: /tdd <generate|coverage|validate> [target]
tugboat github/awesome-copilot · score 71/100 (grade C)
Anxiety-aware, evidence-driven collaboration for stalled or high-stakes work when a user says uncertainty, repeated setbacks, or lack of visible progress is causing significant anxiety or distress. Use immediately when explicitly invoked; when this fit is only inferred from the user''s own account, ask permission before applying it. Preserve the user''s ideal and turn grounded perspective-taking into persistent, bounded problem solving. Do not use to diagnose, provide therapy, manufacture certainty, or lower goals for reassurance.
v-development github/awesome-copilot · score 71/100 (grade C)
Guide GitHub Copilot through V language development: installing the toolchain, project layout with v.mod, building, testing, formatting, and writing idiomatic V including Option/Result error handling. Use when the user works with V source files, v.mod projects, or asks about V syntax, tooling, and conventions.
web-design-reviewer Galaxy-Dawn/claude-scholar · score 71/100 (grade C)
This skill enables visual inspection of websites running locally or remotely to identify and fix design issues. Triggers on requests like "review website design", "check the UI", "fix the layout", "find design problems". Detects issues with responsive design, accessibility, visual consistency, and layout breakage, then performs fixes at the source code level.
windows-desktop-e2e affaan-m/ECC · score 71/100 (grade C)
E2E testing for Windows native desktop apps (WPF, WinForms, Win32/MFC, Qt) using pywinauto and Windows UI Automation. Use when writing E2E tests for a Windows native desktop app with pywinauto or UI Automation.
windows-desktop-e2e affaan-m/everything-claude-code · score 71/100 (grade C)
E2E testing for Windows native desktop apps (WPF, WinForms, Win32/MFC, Qt) using pywinauto and Windows UI Automation. Use when writing E2E tests for a Windows native desktop app with pywinauto or UI Automation.
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.
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.
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.
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.
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.
antithesis-mutation-testing antithesishq/antithesis-skills · score 70/100 (grade C)
Validate that an Antithesis property catalog can actually catch bugs. For each safety property, inject one realistic mutant into the SUT, run it, and confirm the targeted property fires. Diagnoses survivors as a bad mutant, bad oracle, bad workload, or bad property, and routes fixes back to antithesis-workload or antithesis-research. Use once the harness is built and a baseline run is green.
api-design-principles sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers and stand the test of time.
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.
asc-workflow rudrankriyam/app-store-connect-cli-skills · score 70/100 (grade C)
Define, validate, run, resume, and audit repo-local multi-step automations with current `asc workflow` and `.asc/workflow.json`, including step outputs and safe release/TestFlight workflows.
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.
bio-alignment-filtering GPTomics/bioSkills · score 70/100 (grade C)
Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.
bio-clip-seq-crosslink-site-detection GPTomics/bioSkills · score 70/100 (grade C)
Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
bio-clip-seq-differential-clip GPTomics/bioSkills · score 70/100 (grade C)
Identify differentially bound regions across CLIP-seq conditions (knockdown vs control, treatment vs vehicle, disease vs healthy) using DEWSeq (sliding-window DESeq2), Flipper (Skipper-downstream), ASpeak, edgeR, or limma-voom. Use when computing condition-level changes in RBP binding intensity, choosing peak-level vs window-level vs crosslink-level testing, designing replicate experiments, or distinguishing biological binding shifts from technical confounders.
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.
bio-ctdna-mutation-detection GPTomics/bioSkills · score 70/100 (grade C)
Detects somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.
bio-filter-sequences GPTomics/bioSkills · score 70/100 (grade C)
Filter and select sequences by criteria (length, ID, GC content, N content, motifs, patterns, description) using Biopython, streaming so large files never load into RAM. Use when subsetting a FASTA/FASTQ file, removing unwanted or low-quality records, or selecting records by specific criteria. Use the paired-end-fastq skill instead whenever the input is paired R1/R2 reads.
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).
bio-genome-intervals-bedgraph-handling GPTomics/bioSkills · score 70/100 (grade C)
Generates, normalizes, and converts bedGraph signal tracks (4-column chrom/start/end/value, 0-based half-open) with bedtools genomecov, deepTools bamCoverage/bamCompare/bigwigCompare, bedtools unionbedg, and UCSC bedGraphToBigWig. Covers why a raw coverage bedGraph is not comparable across samples until normalized, the CPM/RPKM/BPM/RPGC normalization menu and the conserved-total assumption that makes them wrong under a global perturbation, the strict sorted-non-overlapping-chrom.sizes bedGraphToBigWig contract that silently corrupts a bigWig, effective-genome-size selection, and bin-size aliasing. Use when building or normalizing a coverage/signal track from a BAM, comparing tracks across samples or conditions, converting bedGraph to a browser-ready bigWig, or diagnosing a track that looks plausible but reports wrong heights.
bio-methylation-calling GPTomics/bioSkills · score 70/100 (grade C)
Extracts per-cytosine methylation calls from aligned bisulfite/EM-seq reads with bismark_methylation_extractor (Bismark BAM) or the aligner-agnostic MethylDackel/BISCUIT (bwa-meth BAM), producing the beta value M/(M+U) as a coverage file, bedGraph, or genome-wide cytosine report across CpG/CHG/CHH context. Covers conversion-rate QC as the first gate, the 5mC vs 5hmC summed caveat, variant-aware calling so a C/T SNP does not masquerade as unmethylation, paired-end --no_overlap double-counting, symmetric CpG dyad collapse, and the 0-based vs 1-based coordinate trap. Use when extracting methylation levels from a bisulfite/EM-seq alignment, choosing an extractor for a non-Bismark BAM, QC-ing conversion efficiency, or producing coverage/cytosine-report input for testing. For long-read MM/ML modification calling see long-read-sequencing/nanopore-methylation; for the upstream BAM see bismark-alignment; for per-CpG statistics see differential-cpg-testing.
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.
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
bio-ortholog-inference GPTomics/bioSkills · score 70/100 (grade C)
Pull pre-computed ortholog calls from public databases (OrthoDB, Ensembl Compara, OMA browser, eggNOG, PANTHER, KEGG Orthology, HomoloGene) via their REST APIs. Use when orthologs are already curated upstream, when the question is "what is the X ortholog of Y" rather than "how to infer orthology de novo", when batch-mapping gene IDs across species, or when comparing the resources for consensus calls. Encodes confidence-level semantics, 1:1 vs 1:many vs many:many, HomoloGene deprecation, and when to defect to de novo computation.
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.
bio-rna-quantification-count-matrix-qc GPTomics/bioSkills · score 70/100 (grade C)
Quality control and exploration of RNA-seq count matrices before differential expression. Use when checking library sizes and composition, choosing VST vs rlog for visualization, running PCA and sample correlation, detecting outliers with Cook's distance, deciding how to handle known vs unknown batch effects, screening for sample swaps, or judging whether a sample or design is too compromised to test.
bio-sam-bam-basics GPTomics/bioSkills · score 70/100 (grade C)
View, convert, and understand SAM/BAM/CRAM alignment files using samtools and pysam. Use when inspecting alignments, converting between formats, or understanding alignment file structure.
bio-small-rna-seq-mirdeep2-analysis GPTomics/bioSkills · score 70/100 (grade C)
Discovers novel miRNAs and quantifies known miRNAs with miRDeep2 by scoring genome-mapped read stacks against the Dicer/Drosha biogenesis signature. Use when deciding whether a study needs de novo discovery at all versus known-miRNA quantification; choosing the species and related-species miRBase references; reading the miRDeep2 score as a signal-to-noise hypothesis rather than a fixed cutoff; or filtering novel candidates against tRNA/rRNA loci to reject the classic false positives.
bio-variant-calling GPTomics/bioSkills · score 70/100 (grade C)
Call germline SNPs and indels from a BAM/CRAM with bcftools mpileup and call, and select the right calling engine for the job. Use when generating a VCF from aligned reads, choosing between bcftools, GATK HaplotypeCaller, DeepVariant, and DRAGEN, setting ploidy for haploid/organelle/polyploid/sex-chromosome calling, or deciding whether pileup-based calling is good enough versus a local-reassembly caller for indels and difficult regions. Not for cohort joint genotyping (see variant-calling/joint-calling), GATK-specific workflows (see variant-calling/gatk-variant-calling), deep-learning calling (see variant-calling/deepvariant), or somatic/low-VAF detection.
bio-workflows-clinical-trial-pipeline GPTomics/bioSkills · score 70/100 (grade C)
End-to-end clinical trial analysis workflow from CDISC SDTM/ADaM loading through ICH E9(R1) estimand-driven primary analysis to CONSORT 2025 regulatory-compliant reporting. Covers data preparation, FDA 2023 marginal vs conditional logistic regression, categorical tests with Boschloo, modern HTE/subgroup methods, missing-data sensitivity (MMRM, reference-based MI, Permutt tipping point), graphical multiplicity (Bretz-Maurer), survival analysis (Cox/RMST/competing risks) when applicable, and Table 1. Use when performing a complete analysis of clinical trial data.
bio-workflows-clip-pipeline GPTomics/bioSkills · score 70/100 (grade C)
End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding. Use when running the full Yeo lab eCLIP / iCLIP / iCLIP2 / iCLIP3 / irCLIP / PAR-CLIP analysis with SMInput control, protocol-specific UMI extraction, ENCODE STAR parameters, CLIPper or Skipper peak calling with stringent log2 FC and -log10 p thresholds, IDR rescue and self-consistency QC, and downstream motif registration with mCross or PEKA.
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.
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.
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).
blocking-io-guard bytedance/deer-flow · score 70/100 (grade C)
Ensure async-path backend code that could block the asyncio event loop is protected by a teeth-verified runtime anchor in tests/blocking_io/. Use when changing backend Python under app/, packages/harness/deerflow/, or scripts/, when running a blocking-IO triage round over the whole repo, or when a reviewer/CI asks for blocking-IO coverage. Runs a deterministic scan (changed-lines or full-repo), routes each candidate, drafts/extends an anchor, and proves it fails when the blocking IO regresses.
coding-standards affaan-m/ECC · score 70/100 (grade C)
Baseline cross-project coding conventions for naming, readability, immutability, and code-quality review. Use detailed frontend or backend skills for framework-specific patterns. Use when reviewing code quality or naming with no framework-specific skill that applies.
coding-standards affaan-m/everything-claude-code · score 70/100 (grade C)
Baseline cross-project coding conventions for naming, readability, immutability, and code-quality review. Use detailed frontend or backend skills for framework-specific patterns. Use when reviewing code quality or naming with no framework-specific skill that applies.
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.
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.
copilot-cli-quickstart github/awesome-copilot · score 70/100 (grade C)
Use this skill when someone wants to learn GitHub Copilot CLI from scratch. Offers interactive step-by-step tutorials with separate Developer and Non-Developer tracks, plus on-demand Q&A. Just say "start tutorial" or ask a question! Note: This skill targets GitHub Copilot CLI specifically and uses CLI-specific tools (ask_user, sql, fetch_copilot_cli_documentation).
credit-cycle-analysis sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Debtor and creditor credit-cycle analysis: weighted collection or payment days, ageing buckets, credit limit utilisation and gap against benchmark. Use for working-capital review.
csharp-nunit github/awesome-copilot · score 70/100 (grade C)
Get best practices for NUnit unit testing, including data-driven tests
csharp-tunit github/awesome-copilot · score 70/100 (grade C)
Get best practices for TUnit unit testing, including data-driven tests
dart-flutter-patterns affaan-m/ECC · score 70/100 (grade C)
Production-ready Dart and Flutter patterns covering null safety, immutable state with Freezed, async composition, widget architecture, state management (BLoC, Riverpod, Provider), GoRouter navigation with auth guards, Dio networking, error handling, and testing. Use when writing or reviewing Dart and Flutter code — state, widgets, navigation, networking, or architecture.
dart-flutter-patterns affaan-m/everything-claude-code · score 70/100 (grade C)
Production-ready Dart and Flutter patterns covering null safety, immutable state with Freezed, async composition, widget architecture, state management (BLoC, Riverpod, Provider), GoRouter navigation with auth guards, Dio networking, error handling, and testing. Use when writing or reviewing Dart and Flutter code — state, widgets, navigation, networking, or architecture.
data-breach-blast-radius github/awesome-copilot · score 70/100 (grade C)
Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.
error-diagnostics-error-trace sickn33/antigravity-awesome-skills · score 70/100 (grade C)
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging and evaluate monitoring quality.
fda-consultant-specialist alirezarezvani/claude-skills · score 70/100 (grade C)
FDA regulatory consultant for medical device companies. Provides 510(k)/PMA/De Novo pathway guidance, QMSR (21 CFR 820, which incorporates ISO 13485:2016 by reference since 2026-02-02; formerly QSR) compliance, HIPAA assessments, and device cybersecurity. Use when user mentions FDA submission, 510(k), PMA, De Novo, QMSR, QSR, ISO 13485 for FDA, premarket, predicate device, substantial equivalence, HIPAA medical device, or FDA cybersecurity.
frontend-mobile-development-component-scaffold sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Scaffold React and React Native components with TypeScript, accessibility, tests, styles, and documentation.
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.
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.
gen-specs-as-issues github/awesome-copilot · score 70/100 (grade C)
This workflow guides you through a systematic approach to identify missing features, prioritize them, and create detailed specifications for implementation.
google-cloud-slo-alert-configuration google/skills · score 70/100 (grade C)
Configures Cloud Monitoring PromQL-based Service Level Objective (SLO) alerting policies on Google Cloud for resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting policies.
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.
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".
idea-refine addyosmani/agent-skills · score 70/100 (grade C)
Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one. Triggers on "ideate", "refine this idea", or "stress-test my plan".
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.
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.
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).
interview-me addyosmani/agent-skills · score 70/100 (grade C)
Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.
mantis-history google/mantis · score 70/100 (grade C)
Analyzes the repository's version control system (VCS) history to extract past vulnerabilities, security fixes, and vulnerability patterns. Use as an initial pre-processing step to build a historical vulnerabilities database (workspace/historical_learnings.jsonl) that informs subsequent stages about past issues and fixes. Don't use for code reviews, writing test scripts, or patching code.
nasiko-control-plane affaan-m/ECC · score 70/100 (grade C)
Manage the experimental Nasiko CLI lifecycle through ECC — read-only status checks, consent-gated install of the pinned qualified version with dry-run preview, and ownership-checked uninstall, under explicit telemetry and secrets boundaries. Use when the user asks to install, inspect, or remove the Nasiko CLI or check whether it is present.
nasiko-control-plane affaan-m/everything-claude-code · score 70/100 (grade C)
Manage the experimental Nasiko CLI lifecycle through ECC — read-only status checks, consent-gated install of the pinned qualified version with dry-run preview, and ownership-checked uninstall, under explicit telemetry and secrets boundaries. Use when the user asks to install, inspect, or remove the Nasiko CLI or check whether it is present.
observability-monitoring-slo-implement sickn33/antigravity-awesome-skills · score 70/100 (grade C)
You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based engineering practices. Design comprehensive SLO frameworks, establish meaningful SLIs, and create monitoring systems that balance reliability with feature velocity.
passive-deal-screener alirezarezvani/claude-skills · score 70/100 (grade C)
Screens private investment opportunities from the passive LP (limited-partner) perspective — equity syndications, preferred equity, hard money / bridge funds, and private credit — pasted from any source (an investment platform listing, a direct GP email, raw terms). Produces a deal snapshot, stress-tests returns against public benchmarks, deconstructs the fee stack to a gross-to-net drag, surfaces severity-ranked red flags and missing disclosures, assesses GP alignment, and generates prioritized GP questions with bad-answer signals. Use whenever asked to analyze, evaluate, screen, or review a real-estate or private-market deal, syndication, offering, or investment opportunity — e.g. 'is this deal worth pursuing', 'what should I ask the GP', 'analyze this offering memo'. LP lens only; not operator-side underwriting (acquisition/development/asset-management). For corporate-finance DCF/ratio work use financial-analyst.
pci-audit briiirussell/cybersecurity-skills · score 70/100 (grade C)
Audit applications and infrastructure handling payment card data against PCI DSS v4.0. Heavy emphasis on scope determination (the single most-leveraged variable) plus the engineering-relevant requirements — Req 3 (storage of CHD), Req 4 (transmission), Req 6 (secure SDLC), Req 7-8 (access), Req 10 (logging), Req 11 (testing), Req 12 (program). Use when the user mentions 'PCI,' 'PCI DSS,' 'PCI DSS 4.0,' 'payment card,' 'cardholder data,' 'CHD,' 'PAN,' 'PCI scope,' 'PCI compliance,' 'SAQ,' 'AoC,' 'attestation of compliance,' 'tokenization,' 'P2PE,' 'network segmentation for PCI,' or audits any system that stores, processes, or transmits payment card data.
react-native-dev MiniMax-AI/skills · score 70/100 (grade C)
React Native and Expo development guide covering components, styling, animations, navigation, state management, forms, networking, performance optimization, testing, native capabilities, and engineering (project structure, deployment, SDK upgrades, CI/CD). Use when: building React Native or Expo apps, implementing animations or native UI, managing state, fetching data, writing tests, optimizing performance, deploying to App Store/Play Store, setting up CI/CD, upgrading Expo SDK, or configuring Tailwind/NativeWind.
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
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.
senior-pm alirezarezvani/claude-skills · score 70/100 (grade C)
Senior Project Manager for enterprise software, SaaS, and digital transformation projects. Specializes in portfolio management, quantitative risk analysis, resource optimization, stakeholder alignment, and executive reporting. Uses advanced methodologies including EMV analysis, Monte Carlo simulation, WSJF prioritization, and multi-dimensional health scoring. Use when a user needs help with project plans, project status reports, risk assessments, resource allocation, project roadmaps, milestone tracking, team capacity planning, portfolio health reviews, program management, or executive-level project reporting — especially for enterprise-scale initiatives with multiple workstreams, complex dependencies, or multi-million dollar budgets.
sepa-strategy himself65/finance-skills · score 70/100 (grade C)
Analyze stocks with Mark Minervini's SEPA (Specific Entry Point Analysis) methodology: stage analysis, the 8-condition trend template, fundamentals, VCP and other base patterns, pivot-point entries, market environment, and risk-based position sizing. Use this skill whenever the user mentions SEPA, Minervini, superperformance, the trend template, VCP (volatility contraction pattern), Stage 2, pivot or breakout entries, moving-average stacking (price above the 50/150/200-day MAs), breakout volume, position sizing from risk percentage, growth-stock screening or swing-trade entry criteria, or bases such as cup-with-handle, flat base, bull flag, or high tight flag. Also use it when the user asks "should I buy this stock" or "is this a good setup" about a growth or momentum name, or shares a chart for pattern analysis.
social-media-analyzer alirezarezvani/claude-skills · score 70/100 (grade C)
Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use when analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards. Also use when the user mentions "social media audit," "engagement rate," or "which platform performs best.
team-collaboration-issue sickn33/antigravity-awesome-skills · score 70/100 (grade C)
You are a GitHub issue resolution expert specializing in systematic bug investigation, feature implementation, and collaborative development workflows. Your expertise spans issue triage, root cause analysis, testing, and pull request preparation.
team-collaboration-standup-notes sickn33/antigravity-awesome-skills · score 70/100 (grade C)
You are an expert team communication specialist focused on async-first standup practices, AI-assisted note generation from commit history, and effective remote team coordination patterns.
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.
telegram-channel-ads sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Vet and price ad posts in Telegram channels: reach benchmarks by size, topic and language, ad-network and channel-age checks, CPM and deletion-window math.
typespec-api-operations github/awesome-copilot · score 70/100 (grade C)
Add GET, POST, PATCH, and DELETE operations to a TypeSpec API plugin with proper routing, parameters, and adaptive cards
understand-explain Egonex-AI/Understand-Anything · score 70/100 (grade C)
Use when you need a deep-dive explanation of a specific file, function, or module in the codebase
web-design-reviewer github/awesome-copilot · score 70/100 (grade C)
This skill enables visual inspection of websites running locally or remotely to identify and fix design issues. Triggers on requests like "review website design", "check the UI", "fix the layout", "find design problems". Detects issues with responsive design, accessibility, visual consistency, and layout breakage, then performs fixes at the source code level.
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.
xcode-build-benchmark AvdLee/Xcode-Build-Optimization-Agent-Skill · score 70/100 (grade C)
Benchmark Xcode clean and incremental builds with repeatable inputs, timing summaries, and timestamped `.build-benchmark/` artifacts. Use when a developer wants a baseline, wants to compare before and after changes, asks to measure build performance, mentions build times, build duration, how long builds take, or wants to know if builds got faster or slower.
xlsx anthropics/skills · score 70/100 (grade C)
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
yield-intelligence sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Passive income portfolio analysis — activate when user asks about dividend yields, Treasury rates, REIT income, monthly passive income goals, or portfolio yield optimization. Scans 4 asset classes, ranks by risk-adjusted return, and builds allocations targeting a specific monthly income.
ab-testing coreyhaines31/marketingskills · score 69/100 (grade C)
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
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
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.
bb-cli davidondrej/skills · score 69/100 (grade C)
Use this when controlling bb. The bb CLI inspects and manages threads, environments, projects, machines, providers, skills, plugins, settings, terminals, and other BB services.
bids K-Dense-AI/claude-scientific-skills · score 69/100 (grade C)
Organizes, queries, validates, and converts Brain Imaging Data Structure (BIDS) datasets. Supports organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.
bio-clip-seq-clip-peak-calling GPTomics/bioSkills · score 69/100 (grade C)
Call protein-RNA binding sites from CLIP-seq BAM with CLIPper, PureCLIP, Skipper, Piranha, omniCLIP, CTK, CLAM, or Paraclu. Use when choosing between coverage-based, HMM-based, beta-binomial window-based, and crosslink-site-based peak callers; applying ENCODE eCLIP thresholds (log2 IP/SMInput >= 3, -log10 p >= 3); deciding when SMInput is mandatory; or reconciling peak-set discordance between callers for the same RBP.
bio-consensus-sequences GPTomics/bioSkills · score 69/100 (grade C)
Generate consensus FASTA sequences by applying VCF variants onto a reference with bcftools consensus, or build viral/amplicon consensus with iVar. Use when reconstructing a sample-specific reference or haplotype, deciding -H haplotype vs IUPAC vs all-ALT projection, masking no-coverage sites so a consensus does not manufacture false reference calls, or setting iVar min-depth/min-frequency policy for surveillance genomes.
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.
bio-crispr-screens-mageck-analysis GPTomics/bioSkills · score 69/100 (grade C)
Analyzes pooled CRISPR screens with MAGeCK (Li et al 2014), covering count generation (mageck count), the RRA two-condition workflow (mageck test using alpha-RRA over per-sgRNA negative-binomial p-values), the MLE multi-condition workflow (mageck mle with explicit design matrix and beta-score output), normalization choice (median vs total vs control-sgRNA vs spike-in), sgRNA efficiency injection, paired-sample testing, time-course design, drug-screen versus dropout-screen design matrices, MAGeCKFlute and MAGeCK-VISPR downstream visualization, and decision logic for when to use MAGeCK vs JACKS / BAGEL2 / drugZ / Chronos. Use when running a fresh CRISPR screen analysis, picking RRA vs MLE for the experimental design, choosing a normalization method from QC signatures, debugging MLE convergence failure or NaN beta scores, comparing MAGeCK output across tools, or building a batch-aware multi-cell-line / multi-condition MLE design matrix.
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.
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.
bio-flow-cytometry-fcs-handling GPTomics/bioSkills · score 69/100 (grade C)
Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.
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.
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.
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.
bio-pathway-go-enrichment GPTomics/bioSkills · score 69/100 (grade C)
Runs Gene Ontology over-representation analysis (ORA) on a gene LIST with clusterProfiler enrichGO, the one-sided hypergeometric/Fisher 2x2 test phyper(k-1, M, N-M, n, lower.tail=FALSE). Covers why the BACKGROUND universe (not the gene list) is the null and decides significance, why omitting universe= is a bug, why enrichGO defaults to ont='MF' not 'BP', why pvalueCutoff filters p.adjust not raw p, why ORA discards effect magnitude and inherits GO-DAG true-path redundancy (simplify, topGO), why RNA-seq gene-length bias inflates long-gene terms (GOseq Wallenius), plus GeneRatio/BgRatio, bitr ID mapping, minGSSize/maxGSSize, groupGO. Use when a pre-selected gene list (DE hits, co-expression module, screen, GWAS-mapped) needs GO annotation. For a ranked no-cutoff analysis see gsea; for other databases see kegg-pathways, reactome-pathways, wikipathways; DE source is differential-expression/de-results; plots in enrichment-visualization.
bio-population-genetics-plink-basics GPTomics/bioSkills · score 69/100 (grade C)
Manages PLINK genotype filesets - format conversion (VCF, BED/BIM/FAM, PED/MAP, pgen/pvar/psam) and sample/variant QC (missingness, MAF, HWE, sex check, heterozygosity, KING relatedness) with PLINK 1.9 and 2.0. PLINK rewrites allele bookkeeping: PLINK 1.x A1 defaults to the minor allele and is recomputed every load, silently flipping effect-allele meaning unless --keep-allele-order, while PLINK 2.0 tracks explicit REF/ALT. QC order matters (variant before sample missingness), HWE is controls-only in 1.9 but not 2.0, add midp, and differential case/control missingness injects false hits. Use when converting between PLINK formats or running genotype QC before association, structure, or LD analysis. For LD pruning/clumping see linkage-disequilibrium; for GWAS see association-testing; VCF input from variant-calling/vcf-basics.
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.
bio-single-cell-splicing GPTomics/bioSkills · score 69/100 (grade C)
Analyzes alternative splicing at single-cell resolution. The first decision is library chemistry — 10X 3' is fundamentally limited (RT primes from poly-A, R2 falls in 3' UTR, <0.1 junction read per cell per AS event). Plate-based full-length methods (Smart-seq3, FLASH-seq, VASA-seq, STORM-seq) and single-cell long-read (MAS-Iso-seq, scISOr-Seq2) are the chemistries that give per-cell isoform structure. Tools include MARVEL (R, Smart-seq integrated), BRIE2 (Bayesian PSI with regulatory features and ELBO_gain test), scQuint (junction-cluster, plate-based; not for 10X), SpliZ (annotation-free Z-score), Psix (graph-smoothness regulated AS), and Sierra (alternative polyadenylation, often confused with AS). Use when analyzing isoform usage in scRNA-seq, identifying cell-type-specific splicing, or determining whether scRNA-seq chemistry supports splicing analysis at all.
bio-splice-variant-prediction GPTomics/bioSkills · score 69/100 (grade C)
Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (empirical 300K-RNA lookup of likely mis-splicing outcomes), CADD-Splice (composite score). Applies the ClinGen SVI 2023 framework for ACMG/AMP variant interpretation (PVS1, PP3, BP4 evidence codes), HGVS splicing nomenclature (c.123+1G>A, c.123-3T>G, r.spl?), extended-window scoring for deep-intronic pseudoexons, tissue-specific predictions, branchpoint variant detection (BPHunter, LaBranchoR), and splice-switching ASO design. Use when interpreting splice impact of clinical variants, prioritizing VUS, identifying deep-intronic pathogenic variants, or designing ASOs.
bio-temporal-genomics-circadian-rhythms GPTomics/bioSkills · score 69/100 (grade C)
Tests and estimates rhythmicity at a PRE-SPECIFIED period (canonically 24h) in time-series omics using cosinor regression (CosinorPy), JTK_CYCLE/ARSER/Lomb-Scargle meta-analysis (MetaCycle meta2d), and non-parametric tests for asymmetric waveforms (RAIN, DiscoRhythm); estimates phase (acrophase), amplitude, and MESOR, and controls FDR with an effect-size (rAMP) filter against over-detection. Use when testing for 24-hour or other known-period oscillations in a single condition (circadian, feeding-fasting, or light-dark experiments) and estimating their phase/amplitude. Not for unknown-period discovery (see temporal-genomics/periodicity-detection) or comparing rhythms between conditions (see temporal-genomics/differential-rhythmicity).
bio-temporal-genomics-temporal-clustering GPTomics/bioSkills · score 69/100 (grade C)
Clusters temporally variable genes by expression-profile SHAPE (not significance) using Mfuzz fuzzy c-means, TCseq, DEGreport degPatterns, and tslearn DTW/soft-DTW. Use when grouping pre-selected time-course genes into shared trajectory programs (co-expression modules), choosing between soft vs hard clustering, picking k, selecting a distance metric (Euclidean/correlation/DTW), or interpreting clusters with per-cluster enrichment. Requires temporally variable genes selected FIRST (differential-expression/timeseries-de or a variance filter); clustering is descriptive and downstream of selection, never a test of which genes are dynamic.
break-ui emilkowalski/skills · score 69/100 (grade C)
Try to break a piece of UI by feeding it worst-case data — long names, unbreakable emails, one-letter names, missing fields, huge counts, zero items, long labels, non-Latin text, emoji, extreme numbers — then render it behind a "Demo data / Worst case" toggle and report everything that broke, with the fix for each. Use when the user asks to stress-test, break, or find edge cases in a component or screen, or to "try the worst case". For visual design critique use emil-design-eng; for motion use review-animations.
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.
browser-automation alirezarezvani/claude-skills · score 69/100 (grade C)
Use when the user asks to automate browser tasks, scrape websites, fill forms, capture screenshots, extract structured data from web pages, or build web automation workflows. NOT for testing — use playwright-pro for that.
browser-harness davidondrej/skills · score 69/100 (grade C)
Direct browser control via CDP. Use when the user wants to automate, scrape, test, or interact with web pages. Connects to the user's already-running Chrome.
browser-skill Tencent/BrowserSkill · score 69/100 (grade C)
Automate the user's logged-in Chromium browser: read pages, fill forms, scrape data, operate tabs, test a UI, or debug a website. Requires the bsk CLI and browser extension.
cloud-monitoring-list-time-series-request google/skills · score 69/100 (grade C)
Generates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.
codebase-design mattpocock/skills · score 69/100 (grade C)
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
content-strategy coreyhaines31/marketingskills · score 69/100 (grade C)
When the user wants to plan a content strategy, decide what content to create, or figure out what topics to cover. Also use when the user mentions "content strategy," "what should I write about," "content ideas," "blog strategy," "topic clusters," "content planning," "editorial calendar," "content marketing," "content roadmap," "what content should I create," "blog topics," "content pillars," or "I don't know what to write." Use this whenever someone needs help deciding what content to produce, not just writing it. For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit. For social media content specifically, see social.
cs-karpathy-reviewer alirezarezvani/claude-skills · score 69/100 (grade C)
Reviews staged git changes against Karpathy's 4 coding principles. Runs complexity_checker on changed files, diff_surgeon on the diff, and produces a verdict with specific fix recommendations. Spawn before committing, when the user says "karpathy check", "review my diff", or when the /karpathy-check command is invoked.
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.
database-optimizer sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
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.
dd-meeting-prep anthropics/financial-services · score 69/100 (grade C)
Prepare for due diligence meetings — management presentations, expert network calls, customer references, and advisor sessions. Generates targeted question lists, benchmarks to reference, and red flags to probe. Use before any diligence meeting or call. Triggers on "prep for management meeting", "diligence call prep", "expert call questions", "customer reference questions", or "meeting prep for [company]".
debugging-and-error-recovery addyosmani/agent-skills · score 69/100 (grade C)
Guides systematic root-cause debugging. Use when tests fail, builds break, something that worked yesterday broke, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need to figure out what broke and why — a systematic approach to finding and fixing the root cause rather than guessing.
doc2math sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Convert narrative technical documents into grounded Mathematical Problem Specifications with variables, constraints, objectives, and uncertainty.
earnings-recap himself65/finance-skills · score 69/100 (grade C)
Analyze a company's most recent (or a specified past) earnings report from Yahoo Finance data (yfinance): actual vs estimated EPS, surprise size, revenue and margin trends, and the stock's price reaction. Use this skill whenever the user asks how earnings went — beat or miss, earnings surprise, quarterly results, the post-earnings move, or an earnings call recap — including casual references to a past report such as "AMZN reported last night" or "how did they do". For an upcoming report, use earnings-preview.
error-debugging-error-trace sickn33/antigravity-awesome-skills · score 69/100 (grade C)
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.
figma-use openai/skills · score 69/100 (grade C)
**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.
gke-node-notready google/skills · score 69/100 (grade C)
Diagnoses GKE nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health. Don't use for pod-level application failures (use gke-workload-troubleshooting), autoscaler scale-up/scale-down decisions (use gke-cluster-autoscaler), or non-GKE compute.
google-cloud-solution-architecture google/skills · score 69/100 (grade C)
Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution skills.
interview-system-designer alirezarezvani/claude-skills · score 69/100 (grade C)
This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
launch coreyhaines31/marketingskills · score 69/100 (grade C)
When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' 'product update,' 'how do I launch this,' 'site launch,' 'go live,' 'pre-launch QA,' 'launch checklist,' 'GTM plan,' 'we're about to ship,' 'changelog,' 'release notes,' or 'what did we ship this week.' Use this whenever someone is preparing to release something publicly. For ongoing marketing after launch, see marketing-ideas. For the offer being launched (bonuses, guarantees, scarcity, naming), see offers.
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.
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.
legacy-circuit-mockups github/awesome-copilot · score 69/100 (grade C)
Generate breadboard circuit mockups and visual diagrams using HTML5 Canvas drawing techniques. Use when asked to create circuit layouts, visualize electronic component placements, draw breadboard diagrams, mockup 6502 builds, generate retro computer schematics, or design vintage electronics projects. Supports 555 timers, W65C02S microprocessors, 28C256 EEPROMs, W65C22 VIA chips, 7400-series logic gates, LEDs, resistors, capacitors, switches, buttons, crystals, and wires.
macos-reverse sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Authorized macOS and Mach-O reverse engineering: codesign inspection, Objective-C/Swift recovery, endpoint-security surfaces, and Apple-platform malware analysis.
marketing-skills alirezarezvani/claude-skills · score 69/100 (grade C)
Directory and router for the marketing skills library. Use when you need to find the right marketing skill for a task, see what marketing capabilities exist, or get oriented in this plugin. 44 specialist skills across 8 pods (content, SEO + AEO, CRO, channels, growth, intelligence, sales enablement, ops), 59 stdlib Python tools. Routes to one skill — it does not execute marketing work itself.
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.
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).
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.
product-lens affaan-m/ECC · score 69/100 (grade C)
Validate the why before building through four product diagnostics — a YC-style product diagnostic that produces PRODUCT-BRIEF.md with a go/no-go recommendation, a founder review scoring product-market-fit signals, a user journey audit measuring time-to-value, and ICE feature prioritization. Use when pressure-testing product direction, choosing between features, sanity-checking a launch, or converting a vague idea into a product brief.
product-lens affaan-m/everything-claude-code · score 69/100 (grade C)
Validate the why before building through four product diagnostics — a YC-style product diagnostic that produces PRODUCT-BRIEF.md with a go/no-go recommendation, a founder review scoring product-market-fit signals, a user journey audit measuring time-to-value, and ICE feature prioritization. Use when pressure-testing product direction, choosing between features, sanity-checking a launch, or converting a vague idea into a product brief.
red-green-proof alirezarezvani/claude-skills · score 69/100 (grade C)
Turns a suspected bug into a proven one. Verify the cause against reality before claiming it, write a test that FAILS on the current code, apply the fix, watch it pass — then revert the fix and confirm the test goes red again, because a test that passes both ways proves nothing. Invoked bare after a debugging conversation, it takes the target from context rather than asking. Use when fixing a bug, investigating an incident, hardening a flaky area, or when asked to "add tests that reveal the bug". Triggers on "/red-green-proof", "prove the bug", "red-green", "make the test fail first", "is that test load-bearing", "reveal the bug with a test".
resume-tailor Paramchoudhary/ResumeSkills · score 69/100 (grade C)
Customize resume for specific job postings while maintaining truthfulness
retro garrytan/gstack · score 69/100 (grade C)
Weekly engineering retrospective. (gstack)
risk-management-specialist alirezarezvani/claude-skills · score 69/100 (grade C)
Medical device risk management specialist implementing ISO 14971 throughout product lifecycle. Provides risk analysis, risk evaluation, risk control, and post-production information analysis. Use when user mentions risk management, ISO 14971, risk analysis, FMEA, fault tree analysis, hazard identification, risk control, risk matrix, benefit-risk analysis, residual risk, risk acceptability, or post-market risk.
risky-changes davidondrej/skills · score 69/100 (grade C)
Verify assumptions before implementing large or risky changes to APIs, provider data, billing, pricing, quotas, or defaults. Use when a mistake could affect customers or the user asks if a change is safe to ship. Checks real-world impact beyond passing tests.
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.
soc2-audit-prep alirezarezvani/claude-skills · score 69/100 (grade C)
/compliance-os:soc2-audit-prep [scope] — SOC 2 Type II readiness 6-question forcing interrogation. Observation-period focused. Use before Type II observation begins, mid-period checkpoint, or pre-field-test month-10 readiness.
spec-to-repo alirezarezvani/claude-skills · score 69/100 (grade C)
Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and need a codebase', or provides a natural-language project specification and expects a complete, runnable repository. Stack-agnostic: Next.js, FastAPI, Rails, Go, Rust, Flutter, and more.
spm-build-analysis AvdLee/Xcode-Build-Optimization-Agent-Skill · score 69/100 (grade C)
Analyze Swift Package Manager dependencies, package plugins, module variants, and CI-oriented build overhead that slow Xcode builds. Use when a developer suspects packages, plugins, or dependency graph shape are hurting clean or incremental build performance, mentions SPM slowness, package resolution time, build plugin overhead, duplicate module builds from configuration drift, circular dependencies between modules, oversized modules needing splitting, or modularization best practices.
tdd mattpocock/skills · score 69/100 (grade C)
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
tdd-workflow sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Test-Driven Development workflow principles. RED-GREEN-REFACTOR cycle.
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.
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.
test-automator sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Master AI-powered test automation with modern frameworks, self-healing tests, and comprehensive quality engineering. Build scalable testing strategies with advanced CI/CD integration.
track-management sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Use this skill when creating, managing, or working with Conductor tracks - the logical work units for features, bugs, and refactors. Applies to spec.md, plan.md, and track lifecycle operations.
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.
vcpkg github/awesome-copilot · score 69/100 (grade C)
Guide for setting up vcpkg in C++ projects, managing dependency versions, and cross-compiling. Covers manifest initialization, CMake and Visual Studio integration, classic-to-manifest migration, version pinning, baselines, overrides, triplets, and cross-compilation. Use when a user is working with vcpkg project setup, installation, version management, or cross-platform builds. For specialized tasks, additional references cover custom registries and overlay ports (references/registries.md), CI/CD and binary caching (references/ci.md), and troubleshooting and dependency lifecycle (references/troubleshooting.md).
web-pentest briiirussell/cybersecurity-skills · score 69/100 (grade C)
Perform black-box / grey-box web application penetration testing on an authorized target — auth bypass, IDOR, session handling, business-logic flaws, parameter tampering, Burp Suite / OWASP ZAP workflows. Use when the user mentions 'web pentest,' 'web application penetration test,' 'pentesting,' 'bug bounty,' 'Burp Suite,' 'ZAP,' 'OWASP testing,' 'authentication testing,' 'session testing,' 'authorization testing,' 'business logic testing,' 'web vulnerability testing,' or has explicit authorization to test a live web application.
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.
ad-creative coreyhaines31/marketingskills · score 68/100 (grade C)
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'ChatGPT ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'motion video ad,' 'faceless video ad,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'Meta ad format tier list,' or 'creative format taxonomy.' Use it to produce or iterate ad copy at scale. Copy avoids AI tells like 'it's not X, it's Y' reveals. For campaign strategy and targeting, see ads. For landing page copy, see copywriting. Test hypotheses must be falsifiable, naming the metric, the comparison, and the expected direction.
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.
architect-review sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Master software architect specializing in modern architecture
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).
bio-causal-genomics-pleiotropy-detection GPTomics/bioSkills · score 68/100 (grade C)
Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAUSE, LHC-MR, LCV, MR-Clust, MR-Mix, and contamination-mixture methods. Use when validating an MR causal claim, running the STROBE-MR sensitivity battery, suspecting a shared heritable confounder, working under weak-instrument or polygenic-exposure regimes, or reconciling discordant estimates across robust methods.
bio-chipseq-allele-specific-binding GPTomics/bioSkills · score 68/100 (grade C)
Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.
bio-chipseq-cut-and-run-tag GPTomics/bioSkills · score 68/100 (grade C)
Analyzes CUT&RUN (Skene Henikoff 2017) and CUT&Tag (Kaya-Okur 2019) chromatin profiling data. Handles SEACR vs MACS2 peak calling (with the btaf375 2025 benchmark guidance), pA-MNase vs pA-Tn5 vs pAG-Tn5 chimera differences, E. coli spike-in carryover normalization, IgG-only control logic (no input), characteristic fragment-size signatures (25-75 bp for CUT&Tag), and lower depth requirements (5M reads typical vs 25M for ChIP). Use when calling peaks from CUT&RUN/CUT&Tag, scaling by E. coli spike-in carryover, choosing SEACR norm mode, or comparing CUT&RUN/Tag results to traditional ChIP.
bio-clip-seq-clip-preprocessing GPTomics/bioSkills · score 68/100 (grade C)
Preprocess CLIP-seq reads (eCLIP, iCLIP, iCLIP2, iCLIP3, irCLIP, PAR-CLIP, FLASH) with protocol-specific UMI extraction, adapter trimming, length filtering, and post-alignment PCR-duplicate collapse. Use when raw CLIP FASTQ must be turned into deduplicated, crosslink-preserving BAM input for peak calling; choosing between two-pass and single-pass adapter trimming; deciding minimum read length; or mapping UMI patterns to specific eCLIP/iCLIP/iCLIP2/iCLIP3 library preps.
bio-clip-seq-stamp-antibody-free GPTomics/bioSkills · score 68/100 (grade C)
Profiles RNA-binding protein targets without antibody or UV crosslinking using STAMP (APOBEC1-RBP fusion, C-to-U editing), scSTAMP (single-cell), TRIBE/HyperTRIBE (ADAR-RBP, A-to-I editing), DART-seq (APOBEC1-YTH for m6A), or Bullseye/SAILOR edit-site detection pipelines. Use when antibody is unavailable or specificity is doubtful, when single-cell RBP profiling is needed (scSTAMP), or when in vivo RBP profiling without UV is preferred.
bio-crispr-screens-prime-editing-screens GPTomics/bioSkills · score 68/100 (grade C)
Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2/PE3/PE3b/PEmax variants, MOSAIC in situ saturation mutagenesis, the PRIME pooled-screen methodology (Ren 2023; ~3,699 ClinVar variant screens), chromatin context as a major locus-level determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.
bio-epitranscriptomics-m6anet-analysis GPTomics/bioSkills · score 68/100 (grade C)
Detects m6A modifications from Oxford Nanopore direct-RNA-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller versions, or troubleshooting eventalign/dataprep failures.
bio-genome-assembly-assembly-qc GPTomics/bioSkills · score 68/100 (grade C)
Evaluates genome assembly quality across the three orthogonal axes - contiguity (QUAST auN/NG50/NGx, not bare N50), completeness (BUSCO/compleasm gene-space plus Merqury k-mer completeness), and correctness (reference-free Merqury QV, Inspector/CRAQ structural errors, asmgene false-duplication/collapse). Covers why N50 is the most-gamed metric, why QV measured on the polishing reads is circular, distinguishing uncollapsed haplotigs from real WGD, and the EBP/VGP 6.C.Q40 standard. Use when judging whether an assembly is good enough to annotate or publish, comparing assemblers, diagnosing a fragmented or duplicated assembly, or assessing a phased diploid assembly.
bio-longitudinal-monitoring GPTomics/bioSkills · score 68/100 (grade C)
Tracks ctDNA across serial liquid-biopsy timepoints for molecular residual disease (MRD) and treatment-response monitoring, treating MRD as a binary integrated detection call across the patient's full variant set (with a defined LoD95 and per-sample specificity) rather than a per-timepoint VAF threshold, and handling undetectable samples as left-censored at the per-sample limit of detection rather than true zeros. Covers tumor-informed bespoke vs tumor-naive design, landmark vs surveillance sampling, molecular-response definitions and their non-standardization, censoring-aware clearance kinetics, and the multiple-testing structure of repeated surveillance. Use when monitoring ctDNA during therapy, calling molecular relapse before imaging, or estimating clearance half-life from serial samples.
bio-pathway-gsea GPTomics/bioSkills · score 68/100 (grade C)
Tests a ranked gene vector for coordinated expression shifts in GO, KEGG, Reactome, or MSigDB gene sets with clusterProfiler's gseGO, gseKEGG, gsePathway, and GSEA (fgseaMultilevel engine), and scores per-sample pathway activity with ssGSEA and GSVA. Covers why a GSEA result is a deterministic function of three implicit choices (the ranking STATISTIC, the weight exponent p, and which LABELS are permuted), why the input must be a NAMED vector sorted DECREASING by a signed variance-calibrated metric (DESeq2 stat, limma t) not a raw p-value that erases direction, why preranked gene-permutation is anti-conservative for correlated sets (CAMERA is the fix), why nPerm is gone (eps governs tiny p), and why set.seed is required. Use when every gene carries a DE statistic, when a hard cutoff is arbitrary, or when ORA finds nothing. For gene-list ORA see go-enrichment; the ranking statistic comes from differential-expression/de-results.
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.
bio-proteomics-ptm-analysis GPTomics/bioSkills · score 68/100 (grade C)
Frames PTM/phosphoproteomics analysis as three stacked inference layers on a biased enrichment - chemistry selection, site localization (FLR), and protein-level-adjusted quantification with MSstatsPTM - plus kinase-activity and functional triage. Covers MaxQuant Phospho (STY)Sites multiplicity expansion, localization-probability filtering (class I, Ascore, ptmRS, DIA EG.PTMLocalizationProbabilities, DIA-NN PTM.Site.Confidence), false localization rate (LuciPHOr/DeepFLR), motif analysis with experiment-matched backgrounds, diGly/K-GG ubiquitin specificity, acetyl/glyco traps, and KSEA/PTM-SEA. Use when localizing and quantifying phosphorylation, acetylation, ubiquitination, or glycosylation sites from enrichment-based runs and deciding whether an apparent site change is real after subtracting protein abundance. Peptide ID and open/variable-mod search is peptide-identification; underlying protein-level quant is quantification and differential-abundance; DIA acquisition mechanics is dia-analysis.
bio-read-qc-contamination-screening GPTomics/bioSkills · score 68/100 (grade C)
Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via verifyBamID2/NGSCheckMate/somalier). Use when suspecting cross-contamination, PDX host reads, microbial carry-over, or sample swaps, and to decide whether to report, filter, or align to a combined reference. For deep taxonomic profiling use metagenomics/kraken-classification.
bio-rna-quantification-alignment-free-quant GPTomics/bioSkills · score 68/100 (grade C)
Quantify transcript expression from FASTQ with Salmon (selective alignment) or kallisto (pseudoalignment), bypassing genome mapping. Use when quantifying RNA-seq without alignment, deciding whether a decoy-aware index is required, detecting and verifying library strandedness, enabling GC and sequence bias correction, or choosing whether to generate inferential replicates (bootstraps/Gibbs) for transcript-level downstream testing.
bio-single-cell-differential-abundance GPTomics/bioSkills · score 68/100 (grade C)
Test whether cell-type proportions or composition changed between conditions in single-cell data using Milo (miloR), scCODA, sccomp, and propeller. Use when comparing cell-type proportions / composition between conditions, asking which populations expanded or contracted with treatment or disease, running neighborhood-level (cluster-free) abundance testing, or guarding against compositional shifts that masquerade as differential expression.
bio-single-cell-metabolite-communication GPTomics/bioSkills · score 68/100 (grade C)
Infers metabolite-mediated cell-cell communication from scRNA-seq by scoring enzyme-to-sensor pairs (MEBOCOST), with metabolic flux (scFEA), FBA state (Compass), and neurotransmitter (NeuronChat) alternatives. Use when studying metabolic crosstalk between cell types, predicting metabolite secretion and sensing, or deciding which metabolic-communication method fits and how speculative the result is.
bio-splicing-quantification GPTomics/bioSkills · score 68/100 (grade C)
Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters), VAST-TOOLS (cross-species with microexon support), Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage), or IRFinder-S (intron retention coverage-aware). Distinguishes the five canonical event classes (SE, A5SS, A3SS, MXE, RI), special classes (microexons, exitrons, AFE/ALE), intron retention subtypes (canonical RI vs detained introns), and applies effective-length normalization. Use when measuring splice-site usage or isoform inclusion ratios from short-read RNA-seq.
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.
board-deck-builder alirezarezvani/claude-skills · score 68/100 (grade C)
Assembles comprehensive board and investor update decks by pulling perspectives from all C-suite roles. Use when preparing board meetings, investor updates, quarterly business reviews, or fundraising narratives. Covers structure, narrative framework, bad news delivery, and common mistakes.
caveman-manage JuliusBrussee/caveman · score 68/100 (grade C)
Inspect Caveman Cloud's experiment lifecycle and block unsafe execution. Use when asked to start, approve, cancel, promote or roll back a Caveman experiment.
changelog-video heygen-com/hyperframes · score 68/100 (grade C)
Turn a weekly changelog .md into a finished branded changelog video (square 1080, ~45-60s, Annie VO, animated brand background, mock-UI visualizations, lowkey captions). Use when the user provides a changelog/digest markdown and wants the weekly video, or says "changelog video". Self-contained — fonts, background, lexicon, and scripts ship in this skill.
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).
csharp-xunit github/awesome-copilot · score 68/100 (grade C)
Get best practices for XUnit unit testing, including data-driven tests
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.
database-cloud-optimization-cost-optimize sickn33/antigravity-awesome-skills · score 68/100 (grade C)
You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.
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
django-celery affaan-m/ECC · score 68/100 (grade C)
Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
django-celery affaan-m/everything-claude-code · score 68/100 (grade C)
Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
error-diagnostics-error-analysis sickn33/antigravity-awesome-skills · score 68/100 (grade C)
You are an expert error analysis specialist with deep expertise in debugging distributed systems, analyzing production incidents, and implementing comprehensive observability solutions.
fastapi-patterns affaan-m/ECC · score 68/100 (grade C)
FastAPI best practices covering project structure, Pydantic v2 schemas, dependency injection, async handlers, authentication, authorization, transactional service layers, and testing with httpx and pytest. Use when building or reviewing FastAPI apps — Pydantic schemas, dependencies, async handlers, auth, or tests.
fastapi-patterns affaan-m/everything-claude-code · score 68/100 (grade C)
FastAPI best practices covering project structure, Pydantic v2 schemas, dependency injection, async handlers, authentication, authorization, transactional service layers, and testing with httpx and pytest. Use when building or reviewing FastAPI apps — Pydantic schemas, dependencies, async handlers, auth, or tests.
gke-ai-troubleshooting-tpu-reservation-stockout google/skills · score 68/100 (grade C)
Diagnose and resolve cluster-wide GKE TPU node pool creation or scale-up failures caused by Compute Engine reservation stockouts (GCE_STOCKOUT, ZONE_RESOURCE_POOL_EXHAUSTED) when existing unhealthy or NotReady TPU node pools in the cluster have node auto-repair disabled and hold reserved TPU capacity. Use when TPU node pool creation or scale-up fails with GCE_STOCKOUT, ZONE_RESOURCE_POOL_EXHAUSTED, or ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS despite having a specific Compute Engine TPU reservation. Don't use for general pod scheduling without a TPU reservation or workload-level container crashes.
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.
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.
linkedin-analytics alirezarezvani/claude-skills · score 68/100 (grade C)
Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Triggers on "why did my reach drop", "what's working on my LinkedIn", "analyze my posts", "do carousels do better for me", "should I test this", "LinkedIn analytics". Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below 10 posts.
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.
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).
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.
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]
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.
mdr-745-specialist alirezarezvani/claude-skills · score 68/100 (grade C)
EU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Covers Annex VIII classification rules, Annex II/III technical files, Annex XIV clinical evaluation, Art. 86 PSUR schedules, and EUDAMED integration. Use when classifying a medical device under MDR, building or gap-checking a technical file, planning clinical evaluation or PMS/PSUR cadence, or preparing for notified body review (e.g., 'what class is my device under MDR', 'review my PSUR schedule').
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.
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.
ponytail-review DietrichGebert/ponytail · score 68/100 (grade C)
Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last commit", "review my PR", "is this over-engineered", /ponytail-review.
postgresql sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
prospecting coreyhaines31/marketingskills · score 68/100 (grade C)
When the user wants to find, qualify, and build a list of prospects to reach out to, across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions "prospecting," "build a prospect list," "find leads," "lead list," "outbound list," "target account list," "ICP-fit accounts," "find local businesses," "find my first customers," "design partners," "signal-based outbound," "buying signals," "intent data," "job change alerts," "waterfall enrichment," "Clay table," "lookalike accounts," "catch-all emails," "account tiering," or "research this account before I reach out." Always verify emails before they reach a sequence, and never scrape LinkedIn. Define audiences in Sales Navigator and pull contacts from licensed data. Covers list building, signals, enrichment, verification, and account research. For the outreach itself (copy, sending setup, LinkedIn, cadences, replies), see cold-email. For researching competitors, see competitor-profiling.
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.
radio-sdr sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Authorized RF/SDR security research: signal identification, replay-feasibility study in shielded labs, and wireless protocol analysis within applicable spectrum and authorization constraints.
raffle-winner-picker ComposioHQ/awesome-claude-skills · score 68/100 (grade C)
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
retro mattpocock/skills · score 68/100 (grade C)
Conduct a retrospective on a coding session.
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.
springboot-tdd affaan-m/ECC · score 68/100 (grade C)
Test-driven development for Spring Boot using JUnit 5, Mockito, MockMvc, Testcontainers, and JaCoCo. Use when adding features, fixing bugs, or refactoring.
springboot-tdd affaan-m/everything-claude-code · score 68/100 (grade C)
Test-driven development for Spring Boot using JUnit 5, Mockito, MockMvc, Testcontainers, and JaCoCo. Use when adding features, fixing bugs, or refactoring.
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.
swift-protocol-di-testing affaan-m/ECC · score 68/100 (grade C)
Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing. Use when Swift code needs testing and file system, network, or external APIs must be mocked.
swift-protocol-di-testing affaan-m/everything-claude-code · score 68/100 (grade C)
Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing. Use when Swift code needs testing and file system, network, or external APIs must be mocked.
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.
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.
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.
thick-client sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Authorized security testing of desktop thick clients: local storage, update channels, IPC, traffic interception, and client-side trust-boundary review.
ui-ux-pro-max nextlevelbuilder/ui-ux-pro-max-skill · score 68/100 (grade C)
UI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation. Searchable local data: 79 searchable styles (50 active), 192 product palettes and reasoning profiles, 74 font pairings, 119 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.
what-happened entireio/skills · score 68/100 (grade C)
Explain why code looks the way it does by tracing the latest change for a file range or pasted snippet through `git blame` and deduplicated `entire checkpoint explain` lookups. Use when the user asks what happened, says "tell me why" about a code block, is confused about a section of code, asks "wtf is going on", "why is this like this", "why was this changed", or wants provenance for a specific file block.
wifi-wireless sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Authorized wireless security assessment: Wi-Fi capture, WPA handshake analysis, rogue AP detection research, and lab-only deauthentication testing.
android-aso Eronred/aso-skills · score 67/100 (grade C)
When the user wants to optimize their Google Play Store listing — title, short description, full description, keywords, ratings, or Play Store-specific features. Use when the user mentions "Google Play", "Android", "Play Store", "Play Console", "short description", "full description indexed", "Google Play ASO", or wants Google Play-specific keyword, creative, or ratings strategy. For iOS App Store optimization, see aso-audit and metadata-optimization.
app-store-optimization alirezarezvani/claude-skills · score 67/100 (grade C)
App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.
app-store-screenshots ParthJadhav/app-store-screenshots · score 67/100 (grade C)
Use when building App Store or Google Play screenshot pages, generating exportable marketing screenshots for iOS, macOS, and/or Android apps, or scaffolding a screenshot editor with Next.js. Triggers on app store, mac app store, play store, screenshots, marketing assets, html-to-image, phone mockup, mac mockup, android screenshots, feature graphic.
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".
bengali-nlp affaan-m/ECC · score 67/100 (grade C)
Bengali (Bangla) text processing patterns including Unicode normalization, script detection, tokenization, conjunct handling, and Bangla-specific NLP best practices for AI applications.
bengali-nlp affaan-m/everything-claude-code · score 67/100 (grade C)
Bengali (Bangla) text processing patterns including Unicode normalization, script detection, tokenization, conjunct handling, and Bangla-specific NLP best practices for AI applications.
bio-atac-seq-allele-specific-accessibility GPTomics/bioSkills · score 67/100 (grade C)
Detect allele-specific chromatin accessibility from ATAC-seq using WASP, GATK ASEReadCounter, or RASQUAL. Use when mapping cis-regulatory genetic variants from heterozygous SNPs, separating cis from trans regulation, building chromatin QTL (caQTL) maps, validating GWAS variant function with allelic imbalance, or detecting reference allele mapping bias before downstream analysis.
bio-atac-seq-enhancer-gene-linking GPTomics/bioSkills · score 67/100 (grade C)
Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2G), accessibility-only (Cicero), and orthogonal (HiChIP H3K27ac, EpiMap) approaches, validating predictions against CRISPRi-FlowFISH gold-standard, or building cell-type-specific regulatory maps for fine-mapping or therapeutic target discovery.
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.
bio-copy-number-cnvkit-analysis GPTomics/bioSkills · score 67/100 (grade C)
Detect somatic and germline copy number variants from targeted, exome, and whole-genome sequencing with CNVkit, a read-depth caller that combines on-target and off-target (antitarget) coverage. Covers panel-of-normals construction, flat-reference tumor-only calling, hybrid/amplicon/WGS modes, CBS vs HMM segmentation selection, purity-aware integer calling, and reconciliation against GATK and allele-specific callers. Use when calling CNVs from hybrid-capture panels or exomes, deciding whether CNVkit (depth-only) is the right tool versus an allele-specific caller, building a panel of normals, diagnosing flat-reference false positives, or interpreting log2 ratios into copy-number states.
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.
bio-data-visualization-forest-funnel-plots GPTomics/bioSkills · score 67/100 (grade C)
Build forest plots (HR, OR, RR, beta-coefficient summaries with CIs) and funnel plots (meta-analysis publication-bias diagnostics) using forestplot, metafor, ggforest, and MendelianRandomization with proper axis-scaling, summary-diamond placement, subgroup nesting, and Egger / trim-and-fill asymmetry tests. Use when summarizing effects across subgroups, trials, or instruments — meta-analysis, Mendelian randomization, subgroup HRs.
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.
bio-hi-c-analysis-hic-differential GPTomics/bioSkills · score 67/100 (grade C)
Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal comparison.
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.
bio-metagenomics-abundance GPTomics/bioSkills · score 67/100 (grade C)
Turns shotgun classifier output into a defensible abundance table with Bracken Bayesian re-estimation, then compositional treatment (CLR, zero handling), library-size normalization, reference-frame differential abundance, and optional absolute quantification. Covers why a relative-abundance change is not a change, why Bracken read fractions and MetaPhlAn percentages are different physical quantities, the silent -r read-length bias, the genome-size confound no library-size method fixes, and the rarefaction debate. Use when estimating species abundance from a Kraken2 report, normalizing a community count table, choosing a compositional transform, or converting relative to absolute load. For classification see kraken-classification; for diversity/ordination/DA mechanics see metagenome-visualization.
bio-methylation-array-qc-filtering GPTomics/bioSkills · score 67/100 (grade C)
Performs probe filtering and sample-level QC on Illumina Infinium methylation arrays (450K / EPIC / EPICv2) to decide which probes and samples to trust. Drops detection-p-failed and low-bead-count probes, removes cross-reactive/non-specific probes (Chen 2013 / Pidsley 2016 lists via maxprobes), excludes SNP-overlapping probes with dropLociWithSnps, and handles sex-chromosome probes. Collapses EPICv2 replicate probes with betasCollapseToPfx and harmonizes across array versions (EPICv2 hg38 vs 450K/EPIC hg19, intersect plus mLiftOver). Runs sample-identity QC: getSex sex prediction vs sample sheet for swap detection, rs-SNP fingerprint clustering for duplicates/swaps, and Sentrix chip/array-position batch diagnosis. Use when filtering methylation array probes, detecting sample swaps or mislabels, collapsing EPICv2 replicates, or merging 450K/EPIC/EPICv2 cohorts. For IDAT-to-corrected-beta normalization see array-preprocessing; for batch correction and study design see ewas-design.
bio-ncbi-datasets-cli GPTomics/bioSkills · score 67/100 (grade C)
Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assembly_summary.txt scraping and many EFetch workflows). Use when bulk-pulling genome assemblies, gene metadata across species, ortholog sets, or BLAST databases; when E-utilities are too slow for genome-scale work; or when automatic checksum verification, parallel download, and clean accession-driven retrieval are required. Encodes the JSON-lines output format, dataformat conversion, --dehydrated for cloud workflows, and when Datasets is/isn't the right tool.
bio-primer-design-primer-specificity GPTomics/bioSkills · score 67/100 (grade C)
Checks whether a PCR primer PAIR amplifies only the intended target genome-wide, using pair-aware in-silico PCR (MFEprimer-3.0, UCSC isPcr, NCBI Primer-BLAST) plus a primer3-py 3'-end-stability prefilter, against the correct database. Covers why plain BLAST is the wrong tool (it scores per-primer similarity, blind to 3'-terminal anchoring and to whether the two primers form a convergent amplicon in range), why a single 3'-terminal mismatch suppresses amplification while internal mismatches are tolerated, why intron-spanning RT-qPCR is defeated by processed pseudogenes that force a GENOME search not transcriptome-only, how to read a Primer-BLAST report (empty unintended-products means none passed its filter, not none exist), and that in-silico checking reduces but never replaces empirical validation. Use when confirming specificity, screening off-target amplicons, avoiding paralog/pseudogene hits, or checking SNPs under the 3' end. Design is primer-basics; dimers primer-validation; alignment read-alignment.
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.
bio-read-alignment-star-alignment GPTomics/bioSkills · score 67/100 (grade C)
Aligns RNA-seq reads to a genome with STAR, the fast splice-aware aligner whose splice-junction database (built from a GTF at sjdbOverhang = readlength-1) and two-pass mode set junction sensitivity, whose 255-for-unique MAPQ breaks GATK, and whose GeneCounts output reveals library strandedness. Use when RNA reads must be placed on the genome for novel-isoform discovery, fusion detection, RNA variant calling, coverage tracks, splicing QC, or single-cell (STARsolo). Memory-constrained RNA alignment is hisat2-alignment; DE on known transcripts only should skip alignment for rna-quantification/alignment-free-quant; the QC gate and contig-naming reconciliation are alignment-files; counting is rna-quantification; DNA is bwa-alignment/bowtie2-alignment.
bio-small-rna-seq-mirge3-analysis GPTomics/bioSkills · score 67/100 (grade C)
Quantifies known miRNAs, isomiRs, tRFs, and A-to-I editing fast with miRge3.0 by aligning collapsed reads to curated miRBase or MirGeneDB libraries. Use when choosing miRBase versus MirGeneDB as the reference; deciding whether to collapse isomiRs to the parent miRNA or keep 5'-isomiRs separate (they shift the seed and retarget); confirming the organism is among the six supported species; or remembering that RPM output is for display only and raw counts go to DESeq2/edgeR.
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.
bio-tcr-bcr-analysis-vdjtools-analysis GPTomics/bioSkills · score 67/100 (grade C)
Computes immune-repertoire diversity, clonal structure, overlap, and segment usage from TCR/BCR clonotype tables with VDJtools (immunarch as the modern R alternative). Use when deciding which diversity estimator answers a question (q=0 observed richness/chao1/chaoE, q=1 shannonWienerIndex, q=2 inverseSimpson as a Hill profile); normalizing sequencing depth before any cross-sample claim (DownSample or the resampled CalcDiversityStats table); choosing an overlap metric (depth-robust MorisitaHorn/F2 vs depth-biased Jaccard/public counts) and a clonotype match key (-i nt/aa, +/-V/J); summarizing clonality as 1 - normalizedShannonWienerIndex; reading spectratype and V-J usage under primer bias; interpreting public clonotypes; and choosing VDJtools (stable Java CLI) vs immunarch (active tidy R).
bio-workflow-management-nextflow-pipelines GPTomics/bioSkills · score 67/100 (grade C)
Authors reproducible Nextflow DSL2 pipelines built on reactive dataflow, where processes communicate only through channels and execution order is not guaranteed. Use when deciding channel/dataflow (Nextflow) vs rule-based (Snakemake) authoring; wiring queue vs value channels and fixing shared-reference exhaustion with .first(); composing DSL2 modules and subworkflows with take/main/emit; selecting container/conda profiles and pinning images by digest for portability across local/SLURM/LSF/AWS Batch/Google Batch/Kubernetes executors; diagnosing why -resume misses the cache (nondeterministic input order, mtime on network filesystems, mutable :latest tags) with cache 'lenient' and -dump-hashes; managing work/ vs publishDir and dynamic retry escalation; and choosing whether to adopt an nf-core community pipeline or author from scratch.
bio-workflows-edna-pipeline GPTomics/bioSkills · score 67/100 (grade C)
End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal (mandatory before DADA2 filterAndTrim), denoising with OBITools3 v3 (obi stats plural; DMS-based) or DADA2 ASVs (Callahan 2017), decontam combined method as screening-not-classifier (Davis 2018), tag-jumping (Schnell 2015) with a platform-dependent baseline (NovaSeq patterned flow cells ~10x MiSeq), Hill-number effective species counts with coverage-based rarefaction (Jost 2006; Chao & Jost 2012; doubling rule), beta-diversity decomposition with MANDATORY PERMANOVA + PERMDISP pair (Anderson & Walsh 2013), constrained ordination, and the read-counts-not-abundance critique (Lamb 2019). Use when processing eDNA samples for biodiversity assessment, deciding ASV vs OTU, configuring OBITools3 v3, interpreting decontam screening, or reporting community comparisons with the dispersion confound check.
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.
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.
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.
caveman-optimize JuliusBrussee/caveman · score 67/100 (grade C)
Turn a Caveman optimization observation into an operator-chosen candidate with a paired baseline evaluation. Use when asked to inspect or evaluate a Caveman optimization report. Needs explicit approval.
chart-visualization bytedance/deer-flow · score 67/100 (grade C)
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.
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.
competitive-analysis anthropics/financial-services · score 67/100 (grade C)
Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck. Also triggers on "who are the competitors to X", "benchmark X against peers", "build a market map", or any request to systematically evaluate competitive dynamics across an industry.
competitive-report-structure affaan-m/ECC · score 67/100 (grade C)
Assemble scored competitor profile cards (from benchmark-methodology) into a decision-grade competitive report with landscape map, competitor tiers, benchmarking matrix, white-space analysis, strategic recommendations, and team alignment trigger questions. Use when presenting competitive findings to leadership or a board, writing a competitive landscape report, or as the final step of the competitive analysis pipeline.
competitive-report-structure affaan-m/everything-claude-code · score 67/100 (grade C)
Assemble scored competitor profile cards (from benchmark-methodology) into a decision-grade competitive report with landscape map, competitor tiers, benchmarking matrix, white-space analysis, strategic recommendations, and team alignment trigger questions. Use when presenting competitive findings to leadership or a board, writing a competitive landscape report, or as the final step of the competitive analysis pipeline.
competitors coreyhaines31/marketingskills · score 67/100 (grade C)
When the user wants to create competitor comparison or alternative pages for SEO and buyer-facing use. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' 'competitive landing pages,' 'how do we compare to X,' 'competitor teardown,' 'audit our competitor pages,' 'are our comparison pages out of date,' or 'competitive asset audit.' Use this for any content that positions your product against competitors. Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. For auditing existing claims (not researching competitors from scratch, which is competitor-profiling; not technical SEO on these pages, which is seo-audit), use the asset audit here. For internal battle cards and sales-specific competitor docs, see sales-enablement.
copilot-spaces github/awesome-copilot · score 67/100 (grade C)
Use Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.
create-github-issues-for-unmet-specification-requirements github/awesome-copilot · score 67/100 (grade C)
Create GitHub Issues for unimplemented requirements from specification files using feature_request.yml template.
creating-oracle-to-postgres-migration-integration-tests github/awesome-copilot · score 67/100 (grade C)
Creates integration test cases targeting Oracle for .NET data access artifacts. Tests capture Oracle expected behavior as the authoritative baseline; they are written once and later ported to PostgreSQL by migrating the test project in Phase 6. Use only during Phase 3, before any PostgreSQL migration work has begun. Do not invoke during Phase 6 or against a project that has already been migrated.
data-manager-api-audience-ingestion google/skills · score 67/100 (grade C)
Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).
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.
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).
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.
image-enhancer ComposioHQ/awesome-claude-skills · score 67/100 (grade C)
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
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.
obsidian-markdown kepano/obsidian-skills · score 67/100 (grade C)
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax. Use when working with .md files in Obsidian, or when the user mentions wikilinks, callouts, frontmatter, tags, embeds, or Obsidian notes.
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.
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.
ponytail-audit DietrichGebert/ponytail · score 67/100 (grade C)
Quality audit of a whole repo: bugs, security holes, what breaks under real load, risky code without tests, slow paths, and what to delete, merge or split. Ranked, each finding explained in plain English. One-shot report, changes nothing. Use for "audit this codebase", "review the whole repo", "find bloat", "what can I delete", /ponytail-audit.
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.
python-pypi-package-builder github/awesome-copilot · score 67/100 (grade C)
End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI. Covers all four build backends (setuptools+setuptools_scm, hatchling, flit, poetry), PEP 440 versioning, semantic versioning, dynamic git-tag versioning, OOP/SOLID design, type hints (PEP 484/526/544/561), Trusted Publishing (OIDC), and the full PyPA packaging flow. Use for: creating Python packages, pip-installable SDKs, CLI tools, framework plugins, pyproject.toml setup, py.typed, setuptools_scm, semver, mypy, pre-commit, GitHub Actions CI/CD, or PyPI publishing.
sales-enablement coreyhaines31/marketingskills · score 67/100 (grade C)
When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'battle card,' 'battlecard,' 'competitive one-pager,' 'win-loss analysis,' 'why are we losing deals,' 'loss reasons,' 'how do I respond to this objection,' 'prospect just said,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps,' 'cold call script,' or 'voicemail script.' Use this for any document or asset that helps a sales team close deals. For public competitor comparison pages, see competitors. For running buyer interviews or churn research, see customer-research. For marketing website copy, see copywriting. For cold outreach emails, see cold-email. For the offer being sold (bonuses, guarantees, pricing structure), see offers.
siem-detection briiirussell/cybersecurity-skills · score 67/100 (grade C)
Engineer and audit SIEM detection rules — log source coverage, Sigma / KQL / SPL / Elastic query authoring, MITRE ATT&CK mapping, false-positive tuning, and detection-as-code workflows. Use when the user mentions 'SIEM,' 'detection engineering,' 'detection rules,' 'Sigma,' 'KQL,' 'SPL,' 'Splunk,' 'Sentinel,' 'Elastic,' 'Wazuh,' 'Chronicle,' 'detection-as-code,' 'MITRE ATT&CK mapping,' 'log coverage,' 'alert tuning,' 'use case development,' or needs help building or improving security detections.
stock-correlation himself65/finance-skills · score 67/100 (grade C)
Analyze how stocks move together using Yahoo Finance price history (yfinance): find correlated peers for a ticker, measure correlation, beta, and spread between specific tickers, cluster a group into a correlation matrix, and track rolling or regime-dependent correlation. Use this skill whenever the user asks what moves with a stock, what else drops when it drops, related tickers or sympathy plays, sector or supply-chain peers, pair trading or hedging pairs, beta or relative performance, correlation matrices, co-movement, or rolling/realized correlation — including well-known pairs like AMD/NVDA, GOOGL/AVGO, or LITE/COHR. With a single ticker, assume the user wants its correlated peers.
stock-liquidity himself65/finance-skills · score 67/100 (grade C)
Analyze how liquid a stock is using Yahoo Finance data (yfinance): bid-ask spreads, volume and dollar volume (ADTV), top-of-book and options depth, square-root market impact and slippage estimates, turnover ratio, and Amihud illiquidity, rolled into a liquidity grade. Use this skill whenever the user asks about liquidity or trading costs — how easily a position can be entered or exited, what a large order would do to the price, spread or execution-cost estimates, order book depth, volume patterns, or liquidity comparisons — especially for small caps, penny stocks, and thinly traded names.
tdd-workflows-tdd-green sickn33/antigravity-awesome-skills · score 67/100 (grade C)
Implement the minimal code needed to make failing tests pass in the TDD green phase.
threejs-materials cloudai-x/threejs-skills · score 67/100 (grade C)
Choosing and configuring three.js materials - unlit, diffuse, specular, PBR, toon, point and line materials - shared properties like blending and stencil, environment response, and the WebGPU node-material and TSL equivalents. Use when styling meshes or tuning material behavior.
ua-campaign Eronred/aso-skills · score 67/100 (grade C)
When the user wants to plan or optimize paid user acquisition campaigns. Also use when the user mentions "Apple Search Ads", "user acquisition", "paid ads", "UA", "ad campaign", "install campaign", "Facebook ads for apps", "TikTok ads", or "cost per install". For organic growth, see aso-audit. For launch-specific UA, see app-launch.
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.
benchmark affaan-m/ECC · score 66/100 (grade C)
Measure performance baselines and detect regressions across browser Core Web Vitals (LCP, INP, CLS, page weight), API endpoint latency percentiles, and build/test feedback times, with before/after comparison stored in git-tracked .ecc/benchmarks JSON. Use when checking page speed, responding to 'it feels slow' reports, verifying launch performance targets, or comparing stack alternatives.
benchmark affaan-m/everything-claude-code · score 66/100 (grade C)
Measure performance baselines and detect regressions across browser Core Web Vitals (LCP, INP, CLS, page weight), API endpoint latency percentiles, and build/test feedback times, with before/after comparison stored in git-tracked .ecc/benchmarks JSON. Use when checking page speed, responding to 'it feels slow' reports, verifying launch performance targets, or comparing stack alternatives.
bio-causal-genomics-colocalization-analysis GPTomics/bioSkills · score 66/100 (grade C)
Test whether two or more traits share a causal variant at a locus using Bayesian colocalization (coloc.abf, coloc.susie, HyPrColoc, moloc, eCAVIAR, SMR/HEIDI, PWCoCo, SharePro). Use when integrating GWAS with eQTL/sQTL/pQTL/mQTL, distinguishing shared causal variants from LD-driven coincidence, handling allelic heterogeneity, choosing between single-causal vs multi-causal methods, picking PP.H4 thresholds, running sensitivity over p12, or harmonising summary statistics for colocalization.
bio-clip-seq-clip-motif-analysis GPTomics/bioSkills · score 66/100 (grade C)
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
bio-ensembl-rest GPTomics/bioSkills · score 66/100 (grade C)
Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.
bio-flow-cytometry-cytometry-qc GPTomics/bioSkills · score 66/100 (grade C)
Quality control for flow, spectral, and mass cytometry - time-based anomaly cleaning (flowAI, flowCut, PeacoQC, flowClean), margin/boundary event removal, signal-drift detection, dead-cell exclusion, CyTOF Gaussian/DNA/event-length checks, instrument calibration/standardization (MESF, CS&T, peak-2), and batch-level outlier flagging. Use when assessing acquisition quality, choosing a cleaning tool, ordering QC relative to compensation, deciding margin removal before density-based steps, or flagging problematic samples before clustering or differential analysis.
bio-flow-cytometry-doublet-detection GPTomics/bioSkills · score 66/100 (grade C)
Detects and removes doublets/aggregates from flow, spectral, and mass cytometry before clustering or quantification. Covers FSC-A vs FSC-H singlet discrimination (the Area-Height non-proportionality, not a 1D area gate), FSC-W/SSC width gating, CyTOF Gaussian discrimination parameters (Center/Offset/Width/Residual/Event_length) and DNA intercalator gating, and the residual heterotypic conjugates that survive scatter gating and masquerade as double-positive populations. Use when filtering aggregates before phenotyping, choosing a doublet method for flow vs CyTOF, or diagnosing a suspicious double-positive cluster.
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.
bio-genome-assembly-metagenome-assembly GPTomics/bioSkills · score 66/100 (grade C)
Assembles microbial-community sequencing into metagenome-assembled genomes (MAGs) with metaFlye (ONT), metaSPAdes/MEGAHIT (Illumina), and hifiasm-meta/metaMDBG (PacBio HiFi), then recovers genomes via multi-binner consolidation (MetaBAT2, MaxBin2, CONCOCT, SemiBin2, VAMB -> DAS_Tool) and QCs them against MIMAG with CheckM2, GUNC, and GTDB-Tk. Covers why a metagenome is not a genome (uneven coverage, micro-diversity, strain collapse to consensus), differential-coverage binning, co-assembly vs per-sample, the rRNA-operon collapse that fails short-read MAGs, and strain resolution with inStrain. Use when reconstructing genomes from a microbiome, soil, ocean, or gut community, recovering MAGs, or resolving strain-level variation.
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.
bio-metabolomics-lipidomics GPTomics/bioSkills · score 66/100 (grade C)
Assigns honest lipid annotation levels, designs class-based internal-standard quantification, and runs lipid-aware differential and enrichment analysis with lipidr, guarding against in-source-fragment phantoms, sn-position over-claims, and invalid cross-class quantification. Use when naming or canonicalizing lipid species (shorthand separators, Goslin), deciding shotgun vs RP vs HILIC LC-MS, picking internal standards (SPLASH/EquiSPLASH), interpreting MS-DIAL/LipidSearch output, or comparing lipid classes. For general feature detection see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for non-lipid annotation confidence see metabolomics/metabolite-annotation; for normalization/QC see metabolomics/normalization-qc; for multivariate stats see metabolomics/statistical-analysis.
bio-metabolomics-metabolite-annotation GPTomics/bioSkills · score 66/100 (grade C)
Turns untargeted LC-MS/MS features (m/z, RT, MS/MS) into confidence-stratified metabolite annotations using spectral-library matching (matchms), in-silico tools (SIRIUS/CSI:FingerID, MetFrag) and molecular networking, and assigns a defensible MSI/Schymanski confidence level to each. Use when naming detected features, scoring MS/MS against a reference library, running SIRIUS, or deciding what confidence level an evidence set actually supports. For upstream feature extraction see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for downstream enrichment that must respect these levels see metabolomics/pathway-mapping; for lipid-specific structural annotation see metabolomics/lipidomics.
bio-metabolomics-msdial-preprocessing GPTomics/bioSkills · score 66/100 (grade C)
Runs the MS-DIAL preprocessing workflow (peak picking, MS2Dec spectral deconvolution, alignment, gap-filling) and imports the alignment-result table into R or Python with honest filtering. Use when preprocessing LC-MS DDA/DIA (SWATH) raw data with MS-DIAL, deciding MS-DIAL vs XCMS, configuring the MsdialConsoleApp console run, or parsing an MS-DIAL export into a clean feature matrix. For programmatic R peak detection and the feature-table-as-artifact framing see metabolomics/xcms-preprocessing; for lipid annotation mode see metabolomics/lipidomics; for MSI-level confidence honesty see metabolomics/metabolite-annotation; for drift correction and QC see metabolomics/normalization-qc.
bio-metagenomics-metaphlan GPTomics/bioSkills · score 66/100 (grade C)
Profiles shotgun metagenomes to species/SGB relative abundance with MetaPhlAn 4's clade-specific marker genes (bowtie2 short reads, minimap2 long reads). Covers why a MetaPhlAn percentage is a cell fraction (genome-size-normalized taxonomic abundance) and must never be merged with Kraken/Bracken read fractions, kSGB vs uSGB units for quantifying database-absent taxa, the unknown-fraction rescaling and its version-default flip, --index pinning as a batch variable, and when mOTUs3 or sourmash gather beat marker profiling. Use when profiling who-is-there with high precision, needing HMP-comparable species abundances, quantifying novel taxa, or deciding marker-gene vs k-mer profiling. For k-mer classification see kraken-classification; for strains see strain-tracking; for 16S amplicon see the microbiome category.
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.
bio-methylation-array-preprocessing GPTomics/bioSkills · score 66/100 (grade C)
Turns raw Illumina Infinium methylation BeadChip IDATs (450K, EPIC, EPICv2) into a defensible beta/M matrix with sesame (openSesame/SigDF) or minfi (RGChannelSet -> MethylSet -> GenomicRatioSet). Covers Type I vs Type II probe chemistry and why raw Type II beta is compressed, the signal-to-beta math (beta = M/(M+U+100)) and M-value logit, detection-p / pOOBAH masking including the out-of-band deletion-artifact catch, dye-bias correction, and the normalization decision (noob, funnorm, quantile, SWAN, BMIQ, dasen, sesame QCDPB). Use when reading IDATs, choosing a normalization for a 450K/EPIC/EPICv2 cohort, deciding beta vs M, masking failed probes, or producing the corrected matrix before testing. For probe/sample filtering, EPICv2 replicate collapse, and sample-identity QC see array-qc-filtering; for native long-read 5mC see long-read-sequencing/nanopore-methylation (a different platform).
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.
bio-phylo-species-trees GPTomics/bioSkills · score 66/100 (grade C)
Estimates species trees under the multispecies coalescent from per-locus gene trees with the modern ASTER astral binary (ASTRAL-III/wASTRAL/ASTRAL-Pro), plus SVDQuartets, BPP, and StarBEAST2. Covers why a species tree is not a gene tree, why each locus has its own genealogy that disagrees by incomplete lineage sorting (ILS) even with zero error, why concatenation is statistically inconsistent and positively misleading in the anomaly zone where more loci converge on the wrong tree with full support, why gene-tree estimation error biases summary methods, that localPP is not bootstrap and ASTRAL branch lengths are coalescent units, and how minority-quartet symmetry separates ILS from introgression. Use when multi-locus discordance, rapid radiations, anomaly-zone risk, concordance-factor interpretation, or concatenation-vs-coalescent choice arise. Routes per-locus gene-tree inference and gCF/sCF to modern-tree-inference, dating to divergence-dating, orthology to comparative-genomics/ortholog-inference.
bio-primer-design-primer-validation GPTomics/bioSkills · score 66/100 (grade C)
Validates chosen PCR/qPCR oligos for intramolecular thermodynamic liabilities with primer3-py - hairpins, self-dimers, cross-dimers (calc_hairpin/homodimer/heterodimer), and 3'-end stability (calc_end_stability) - returning ThermoResult dG/Tm and ASCII structures. Covers why a "dimer-free" verdict is a PREDICTION at the supplied salt/Mg/dNTP/oligo conditions and temp_c (so the same primer is fine or dimer-prone depending on conditions), why a 3'-END dimer or hairpin is the lethal class (polymerase-extendable into primer-dimer) so structures are ranked by dG at the annealing temperature and 3'-end involvement rather than global Tm, that ThermoResult dG is in cal/mol not kcal/mol, and that .structure_found must gate the numbers. Use when checking primer pairs before ordering, troubleshooting primer-dimers or smears, or screening oligos for secondary structure. Genome off-target/mispriming is primer-specificity; design is primer-basics; probe assays are qpcr-primers.
bio-proteomics-peptide-identification GPTomics/bioSkills · score 66/100 (grade C)
Peptide-spectrum matching from MS/MS with target-decoy FDR control, framing identification confidence as a property of a ranked list (q-value/PEP) rather than a raw engine score (XCorr, hyperscore, Andromeda, SpecEValue). Covers sequence-database search engines (Comet, MS-GF+, MSFragger, Sage, MaxQuant, MetaMorpheus), concatenated vs separate target-decoy competition, PEP vs q-value, the multi-level FDR cascade, open/mass-tolerant search, rescoring (Percolator, mokapot, MS2Rescore), and pyOpenMS SimpleSearchEngineAlgorithm + FalseDiscoveryRate. Use when identifying peptides from tandem mass spectra and deciding what FDR threshold to act on. Protein grouping and protein-level FDR are protein-inference; PTM site localization is ptm-analysis; DIA peptide-centric scoring is dia-analysis; intensity quant is quantification.
bio-proteomics-quantification GPTomics/bioSkills · score 66/100 (grade C)
Quantifies protein abundance from mass spectrometry using label-free (LFQ/MaxLFQ, DIA fragment-level), isobaric (TMT/iTRAQ reporter ions, MS2 vs SPS-MS3), and metabolic (SILAC) approaches, including peptide-to-protein summarization (Tukey median polish, MaxLFQ, msqrob), sample-loading and IRS cross-plex normalization, and isotopic impurity correction. Use when turning peptide/PSM/reporter signal into a protein-by-sample abundance matrix for downstream analysis. Statistical testing of that matrix is differential-abundance; DIA quant mechanics and DIA-NN runs are dia-analysis; reading search-engine outputs is data-import; razor/shared-peptide group assignment is protein-inference.
bio-read-alignment-bwa-alignment GPTomics/bioSkills · score 66/100 (grade C)
Aligns DNA short reads (paired- or single-end) to a reference genome with bwa-mem2, the maintained successor to BWA-MEM, for WGS/WES and germline/somatic variant-calling pipelines; covers index build, read-group injection, the collate/fixmate/sort/markdup ordering, soft-clipping for SV split reads, ALT/decoy-aware mapping on GRCh38, -K determinism, and streaming straight to a sorted BAM. Use when mapping DNA short reads to a reference for variant calling, coverage, ChIP/ATAC (alongside bowtie2-alignment), or SV detection. RNA-seq spliced alignment is star-alignment/hisat2-alignment; BAM sort/dedup/stats, the QC gate, and the cross-tool MAPQ scale are alignment-files; read trimming is read-qc; counting reads over features is rna-quantification.
bio-sashimi-plots GPTomics/bioSkills · score 66/100 (grade C)
Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA (LSV posteriors interactive HTML), leafviz (leafcutter clusters Shiny), Jutils (tool-agnostic heatmaps and sashimi for rMATS/leafcutter/MntJULiP/MAJIQ output), or pyGenomeTracks (multi-track publication figures). Tool choice depends on the upstream differential-splicing tool's output format and the publication vs interactive use case. Use when visualizing specific splicing events, validating differential splicing calls, or producing publication-quality figures.
bio-shape-similarity GPTomics/bioSkills · score 66/100 (grade C)
Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.
bio-small-rna-seq-trf-pirna-profiling GPTomics/bioSkills · score 66/100 (grade C)
Profiles non-miRNA small RNAs - tRNA-derived fragments (tRFs/tsRNAs), piRNAs, and rRNA/snoRNA-derived species - with MINTmap, unitas, SPORTS, and proTRAC. Use when annotating all small-RNA classes in a library; quantifying tRFs at locus resolution where tRNA loci are redundant (exclusive vs ambiguous); testing the piRNA ping-pong signature; deciding whether a species is a processed functional RNA or a degradation fragment; or judging whether the prep could even capture 5'-OH/cyclic-phosphate classes.
bio-splicing-qc GPTomics/bioSkills · score 66/100 (grade C)
Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.
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.
bio-workflow-management-nf-core-pipelines GPTomics/bioSkills · score 66/100 (grade C)
Runs and configures curated nf-core community Nextflow pipelines (rnaseq, sarek, atacseq, methylseq, ampliseq, taxprofiler, fetchngs) reproducibly, pinning the pipeline revision with -r and selecting a container engine and institutional config via -profile. Use when deciding to adopt a community pipeline versus author one from scratch; picking a pipeline and pinning its -r revision; selecting -profile test/docker/singularity/conda plus an institutional config from nf-core/configs; building and validating a samplesheet CSV against the pipeline schema (nf-schema); choosing --genome/iGenomes versus custom references; configuring resources and max_memory for SLURM/AWS Batch; using -resume and -stub; and reading MultiQC outputs.
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.
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.
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.
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.
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.
co-marketing coreyhaines31/marketingskills · score 66/100 (grade C)
When the user wants to find co-marketing partners, plan joint campaigns, or brainstorm partnership opportunities. Use when the user says 'co-marketing,' 'partner marketing,' 'joint campaign,' 'who should we partner with,' 'integration marketing,' 'cross-promotion,' 'collaborate with another company,' 'partnership ideas,' or 'co-brand.' For customer referral programs, see referrals. For launch-specific partnerships, see launch.
cold-email-writer Paramchoudhary/ResumeSkills · score 66/100 (grade C)
Write personalized cold outreach emails to hiring managers and founders — specific, human, not a pitch deck
commercial-forecaster alirezarezvani/claude-skills · score 66/100 (grade C)
Use when building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board number — especially when the CRO needs to walk the board through funnel math + cohort ARR + per-stage conversion assumptions without the theatre of a single undefended number. Decomposes pipeline into commit, best-case, and pipe-only tiers; projects cohort-level NRR/GRR to surface leaky cohorts before they show up in the consolidated number; scores per-stage funnel confidence so soft-floor stages get treated differently from high-confidence ones. Every output explicitly names the conversion rate used, the data window, and the weighting choice. For Head of Commercial, RevOps, VP Sales, and CRO at quarterly forecast or board prep. NOT financial close (see finance/financial-analysis). NOT strategic CRO hiring/territory (see c-level-advisor/cro-advisor). NOT pricing (see sibling pricing-strategist).
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.
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",...}).
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.
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.
generating-python-installer affaan-m/ECC · score 66/100 (grade C)
Commercial-grade Python installer expert for Windows: Nuitka extreme compilation, dist slimming, DLL footprint analysis, and Inno Setup packaging to ship the smallest, fastest installers. Use when a Python app must ship as a minimal, fast-starting Windows installer; not for basic script-to-exe conversion. 中文触发：Nuitka 极限优化、Python 商业打包、极限编译 Python、dist 瘦身、DLL 分析、最小安装包、最快启动、商业级打包风格
generating-python-installer affaan-m/everything-claude-code · score 66/100 (grade C)
Commercial-grade Python installer expert for Windows: Nuitka extreme compilation, dist slimming, DLL footprint analysis, and Inno Setup packaging to ship the smallest, fastest installers. Use when a Python app must ship as a minimal, fast-starting Windows installer; not for basic script-to-exe conversion. 中文触发：Nuitka 极限优化、Python 商业打包、极限编译 Python、dist 瘦身、DLL 分析、最小安装包、最快启动、商业级打包风格
investment-proposal anthropics/financial-services · score 66/100 (grade C)
Create professional investment proposals for prospective clients. Covers the firm's approach, proposed allocation, expected outcomes, and fee structure. Use when pitching new clients or presenting a new investment strategy. Triggers on "investment proposal", "prospect presentation", "pitch new client", "proposal for [client]", or "new client presentation".
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.
named-persona-adversarial-review alirezarezvani/claude-skills · score 66/100 (grade C)
Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Complements abstract-role adversarial review with named, sourced perspectives. Use when automated review findings feel generic, when a PR has architectural or UX impact, or when the author wants pre-submit hardening beyond standard checks.
obsidian-cli kepano/obsidian-skills · score 66/100 (grade C)
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their Obsidian vault, manage notes, search vault content, perform vault operations from the command line, or develop and debug Obsidian plugins and themes.
planning-oracle-to-postgres-migration-integration-testing github/awesome-copilot · score 66/100 (grade C)
Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.
pypict-skill sickn33/antigravity-awesome-skills · score 66/100 (grade C)
Pairwise test generation
scaffolding-oracle-to-postgres-migration-test-project github/awesome-copilot · score 66/100 (grade C)
Scaffolds an xUnit integration test project targeting Oracle in .NET solutions. Creates the test project, transaction-rollback base class, and seed data manager. Use only during Phase 3, before writing Oracle baseline integration tests. Do not invoke during Phase 6 — the PostgreSQL test project is produced by migrating this project, not by running this skill again.
screenshot-optimization Eronred/aso-skills · score 66/100 (grade C)
When the user wants to design, optimize, or evaluate App Store screenshots and preview videos. Also use when the user mentions "screenshots", "app preview", "product page design", "screenshot design", "creative assets", or "what should my screenshots show". For A/B testing screenshots, see ab-test-store-listing. For full ASO audit, see aso-audit.
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.
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.
startup-analysis himself65/finance-skills · score 66/100 (grade C)
Analyze a startup from three perspectives — VC investor, job applicant, and CEO/founder — covering market, traction, unit economics, team, defensibility, runway, equity value, culture, and competitive position, with a verdict for each. Use this skill whenever the user wants to evaluate a startup or private tech company: due diligence, whether to invest in it or join it, weighing a startup job offer, company health, outlook, or competitive position, or open-ended asks such as "what do you think of [company]" or "research [company] for me".
uncloud affaan-m/ECC · score 66/100 (grade C)
Use when managing an Uncloud cluster — deploying services, configuring Caddy ingress, adding static proxy routes for non-cluster devices, publishing ports, scaling, inspecting logs, or managing machines and volumes with the `uc` CLI.
uncloud affaan-m/everything-claude-code · score 66/100 (grade C)
Use when managing an Uncloud cluster — deploying services, configuring Caddy ingress, adding static proxy routes for non-cluster devices, publishing ports, scaling, inspecting logs, or managing machines and volumes with the `uc` CLI.
update-avm-modules-in-bicep github/awesome-copilot · score 66/100 (grade C)
Update Azure Verified Modules (AVM) to latest versions in Bicep files.
api-breaking-change-detector github/awesome-copilot · score 65/100 (grade C)
Cross-references C# Web API controllers/DTOs against their TypeScript/JavaScript consumers (React, Angular, Vue, Svelte, Node.js, or hand-written/auto-generated HTTP clients like Fetch, Axios, NSwag) to catch contract drift in both directions: backend changes that break client applications (renamed/removed JSON keys, new required parameters, status code shifts) and frontend code sending fields the backend no longer reads. Works directly against source code, not exported OpenAPI spec files. Use when the user asks to check for breaking API changes, verify frontend/backend contract sync, or audit a DTO/controller change against its TypeScript/JS consumers before merging. Not for generating new API code from a spec (see openapi-to-application-code) or scaffolding new endpoints (see aspnet-minimal-api-openapi).
app-icon-optimization Eronred/aso-skills · score 65/100 (grade C)
When the user wants to design, test, or improve their app icon to increase tap-through rate and conversions in App Store search and browse. Use when the user mentions "app icon", "icon design", "icon A/B test", "icon variants", "tap-through rate", "icon conversion", "icon refresh", or wants to know what makes a good app icon. For screenshot optimization, see screenshot-optimization. For full listing A/B tests, see ab-test-store-listing.
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.
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.
bio-causal-genomics-mediation-analysis GPTomics/bioSkills · score 65/100 (grade C)
Decompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR mediation, or double-ML medDML. Use when testing whether a molecular phenotype (expression, methylation, protein) mediates a treatment-outcome relationship, decomposing exposure-mediator interaction via VanderWeele 4-way, screening high-dimensional EWAS mediators, or running MR-based mediation when sequential ignorability is implausible.
bio-chipseq-visualization GPTomics/bioSkills · score 65/100 (grade C)
Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap (ComplexHeatmap-based), ChIPseeker tag heatmaps, and IGV batch screenshots. Handles bigWig normalization choices (CPM, BPM, RPGC, spike-in scaled), bamCompare operations (log2 ratio, subtract) with SES scaling, k-means clustering of heatmaps for biological subgrouping, and spike-in-scaled tracks for global-shift experiments. Use when generating publication-quality ChIP-seq signal heatmaps, profile plots, genome-browser tracks, or comparing samples visually.
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.
bio-experimental-design-multiple-testing GPTomics/bioSkills · score 65/100 (grade C)
Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.
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.
bio-free-energy-calculations GPTomics/bioSkills · score 65/100 (grade C)
Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda scheduling, soft-core potentials, MBAR/BAR analysis, cycle-closure validation, and protocol-appropriate enhanced sampling. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
bio-gene-regulatory-networks-differential-networks GPTomics/bioSkills · score 65/100 (grade C)
Compare gene co-expression and regulatory networks between biological conditions to find rewired relationships using DiffCorr, DiffCoEx, DINGO/iDINGO, and CoDiNA. Covers the differential-connectivity-is-not-differential-expression distinction, the pairwise multiple-testing explosion, marginal vs partial (direct) rewiring, and the underpowered-rewiring failure mode. Use when comparing co-expression networks between disease vs control, treatment, or developmental stages, or finding hub genes that rewire without changing mean expression. For single-condition modules see coexpression-networks; for differential expression of means see differential-expression/de-results.
bio-genome-annotation-functional-annotation GPTomics/bioSkills · score 65/100 (grade C)
Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.
bio-genome-assembly-long-read-assembly GPTomics/bioSkills · score 65/100 (grade C)
Assembles genomes de novo from noisy long reads (Oxford Nanopore R9/R10/Dorado, PacBio CLR) with Flye (repeat graph), Canu (correct-trim-assemble OLC), NextDenovo, Shasta, Raven, wtdbg2, or miniasm, and reconciles bacterial assemblies into a consensus with Trycycler/Autocycler. Covers matching the input flag to the basecaller era (--nano-hq vs --nano-raw), why a raw long-read assembly is contiguous but low-QV and not finished until polished, haplotig false-duplication and purge_dups, coverage and read-N50 as non-substitutable inputs, and mid-read adapter de-chimerization. Use when assembling a bacterial or eukaryotic genome from ONT or PacBio noisy reads, choosing a long-read assembler, or diagnosing an over-collapsed or duplicated assembly. For PacBio HiFi use hifi-assembly instead.
bio-imaging-mass-cytometry-spatial-analysis GPTomics/bioSkills · score 65/100 (grade C)
Analyze spatial cell-cell interactions, neighborhoods, and niches in IMC/MIBI data with squidpy and imcRtools, covering neighborhood-enrichment permutation nulls, the abundance-vs-density confound, inhomogeneous Ripley's K, cellular-neighborhood discovery, graph-construction (contact vs proximity), and edge effects. Use when testing whether cell types co-locate, choosing a spatial null, building a neighbor graph, discovering tissue niches, or deciding whether a spatial pattern is real or a density/segmentation artifact.
bio-long-read-sequencing-nanopore-methylation GPTomics/bioSkills · score 65/100 (grade C)
Calls DNA base modifications (5mC, 5hmC, 6mA, 4mC) directly from Oxford Nanopore and PacBio HiFi long reads encoded as MM/ML SAM tags, piles them into per-site bedMethyl with modkit (or pb-CpG-tools for PacBio), and produces phased allele-specific methylation. Covers why methylation is a basecalling decision that cannot be recovered later, the MM/ML tag-drop failure that silently zeroes methylation through alignment, the MM ? vs . no-call semantics, 5mC/5hmC resolution vs bisulfite, modkit's 10th-percentile auto-threshold, and the haplotagged ASM workflow. Use when calling 5mC/5hmC/6mA from a modBAM, generating bedMethyl, preserving methylation tags through alignment, doing allele-specific or differential methylation, or QC-ing a modification BAM.
bio-metagenomics-functional-profiling GPTomics/bioSkills · score 65/100 (grade C)
Profiles the functional potential of shotgun metagenomes with HUMAnN 3's tiered search (MetaPhlAn prescreen, Bowtie2 pangenome, translated DIAMOND vs UniRef), giving gene-family (RPK) and MetaCyc pathway abundances stratified by species. Covers why a metagenome measures potential not activity, why dropping UNMAPPED/UNINTEGRATED biases everything, why stratification is an estimate, coverage-vs-abundance and MinPath/gap-fill, UniRef90-vs-50 and biome database bias, and the assembly/eggNOG/dbCAN/antiSMASH alternatives. Use when obtaining pathway or gene-family abundances, regrouping to KO/EC/GO, normalizing functional tables, or choosing read-based vs assembly-based functional profiling. For AMR genes see amr-detection; for host-gene enrichment see pathway-analysis.
bio-multi-omics-similarity-network GPTomics/bioSkills · score 65/100 (grade C)
Stratifies patients into multi-omics subtypes by building one patient-by-patient similarity network per omic, fusing them with SNF's cross-network diffusion, and spectral-clustering the fused graph - then defending the clusters with stability, survival separation, and replication. Covers why spectral clustering always returns the requested cluster count so a subtype is a claim not a discovery, why the eigengap is a graph property not a biological truth, why fusion is not automatically better than the best single omic, why SNF needs complete data while NEMO handles mosaic cohorts, and the SNFtool API gotchas (dist2 returns squared distance, affinityMatrix width is sigma, spectralClustering K is the cluster count). Use when discovering patient subtypes from multiple omics, choosing a cluster number, validating subtypes, or handling partial multi-omic data. For feature-space factors see mofa-integration; for supervised signatures see mixomics-analysis; for survival see clinical-biostatistics/survival-analysis.
bio-phasing-imputation-haplotype-phasing GPTomics/bioSkills · score 65/100 (grade C)
Estimates haplotype phase from population linkage disequilibrium with SHAPEIT5, SHAPEIT4, Eagle2, or Beagle - turning unphased genotypes (0/1) into phased haplotypes (0|1) for imputation input, compound-heterozygote calls, HLA typing, or population genetics. Covers why statistical phase is an INFERENCE (not a measurement) whose error concentrates at rare variants, why a genome-wide switch-error rate hides catastrophic rare-variant error and must be reported MAC-stratified, the SHAPEIT5 common-scaffold-then-rare design (phase_common, ligate, phase_rare, switch), reference-based vs within-cohort phasing, the build-matched genetic map, chrX male-haploid handling, and the switch-vs-flip-vs-Hamming distinction. Use when phasing genotypes before imputation, for compound-het/ASE/HLA, or benchmarking against trios. Read-backed / molecular phasing (long reads, Hi-C) is long-read-sequencing/haplotype-phasing; panel choice is reference-panels; imputation is genotype-imputation.
bio-phasing-imputation-imputation-qc GPTomics/bioSkills · score 65/100 (grade C)
Assesses and filters phasing/imputation output - the quality metrics (Beagle DR2, Minimac R2 and EmpRsq, IMPUTE/GLIMPSE INFO), MAF-stratified filtering, true accuracy by masking, the differential-imputation confound, dosage-based downstream usage, and phasing switch-error QC. Covers why every routine quality score is an ESTIMATE of r2 from the posterior spread (not validation against truth), why it is confounded with MAF so a flat INFO>=0.3 cutoff is a hidden rare-variant filter, why concordance lies for rare variants while masked dosage-r2 by MAF is the gold standard, why separate case/control imputation manufactures false GWAS hits, and that the field name tells the tool (DR2=Beagle, R2=Minimac, INFO=GLIMPSE/IMPUTE). Use when filtering imputed variants before GWAS, validating accuracy, benchmarking phasing against trios, or diagnosing inflated association. Imputation is genotype-imputation; phasing is haplotype-phasing; panel ancestry is reference-panels; the test is population-genetics/association-testing.
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.
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.
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.
bio-proteomics-data-import GPTomics/bioSkills · score 65/100 (grade C)
Loads mass-spectrometry data into Python/R and strips the search engine's bookkeeping before any number is trusted -- removes decoys (REV__/Reverse), contaminants (CON__/Potential contaminant), Only-identified-by-site groups, and resolves semicolon razor/leading protein-ID ambiguity in MaxQuant proteinGroups.txt, DIA-NN report.parquet, and mzML/mzXML. Distinguishes Intensity (raw) vs LFQ intensity (MaxLFQ) vs iBAQ, treats a MaxQuant zero as missing (NaN, not log2(-inf)), and inherits the acquisition mode's missingness contract (DDA MNAR vs DIA MCAR). Use when starting an analysis from raw spectra or a search engine output. Downstream normalization and stats are differential-abundance; reporter-ion/MaxLFQ quant is quantification; protein grouping is protein-inference.
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.
bio-single-cell-cell-communication GPTomics/bioSkills · score 65/100 (grade C)
Infers ligand-receptor cell-cell communication from scRNA-seq with a consensus-first workflow (LIANA), plus CellPhoneDB specificity tests, CellChat pathway probabilities, and NicheNet downstream ligand-activity. Use when ranking ligand-receptor interactions between cell types, comparing communication across conditions, asking which ligand drives a receiver response, or deciding which CCC method and resource to trust.
bio-small-rna-seq-smrna-preprocessing GPTomics/bioSkills · score 65/100 (grade C)
Trims kit-specific 3' adapters, strips UMIs or 4N degenerate ends, size-selects, and collapses small RNA-seq reads (miRNA, piRNA, tRF) with cutadapt or fastp. Use when choosing the kit's 3' adapter; setting the size window (18-26 nt miRNA vs 24-32 nt piRNA); deciding whether a library carries a true UMI (QIAseq) versus a 4N debiasing spacer (NEXTflex); reading the read-length histogram to judge library quality; or deciding whether to collapse identical reads before mapping.
bio-spatial-transcriptomics-spatial-domains GPTomics/bioSkills · score 65/100 (grade C)
Identify spatially coherent tissue domains (regions like cortical layers, tumor vs stroma) in Visium, Visium HD, Xenium, MERFISH, Slide-seq, and Stereo-seq data with Squidpy, BANKSY, BayesSpace, STAGATE, and GraphST. Use when distinguishing a domain (a region with many cell types) from a cell type (one cell's identity) and a niche (local cell-type composition); choosing a domain method by tissue geometry (laminar/continuous vs high-resolution imaging vs non-contiguous); tuning the spatial-weight knob (BANKSY lambda, BayesSpace smoothing, SpaGCN histology weight, GNN graph radius) to avoid over-smoothing into blobs or under-smoothing into salt-and-pepper; choosing the number of domains k as a biological decision with k+-1 sensitivity; and reading the Yuan 2024 benchmark with the DLPFC continuous-laminar caveat.
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.
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.
bio-variant-calling-joint-calling GPTomics/bioSkills · score 65/100 (grade C)
Joint genotype a cohort of per-sample gVCFs with GATK (HaplotypeCaller -ERC GVCF -> GenomicsDBImport or CombineGVCFs -> GenotypeGVCFs) or GLnexus for DeepVariant gVCFs, producing a squared-off sample-by-site genotype matrix. Use when deciding between joint genotyping and merging single-sample callsets (never bcftools merge as absent==hom-ref), choosing GenomicsDBImport vs CombineGVCFs by cohort size and memory, solving the N+1 problem so a new sample does not force re-calling everyone, understanding cohort rescue of low-coverage het sites, handling the spanning-deletion star allele and GQ/PL recomputation at the joint step, scaling to biobank cohorts by interval sharding, or picking DeepVariant+GLnexus over the GATK path on throughput. Not for single-sample calling (see variant-calling/gatk-variant-calling) or VQSR/hard-filter mechanism (see variant-calling/filtering-best-practices).
clawhub-installer GPTomics/bioSkills · score 65/100 (grade C)
Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.
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.
cs-ceo-advisor alirezarezvani/claude-skills · score 65/100 (grade C)
Strategic leadership advisor for CEOs covering vision, strategy, board management, investor relations, and organizational culture. Use when a founder or CEO faces a company-level strategic decision — e.g., preparing the narrative and metrics for a quarterly board meeting, or stress-testing a pivot or market-expansion decision against vision, runway, and stakeholder expectations.
custom-product-pages Eronred/aso-skills · score 65/100 (grade C)
When the user wants to design, deploy, or measure Apple Custom Product Pages (CPP) — the alternate App Store product pages with different screenshots, preview videos, and promo text shown to users coming from specific URLs (typically ad campaigns or social posts). Use when the user mentions "Custom Product Page", "CPP", "alternate product page", "App Store URL variant", "ASA CPP", "campaign-specific landing page", "product page per audience", "App Store Connect CPP", "ppoUrl", "?cpp=" parameter, or "show different screenshots to different ad audiences". For App Store A/B tests on the default page, see ab-test-store-listing. For paid ad campaigns that route to CPPs, see apple-search-ads or ua-campaign.
design-taste-frontend Leonxlnx/taste-skill · score 65/100 (grade C)
tasteskill v2, the anti-slop frontend skill. Art direction for websites, distilled from a study of 247 curated gallery sites (One Page Love, Awwwards Sites of the Day). Deals researched directions (idea, composition, type, palette, photographs, section blueprints) from a library, enforces a strict no-slop house style with a real-browser inspector, and runs a look-and-fix loop on screenshots. Use this whenever you build, design, redesign, restyle, polish or review a landing page, marketing site, portfolio, product page, one-pager, hero or any public-facing web page, in any stack (HTML/CSS, React, Next.js, Vue, Svelte, Astro, Tailwind) — also when the user says a page looks generic, templated, "AI-made", sloppy, or asks to make it look designed, premium, award-level or less like every other site. Also for app screens: dashboards, admin and analytics views, settings, inboxes and other screens people work in, with their own run and rules.
discernment-nudge anthropics/skills · score 65/100 (grade C)
After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
engineer-system-change bytedance/deer-flow · score 65/100 (grade C)
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
gstack-openclaw-retro garrytan/gstack · score 65/100 (grade C)
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware with per-person contributions, praise, and growth areas. Use when asked for weekly retro, what shipped this week, or engineering retrospective.
gstack-upgrade garrytan/gstack · score 65/100 (grade C)
Upgrade gstack to the latest version.
ito-compute affaan-m/ECC · score 65/100 (grade C)
Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, revoke device credentials, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, validate GPU nodes, revoke Itô access, or rent or purchase GPU compute and needs the supported boundary explained.
ito-compute affaan-m/everything-claude-code · score 65/100 (grade C)
Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, revoke device credentials, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, validate GPU nodes, revoke Itô access, or rent or purchase GPU compute and needs the supported boundary explained.
javascript-typescript-jest github/awesome-copilot · score 65/100 (grade C)
Best practices for writing JavaScript/TypeScript tests using Jest, including mocking strategies, test structure, and common patterns.
motion-patterns affaan-m/ECC · score 65/100 (grade C)
Production-ready animation patterns for React / Next.js — button, modal, toast, stagger, page transitions, exit animations, scroll, and layout — built on motion-foundations tokens and springs. Use when animating a specific UI element in React or Next.js — button, modal, toast, stagger, page transition, or scroll.
motion-patterns affaan-m/everything-claude-code · score 65/100 (grade C)
Production-ready animation patterns for React / Next.js — button, modal, toast, stagger, page transitions, exit animations, scroll, and layout — built on motion-foundations tokens and springs. Use when animating a specific UI element in React or Next.js — button, modal, toast, stagger, page transition, or scroll.
project-guidelines-example affaan-m/ECC · score 65/100 (grade C)
Project-specific skill template covering architecture, patterns, testing, and deployment guidance.
project-guidelines-example affaan-m/everything-claude-code · score 65/100 (grade C)
Project-specific skill template covering architecture, patterns, testing, and deployment guidance.
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.
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.
react19-test-patterns github/awesome-copilot · score 65/100 (grade C)
Provides before/after patterns for migrating test files to React 19 compatibility, including act() imports, Simulate removal, and StrictMode call count changes.
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.
saas-valuation-compression himself65/finance-skills · score 65/100 (grade C)
Analyze how a private SaaS company's ARR valuation multiple changed across funding rounds, and attribute the compression or expansion to rate cycles and macro selloffs, growth deceleration, narrative shifts (including an AI premium), competition, and investor demand, benchmarked against private-market medians and peers. Use this skill whenever the user asks about valuation compression, ARR multiples, round-to-round valuation or multiple changes, down rounds, or wants to compare a VC-backed software company's funding rounds. Research the rounds rather than answering from memory.
salesforce-component-standards github/awesome-copilot · score 65/100 (grade C)
Quality standards for Salesforce Lightning Web Components (LWC), Aura components, and Visualforce pages. Covers SLDS 2 compliance, accessibility (WCAG 2.1 AA), data access pattern selection, component communication rules, XSS prevention, CSRF enforcement, FLS/CRUD in AuraEnabled methods, view state management, and Jest test requirements. Use this skill when building or reviewing any Salesforce UI component to enforce platform-specific security and quality standards.
stock-analysis alirezarezvani/claude-skills · score 65/100 (grade C)
Produce a rigorous, sector-relative, multi-factor fundamental analysis of a publicly listed company — Indian (NSE/BSE) or US/global. Use when the user asks to analyse, research, evaluate, or value a stock, ticker, or listed company; asks whether a business is fundamentally strong, cheap, or expensive; compares companies or benchmarks one against its sector; or mentions OPM, ROCE, ROE, ROIC, P/E, EV/EBITDA, free cash flow, NIM, GNPA, CASA, promoter holding or pledging. Use it for accounting-quality and forensic questions — "is the profit real", "why is profit rising but cash isn't", auditor qualifications, related-party concerns — which route to the forensic-only mode, and for IPOs and not-yet-listed companies — "should I apply to this IPO", DRHP/RHP or S-1 questions, price band, grey market premium — which route to the IPO mode. Use it even when the request sounds casual ("is Infosys any good?"). Do not use it for personalised investment advice, portfolio allocation, or trading signals.
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.
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.
update-markdown-file-index github/awesome-copilot · score 65/100 (grade C)
Update a markdown file section with an index/table of files from a specified folder.
asc-crash-triage rudrankriyam/app-store-connect-cli-skills · score 64/100 (grade D)
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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.
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.
bio-chipseq-peak-annotation GPTomics/bioSkills · score 64/100 (grade D)
Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CA-CTCF/CA-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to target genes, classifying peaks against ENCODE cCRE registry, or running gene-set enrichment on peak-associated genes.
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.
bio-comparative-genomics-introgression-detection GPTomics/bioSkills · score 64/100 (grade D)
Detect introgression and admixture between species or populations using Dsuite (Malinsky 2021 fast D-statistics), Patterson's D / ABBA-BABA test (Green 2010; Durand 2011), f4-ratio and f-branch statistic (Malinsky 2018), TreeMix (Pickrell & Pritchard 2012), HyDe (Blischak 2018), QuIBL (Edelman 2019), sprime (Browning 2018), Twisst (Martin 2017), PhyloNet (Than 2008) for explicit phylogenetic networks, and qpAdm / qpGraph (Patterson 2012). Distinguish introgression from incomplete lineage sorting (ILS), ancestral structure, ghost-lineage admixture, and rate variation. Use when testing inter-species gene flow, dating admixture events, identifying introgressed segments, building phylogenetic networks for reticulate evolution, or applying the ABBAclustering (Koppetsch-Malinsky-Matschiner 2024) framework for divergent-species gene flow.
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.
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.
bio-data-visualization-multipanel-figures GPTomics/bioSkills · score 64/100 (grade D)
Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.
bio-data-visualization-statistical-annotation GPTomics/bioSkills · score 64/100 (grade D)
Add p-value brackets, significance asterisks, and effect-size annotations to distribution plots using ggpubr, ggsignif, and statannotations with correct test selection (parametric vs non-parametric vs paired), multiple-testing adjustment, and rendering of negative results. Use when a boxplot/violin/raincloud needs in-figure statistical comparisons between groups.
bio-differential-expression-de-results GPTomics/bioSkills · score 64/100 (grade D)
Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.
bio-ecological-genomics-landscape-genomics GPTomics/bioSkills · score 64/100 (grade D)
Tests genotype-environment associations and identifies adaptive loci while correcting for the four-confound landscape (structure, demography, background selection, sampling design) using LFMM2 with mandatory K via sNMF cross-entropy elbow (LEA 3), BayPass Core/AUX/C2/IS with Omega covariance matrix, RDA / pRDA for polygenic adaptation (Forester 2018; requires imputed genotypes), OutFLANK with trimmed FST null, pcadapt, gradient forests (Ellis-Smith-Pitcher 2012, NOT mis-cited Ellis-Manel), Capblancq & Forester 2021 RDA Swiss-army-knife, genomic-offset prediction with Lind & Lotterhos 2025 three-regime caveat, Lotterhos-Whitlock sampling optima, Wang & Bradburd 2014 IBD vs IBE, and Circuitscape + ResistanceGA. Use when identifying adaptive loci across gradients, choosing K for LFMM2, deciding among GEA methods, predicting maladaptation with the novel-environment caveat, distinguishing IBD vs IBE, or optimizing sampling design.
bio-genome-annotation-annotation-qc GPTomics/bioSkills · score 64/100 (grade D)
Assesses the quality and completeness of a genome annotation with BUSCO (conserved single-copy ortholog recovery), OMArk (proteome completeness, consistency, and contamination), CheckM2 (prokaryotic completeness/contamination), and a gene-set sanity panel (gene count, mono-exonic fraction, protein-length distribution, mRNA:gene ratio, coding density). Covers the assembly-BUSCO-vs-proteome-BUSCO diagnostic, what BUSCO-Duplicated really means, why gene count is a vanity metric, and the QC of transferred annotations. Use when judging whether an annotation is good enough to publish or submit, diagnosing a suspect annotation, or comparing annotation completeness across pipelines.
bio-genome-assembly-hifi-assembly GPTomics/bioSkills · score 64/100 (grade D)
Assembles haplotype-resolved diploid and telomere-to-telomere (T2T) genomes from PacBio HiFi reads with hifiasm (HiFi-only, Hi-C, or trio phasing) and verkko (HiFi + ultralong ONT for T2T), extracting contigs from GFA and routing phasing QC to k-mer/trio metrics. Covers why a primary assembly is a haplotype mosaic that exists in no cell, partial-vs-full phasing (the .bp. vs .dip. filename convention), the purge-default trap on inbred samples, the --hom-cov coverage-estimate alarm, and verkko-vs-hifiasm for T2T. Use when assembling a diploid eukaryote from HiFi, phasing haplotypes with parents (trio) or Hi-C, deciding whether to chase T2T, or diagnosing switch errors invisible to N50/BUSCO/QV.
bio-genome-intervals-coverage-analysis GPTomics/bioSkills · score 64/100 (grade D)
Computes and interprets sequencing read depth and coverage over a genome, windows, or target regions with mosdepth (windowed depth, cumulative distribution, --quantize callable BEDs), bedtools genomecov/coverage (bedGraph tracks, per-target stats), samtools depth/coverage (per-base depth, per-contig depth+breadth). Covers the breadth-vs-mean distinction, the cumulative-coverage curve, evenness (CV/Fano/fold-80/Gini), what each tool silently counts (duplicates, secondary/supplementary, MAPQ, read span vs fragment, mate-overlap), the samtools-depth 8000-cap version trap, and the bedtools coverage -a/-b orientation flip. Use when assessing sequencing adequacy, building coverage tracks, computing breadth at a depth threshold, defining callable regions, or QCing target-capture uniformity.
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.
bio-hi-c-analysis-contact-pairs GPTomics/bioSkills · score 64/100 (grade D)
Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked. Covers the bwa mem -SP5M / bwa-mem2 / chromap --preset hic alignment idiom (mates mapped as independent single-end reads), pairtools parse vs parse2 and the walks-policy choice (5unique pairwise vs all for Pore-C/Micro-C concatemers), pair-type classification (keep UU and rescued UC), dedup (PCR vs optical/by-tile), select by pair_type/MAPQ/distance, restriction-fragment handling (restrict, Arima dual-enzyme, Micro-C/DNase fragment-free), and allele-specific phasing (pairtools phase to two coolers). The library-QC decision uses % long-range cis as the one-number quality metric, trans as the noise floor, orientation balance as fragment-map-free dangling-end/self-circle QC, and % duplicates as a complexity proxy. Use when processing Hi-C/Micro-C/Omni-C reads into pairs, judging library quality, handling multi-enzyme or restriction-agnostic protocols, or generating allele-specific contacts.
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.
bio-long-read-sequencing-structural-variants GPTomics/bioSkills · score 64/100 (grade D)
Detects structural variants (deletions, insertions, inversions, duplications, translocations) from Oxford Nanopore and PacBio long-read alignments with Sniffles2, cuteSV, SVIM, and assembly-based callers, joint-genotypes cohorts via the Sniffles2 .snf workflow, and benchmarks with Truvari against GIAB. Covers why an SV call is a representation artifact (the tandem-repeat BED, aligner, and Truvari params set precision/recall as much as the caller), the cuteSV per-platform parameter trap, soft-clipped supplementary alignments as the SV substrate, and the somatic/mosaic boundary to Severus/nanomonsv. Use when calling germline or somatic SVs from ONT/HiFi reads, joint-genotyping a cohort, choosing or tuning an SV caller, or benchmarking SV calls.
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.
bio-methylation-ewas-design GPTomics/bioSkills · score 64/100 (grade D)
Designs and defends an epigenome-wide association study (EWAS) on 450K/EPIC array or bisulfite methylation - the layer deciding whether a hit is credible. Covers the confounding hierarchy (cell composition covariates as the dominant confounder, batch/Sentrix chip/array position, age/sex, smoking AHRR cg05575921, ancestry/mQTL, reverse causation), chip randomization (no-rescue theorem), surrogate variable analysis sva/SmartSVA, ComBat, RUVm, over-correction, genomic inflation lambda vs GWAS genomic control, BACON bias/inflation, genome-wide significance threshold 450K/EPIC, FWER vs FDR, pwrEWAS power, meta-analysis, EWAS Catalog/Atlas, methylation risk scores. Use when designing an EWAS, choosing a covariate set, randomizing a plate layout, interpreting lambda, applying BACON, setting a threshold, powering a study, or using an MRS. For the per-site test see differential-cpg-testing; for cell fractions see cell-type-deconvolution; for causal mQTL orientation see causal-genomics/mendelian-randomization.
bio-population-genetics-rare-variant-association GPTomics/bioSkills · score 64/100 (grade D)
Gene and region-based rare-variant aggregation - burden/collapsing, SKAT, SKAT-O, ACAT-V/ACAT-O, annotation-weighted STAAR - with regenie (--vc-tests), SAIGE-GENE+, and the SKAT R package. Single-variant tests are powerless at low minor allele count, so rare variants are aggregated across a gene or region under an explicit mask (functional class plus a MAF cutoff). A burden test collapses variants into one score assuming a single effect direction (powerful when true, near-zero power when risk and protective variants cancel); SKAT is a variance-component test robust to mixed directions; SKAT-O blends the two; ACAT/STAAR are dependence-robust and annotation-weighted. The mask is the hypothesis, imbalance needs SPA or Firth, and testing burden is per-gene-per-mask. Use when aggregating rare coding or regulatory variants into gene or region tests, choosing burden vs SKAT vs SKAT-O, or building masks. For single-variant GWAS see association-testing; for mask annotations see variant-calling/variant-annotation.
bio-primer-design-primer-basics GPTomics/bioSkills · score 64/100 (grade D)
Designs and ranks PCR primer pairs for a target template with primer3-py (design_primers), returning pairs with nearest-neighbor Tm, GC, product size, and complementarity scores. Covers why primer3 is a LOCAL weighted-penalty minimizer over the single template supplied (so PRIMER_PAIR_0 is the lowest-penalty pair under the given bounds, never a genome-specificity guarantee), why Tm is a salt/concentration-dependent SantaLucia prediction not a fixed property, why the two primers must be Tm-matched, the seq_args/global_args tag semantics (SEQUENCE_TARGET/INCLUDED/EXCLUDED/OVERLAP_JUNCTION/FORCE_*, 0-based [start,length]), 3'-end and GC-clamp mechanism, 5'-tail handling, masking SNPs under 3' ends, and diagnosing zero-pair runs. Use when designing standard PCR, cloning, genotyping, or sequencing primers, flanking a target, or screening pairs by Tm/size/GC. Genome off-target checking is primer-specificity; dimers/hairpins primer-validation; qPCR and probes qpcr-primers.
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.
bio-temporal-genomics-periodicity-detection GPTomics/bioSkills · score 64/100 (grade D)
Discovers a periodic signal of UNKNOWN period in time-series omics data and puts a defensible significance on it, especially when sampling is IRREGULAR (dropped timepoints, pooled harvests) so FFT/Welch/JTK are invalid. Estimates the dominant period with Lomb-Scargle / generalized Lomb-Scargle (scipy, astropy), corroborates with autocorrelation, resolves transient/time-varying periodicity with the wavelet CWT (pywt), and screens genome-wide with false-alarm probabilities under BH FDR. Use when finding an oscillation whose period is not known a priori, analyzing cell-cycle or ultradian rhythms, or handling unevenly sampled time courses. Not for testing a KNOWN 24-hour rhythm (see temporal-genomics/circadian-rhythms).
bio-variant-calling-clinical-interpretation GPTomics/bioSkills · score 64/100 (grade D)
Classify variant clinical significance with the ACMG/AMP germline framework and its 2018-2025 ClinGen refinements (graded PVS1 decision tree, PM2 downgraded to Supporting, PP5/BP6 retired, calibrated PP3/BP4, Bayesian points), the AMP/ASCO/CAP somatic tiers and ClinGen oncogenicity system, ClinVar star-rating and gnomAD grpmax filtering-AF interpretation. Use when deciding germline-vs-somatic framework, applying current (not flat-2015) ACMG points, checking for a gene-specific VCEP specification, judging whether a ClinVar assertion or gnomAD frequency is usable evidence, calibrating a pathogenicity predictor, evaluating PVS1 on the MANE Select transcript, or building a VUS reanalysis loop. Not for functional annotation itself (see variant-calling/variant-annotation).
bio-vcf-basics GPTomics/bioSkills · score 64/100 (grade D)
View, query, and interpret VCF/BCF variant files with bcftools and cyvcf2. Use when inspecting variants, extracting fields with query format strings, converting VCF/BCF, or correctly reading a field -- QUAL (site) vs GQ (genotype) vs PL/GL likelihoods, AD vs DP and allele balance, GT phasing/ploidy/PS and missing-vs-hom-ref, INFO/FORMAT Number A/R/G semantics, symbolic alleles (<DEL>, <NON_REF>, spanning *) and END, or telling a raw gVCF apart from a filtered callset.
business-name-fit alirezarezvani/claude-skills · score 64/100 (grade D)
Suggest, pick, or vet a business, startup, or product name that stays true to the founder's cultural origin while working professionally in the markets they want to sell into. Use when someone is naming a company, brand, or product and cares about how it lands across languages and regions — for example a name that sounds right at home but might read oddly to English speakers, or an authentic name they want to check before committing. Trigger this for any request about choosing a business name, checking if a name "works" abroad, spotting bad meanings in other languages, or making a name sound trustworthy in a specific market — even if the person doesn't say the word "skill".
competitive-platform-analysis affaan-m/ECC · score 64/100 (grade D)
Use when scoping a competitive landscape — identifying, categorising, and score-filtering a competitor set before any benchmarking begins. Decides who counts as a competitor, which tier they belong to, and which sources to mine. First step in the three-skill competitive pipeline; precedes benchmark-methodology.
competitive-platform-analysis affaan-m/everything-claude-code · score 64/100 (grade D)
Use when scoping a competitive landscape — identifying, categorising, and score-filtering a competitor set before any benchmarking begins. Decides who counts as a competitor, which tier they belong to, and which sources to mine. First step in the three-skill competitive pipeline; precedes benchmark-methodology.
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.
data-throughput-accelerator affaan-m/ECC · score 64/100 (grade D)
Diagnose and accelerate large data movement — ingestion, backfill, export, ETL, warehouse loading, manifest catch-up, and table synchronization — by isolating the true bottleneck, benchmarking variants, and codifying the fastest path with a hard accounting block proving rows and timestamps cohere. Use when a pipeline or backfill is too slow and must get faster without losing data correctness.
data-throughput-accelerator affaan-m/everything-claude-code · score 64/100 (grade D)
Diagnose and accelerate large data movement — ingestion, backfill, export, ETL, warehouse loading, manifest catch-up, and table synchronization — by isolating the true bottleneck, benchmarking variants, and codifying the fastest path with a hard accounting block proving rows and timestamps cohere. Use when a pipeline or backfill is too slow and must get faster without losing data correctness.
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.
fixed-income-portfolio anthropics/financial-services · score 64/100 (grade D)
Review fixed income portfolios by pricing multiple bonds, retrieving reference data, analyzing cashflows, and running scenario analysis. Use when reviewing bond portfolios, computing portfolio duration and DV01, analyzing cashflow waterfalls, stress testing rate scenarios, or assessing portfolio composition.
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).
ios-application-dev MiniMax-AI/skills · score 64/100 (grade D)
iOS application development guide covering UIKit, SnapKit, and SwiftUI. Includes touch targets, safe areas, navigation patterns, Dynamic Type, Dark Mode, accessibility, collection views, common UI components, and SwiftUI design guidelines. For detailed references on specific topics, see the reference files. Use when: developing iOS apps, implementing UI, reviewing iOS code, working with UIKit/SnapKit/SwiftUI layouts, building iPhone interfaces, Swift mobile development, Apple HIG compliance, iOS accessibility implementation.
kotlin-coroutines-flows affaan-m/ECC · score 64/100 (grade D)
Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing. Use when writing coroutines or Flow code on Android or KMP, or debugging cancellation and concurrency.
kotlin-coroutines-flows affaan-m/everything-claude-code · score 64/100 (grade D)
Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing. Use when writing coroutines or Flow code on Android or KMP, or debugging cancellation and concurrency.
localization Eronred/aso-skills · score 64/100 (grade D)
When the user wants to localize their App Store listing for international markets. Also use when the user mentions "localization", "translate my app", "international markets", "expand to new countries", "localize metadata", or "which countries should I target". For keyword research in specific markets, see keyword-research. For metadata writing, see metadata-optimization.
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.
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.
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.
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.
quarkus-patterns affaan-m/ECC · score 64/100 (grade D)
Quarkus 3.x LTS architecture patterns with Camel for messaging, RESTful API design, CDI services, data access with Panache, and async processing. Use for Java Quarkus backend work with event-driven architectures. Use when building or reviewing a Quarkus service, especially with Camel messaging or Panache data access.
quarkus-patterns affaan-m/everything-claude-code · score 64/100 (grade D)
Quarkus 3.x LTS architecture patterns with Camel for messaging, RESTful API design, CDI services, data access with Panache, and async processing. Use for Java Quarkus backend work with event-driven architectures. Use when building or reviewing a Quarkus service, especially with Camel messaging or Panache data access.
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.
recon briiirussell/cybersecurity-skills · score 64/100 (grade D)
Perform structured reconnaissance and attack surface enumeration for authorized penetration tests, CTF challenges, and bug bounty programs. Use when the user mentions 'recon,' 'reconnaissance,' 'enumerate,' 'attack surface,' 'subdomain enumeration,' 'port scan,' 'fingerprint,' 'asset discovery,' or needs to map a target's external footprint.
retention-optimization Eronred/aso-skills · score 64/100 (grade D)
When the user wants to reduce churn, improve user engagement, or increase lifetime value. Also use when the user mentions "retention", "churn", "users leaving", "engagement", "DAU/MAU", "user activation", or "why are users uninstalling". For onboarding-specific issues, see app-launch. For monetization, see monetization-strategy.
to-spec mattpocock/skills · score 64/100 (grade D)
Turn the current conversation into a spec and publish it to the project issue tracker: no interview, just synthesis of what you've already discussed.
academic-paper-reviewer Imbad0202/academic-research-skills · score 63/100 (grade D)
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정, revisar artículo, revisión entre pares, revisión de manuscrito, informe de árbitro, revisa mi artículo, criticar artículo, simular revisión, revisión editorial, calibrar revisor.
app-analytics Eronred/aso-skills · score 63/100 (grade D)
When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B testing, see ab-test-store-listing. For retention metrics, see retention-optimization.
app-preview-video Eronred/aso-skills · score 63/100 (grade D)
When the user wants to plan, script, produce, or optimize App Store Preview videos or Google Play promo videos — the autoplay videos that show in App Store/Play Store search and product pages. Use when the user mentions "App Preview", "preview video", "app store video", "promo video", "Play Store video", "video poster frame", "YouTube promo for Play Store", "30 second app video", "video script", "video specs", or "should I add a preview video". For static screenshots, see screenshot-optimization. For A/B testing the video, see ab-test-store-listing. For broader creative briefs, see screenshot-optimization (covers stills).
bio-causal-genomics-effector-gene-prioritization GPTomics/bioSkills · score 63/100 (grade D)
Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNP2GENE, cS2G combined SNP-to-gene scores (Gazal 2022), Polygenic Priority Scores (PoPS, Weeks 2023), FLAMES, INQUISIT, DEPICT, and enhancer-gene predictors (ABC, ENCODE-rE2G). Use when narrowing a GWAS lead locus to a candidate causal gene, picking between proximity, eQTL-based, and similarity-based prioritizers, integrating multi-evidence streams (fine-mapping, colocalization, ABC enhancer-gene, distance, chromatin), reconciling discordant L2G vs PoPS calls, prioritizing tissue-specific eQTL evidence, or triangulating across at least three independent lines of evidence for a publication-grade effector-gene nomination.
bio-causal-genomics-mendelian-randomization GPTomics/bioSkills · score 63/100 (grade D)
Estimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments. Implements IVW (fixed/random), MR-Egger, weighted median/mode, MR-RAPS, CAUSE, GSMR-HEIDI, MR-PRESSO, MVMR, MR-Clust, LCV, and LHC-MR via TwoSampleMR, MendelianRandomization, MR-PRESSO, cause, and lhcMR. Use when testing causal direction between traits, evaluating drug-target effects via cis-pQTL/cis-eQTL, performing multivariable mediation MR, distinguishing causation from correlated horizontal pleiotropy, or producing STROBE-MR-compliant sensitivity batteries.
bio-chipseq-qc GPTomics/bioSkills · score 63/100 (grade D)
Assesses ChIP-seq quality across antibody specificity, fragmentation, enrichment, replicate concordance, and library complexity. Computes FRiP, NSC/RSC (phantompeakqualtools), library complexity (NRF/PBC1/PBC2), deepTools plotFingerprint (JS distance, AUC, synthetic JS), ChIPQC, IDR with ENCODE Nself/Nt rules, and detects hyper-ChIPable artifacts. Use when validating an antibody, diagnosing failed peak calls, deciding whether to proceed with downstream analysis, grading against ENCODE thresholds, or auditing replicate concordance.
bio-clinical-biostatistics-categorical-tests GPTomics/bioSkills · score 63/100 (grade D)
Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern McNemar variants with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen). Use when analyzing categorical outcomes, paired binary endpoints, or testing treatment-outcome independence in confirmatory or exploratory clinical trials.
bio-clinical-biostatistics-survival-analysis GPTomics/bioSkills · score 63/100 (grade D)
Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.
bio-comparative-genomics-whole-genome-alignment GPTomics/bioSkills · score 63/100 (grade D)
Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.
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.
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).
bio-gene-regulatory-networks-scenic-regulons GPTomics/bioSkills · score 63/100 (grade D)
Infer transcription factor regulons from single-cell RNA-seq with pySCENIC by combining GRNBoost2 co-expression, cisTarget motif-enrichment pruning, and AUCell per-cell activity scoring. Covers the motif-pruning-as-directionality principle, regulon specificity scoring, run-to-run stability, and database/species matching. Use when identifying TF regulons, scoring TF activity per cell, finding master regulators of cell identity, or comparing regulon activity across conditions. For enhancer-driven multiomic GRNs see multiomics-grn; for bulk inference and VIPER protein-activity see grn-inference.
bio-genome-intervals-bigwig-tracks GPTomics/bioSkills · score 63/100 (grade D)
Reads, queries, and writes bigWig indexed binary signal tracks (coverage, fold-change, conservation, methylation-rate) with pyBigWig (Python) and the UCSC Kent tools (bedGraphToBigWig, bigWigToBedGraph, bigWigInfo, bigWigSummary, bigWigAverageOverBed) and deepTools (multiBigwigSummary, computeMatrix, bigwigCompare). Covers the central trap that a wide query returns a precomputed zoom-level summary (by default the mean, which annihilates narrow peaks) not per-base data, when exact=True/values() is mandatory, the NaN-not-zero gap-handling fork, choosing mean vs max vs sum vs coverage by biological question, and the sorted-bedGraph plus chrom.sizes build requirement. Use when extracting signal at regions, computing mean signal per gene/peak, building a browser track from bedGraph, comparing tracks, or building TSS/gene-body metaprofiles.
bio-genome-intervals-interval-arithmetic GPTomics/bioSkills · score 63/100 (grade D)
Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with bedtools (CLI) and pybedtools/pyranges/bioframe (Python). Covers the sorted-input contract and the -sorted chromosome-order footgun, reciprocal/fractional overlap (-f/-F/-r/-e) and the A-vs-B asymmetry, -split for spliced/BED12/BAM features, and jaccard/fisher as mechanics only. Use when finding overlapping or unique regions between BED/peak/feature files, building consensus peaksets, removing blacklisted regions, transferring annotation values onto intervals, or computing interval-set similarity; route overlap-significance testing to overlap-significance.
bio-immunoinformatics-tcr-epitope-binding GPTomics/bioSkills · score 63/100 (grade D)
Infer or annotate TCR antigen specificity by unsupervised clustering (TCRdist/tcrdist3, GLIPH2, clusTCR, GIANA) and database lookup (VDJdb, IEDB, McPAS-TCR), and rank candidates with supervised predictors (ERGO-II, NetTCR-2.x, pMTnet) under explicit caveats. Encodes the central truth that general TCR-epitope prediction for UNSEEN epitopes essentially does not work (collapses to near-random; IMMREP22, Grazioli 2022) because labeled data is dominated by a few immunodominant epitopes and there is no true negative set — so clustering for discovery is the honest task and de-novo binding needs wet-lab validation. Use when annotating TCR specificity or grouping a repertoire. Epitope/MHC context lives in mhc-binding-prediction.
bio-long-read-sequencing-haplotype-phasing GPTomics/bioSkills · score 63/100 (grade D)
Phases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for allele-resolved downstream analysis. Covers why phase blocks break at het-sparse gaps (read length x heterozygosity), why phasing the VCF is useless until the BAM is haplotagged, the GT-pipe/PS and read HP/PS tag spec, reporting block N50 with switch error, the diploid-assumption/CNV/haploid-region traps, trio phasing as the gold standard, and the boundary to statistical panel phasing. Use when phasing long-read variants, haplotagging reads for allele-specific methylation/expression or phased SVs, choosing WhatsHap vs LongPhase vs HiPhase, trio phasing, or assessing phasing quality.
bio-microbiome-diversity-analysis GPTomics/bioSkills · score 63/100 (grade D)
Alpha and beta diversity of an amplicon (16S/ITS) ASV/OTU community table - observed features, Shannon, Pielou evenness, Faith PD, Bray-Curtis, Jaccard, weighted/unweighted/generalized UniFrac, Aitchison/RPCA - via QIIME2 core-metrics-phylogenetic, phyloseq/vegan, and scikit-bio. Covers the three knobs that set the answer before it is seen (rarefaction sampling depth, the tree, the metric), why core-metrics silently deletes samples below the sampling depth, why de novo trees lose to SEPP fragment-insertion and Greengenes2, why unweighted and weighted UniFrac can flip the story, why observed features is an ASV count not a species count, the QIIME2-log2 vs R-ln Shannon mismatch, and pairing PERMANOVA (adonis2) with betadisper. Use when summarizing whole-community richness/evenness or testing group differences in community structure. Per-taxon testing -> differential-abundance. Shotgun tables -> metagenomics/metagenome-visualization. Shared CoDA/rarefaction theory -> metagenomics/abundance-estimation.
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.
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.
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.
bio-proteomics-proteomics-qc GPTomics/bioSkills · score 63/100 (grade D)
Quality control for bottom-up proteomics across three levels -- instrument/raw-signal (mass accuracy, RT/iRT fit, FWHM, TIC vs injection time, % MS2 identified), identification/run (missed cleavages, charge states, PTM handling artifacts, contaminants), and experiment/quantitative (replicate correlation on log2, CV on the linear scale, completeness, MNAR-vs-MCAR missingness, PCA/batch, TMT channel balance, DIA q-values). Frames QC as a control chart against a per-instrument rolling baseline, not fixed cutoffs, and mandates inspecting raw boxplots, per-sample ID counts, total signal, and contaminant removal BEFORE normalizing -- because median normalization erases loading failures. Use when assessing proteomics data quality, diagnosing outlier samples, or deciding which samples to exclude before differential testing. The statistical test itself is differential-abundance; normalization mechanics are quantification; DIA q-value internals are dia-analysis.
bio-small-rna-seq-differential-mirna GPTomics/bioSkills · score 63/100 (grade D)
Tests miRNAs for differential expression with DESeq2 or edgeR using small-RNA-aware normalization and filtering. Use when deciding which normalization survives a library dominated by a few hyper-abundant miRNAs (compositional fragility); choosing DESeq2 vs edgeR vs a compositional method; setting a lower prefilter than mRNA; handling biofluid data with no endogenous normalizer; or remembering that RPM is for display and TDMD can make a miRNA drop without transcriptional repression.
bio-spatial-transcriptomics-spatial-deconvolution GPTomics/bioSkills · score 63/100 (grade D)
Estimates per-spot cell type composition of spatial transcriptomics mixtures (Visium, Slide-seq, Stereo-seq) from an scRNA-seq reference with cell2location, RCTD, SPOTlight, stereoscope, SpatialDWLS, or reference-free STdeconvolve. Use when deciding whether a platform even needs deconvolution (the resolution fork -- a 55um Visium spot is a 1-10-cell MIXTURE -> deconvolve, but a Xenium/MERFISH/CosMx cell is already single -> segment instead, and running deconvolution there invents fractions that do not exist); choosing cell2location (absolute abundance) vs RCTD/SPOTlight/stereoscope/SpatialDWLS (proportions only) by output and runtime; matching the scRNA reference to tissue and condition (the reference IS the result -- a missing cell type is silently misassigned to its nearest neighbor with no error flag); and handling compositional outputs that sum to 1 with CLR/ILR rather than naive per-type t-tests.
bio-spatial-transcriptomics-spatial-visualization GPTomics/bioSkills · score 63/100 (grade D)
Plots spatial transcriptomics expression, clusters, and annotations on tissue using Squidpy and Scanpy. Use when choosing the plotter and spot size by platform fork (sc.pl.spatial / sq.pl.spatial_scatter with real scalefactors and capture diameter for spot/capture data like Visium and Slide-seq, versus molecule/segmentation overlays for imaging/FOV data like Xenium, MERFISH, and CosMx); getting the histology coordinate-frame transform right (micron<->pixel, scalefactors) so points land on the image; and avoiding the honest-visualization traps where interpolation/KDE manufactures spatial pattern not in the data, oversized markers fake tissue coverage, jet and other non-uniform colormaps distort structure, and non-metric UMAP/tSNE distances are misread as spatial conclusions.
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.
bio-tcr-bcr-analysis-immcantation-analysis GPTomics/bioSkills · score 63/100 (grade D)
Reconstructs B-cell clonal families, quantifies somatic hypermutation and selection, and builds antibody lineage trees with the Immcantation R suite (alakazam, shazam, scoper, dowser, tigger) on AIRR-format BCR data. Use when deriving the clonal-clustering threshold from the distToNearest bimodal valley (never a hardcoded 0.15); choosing hierarchicalClones vs spectralClones (vj vs novj) for SHM-diverged repertoires; personalizing the germline with TIGGER before mutation counting; reconstructing D-masked germlines with createGermlines; measuring R/S mutation frequency by CDR and FWR region; testing antigen-driven selection with BASELINe; comparing Hill-number diversity at equal sampling depth; and inferring IgPhyML lineage trees for affinity maturation, class-switch, and ancestral-antibody analysis.
bio-tcr-bcr-analysis-specificity-annotation GPTomics/bioSkills · score 63/100 (grade D)
Maps TCR/BCR receptor sequences toward candidate antigen specificity and clusters repertoires by shared-specificity signal, while enforcing that a database match or a cluster label is a HYPOTHESIS, not a specificity call. Use when deciding among database annotation (VDJdb/McPAS/IEDB+TCRMatch, requiring V-gene and HLA concordance plus a confidence score) versus sequence clustering (tcrdist3 meta-clonotypes, GLIPH2, GIANA, clusTCR, which find enrichment not per-receptor labels) versus generation-probability nulls (OLGA Pgen, IGoR, SONIA Ppost) for testing public/convergent/shared claims; and when guarding against overclaiming specificity, base-rate false positives from bare CDR3 matches, unpaired beta-only annotation, ML predictor failure on unseen epitopes, and ignored MHC restriction. TCR-focused with a BCR/antibody note (SHM, conformational epitopes, IGHV3-53/3-66 public clonotypes). Keywords CDR3, pMHC, HLA restriction, cross-reactivity, meta-clonotype, Pgen, public clonotype, convergent recombination.
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.
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.
breach-patterns briiirussell/cybersecurity-skills · score 63/100 (grade D)
Learn from public breach disclosures — extract the audit question each one implies and check your own stack. Capital One IMDS abuse, LastPass vault exfiltration, Okta Lapsus$, Snowflake credential reuse, MOVEit, SolarWinds, Equifax, Target POS, Codecov, Uber, Twilio — what would you check now if your boss said 'could that happen to us?' Use when the user mentions 'breach analysis,' 'lessons learned,' 'security postmortem,' 'breach patterns,' 'breach lessons,' 'has this happened to us,' 'apply breach lessons,' 'preempt breaches,' 'security retrospective,' 'real-world security incidents,' or wants to harden against known attacker playbooks.
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\".
compose-multiplatform-patterns affaan-m/ECC · score 63/100 (grade D)
Compose Multiplatform and Jetpack Compose patterns for KMP projects — state management, navigation, theming, performance, and platform-specific UI. Use when building Compose or Jetpack Compose UI, state, navigation, or theming in a KMP project.
compose-multiplatform-patterns affaan-m/everything-claude-code · score 63/100 (grade D)
Compose Multiplatform and Jetpack Compose patterns for KMP projects — state management, navigation, theming, performance, and platform-specific UI. Use when building Compose or Jetpack Compose UI, state, navigation, or theming in a KMP project.
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".
marketing-ideas coreyhaines31/marketingskills · score 63/100 (grade D)
When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' 'ideas to grow,' 'what else can I try,' 'I don't know how to market this,' 'brainstorm marketing,' or 'what marketing should I do.' Use this as a starting point whenever someone is stuck or looking for inspiration on how to grow. For specific channel execution, see the relevant skill (ads, social, emails, etc.).
playwright-generate-test github/awesome-copilot · score 63/100 (grade D)
Generate a Playwright test based on a scenario using Playwright MCP
Product Manager alirezarezvani/claude-skills · score 63/100 (grade D)
Ships outcomes, not features. Writes specs engineers actually read. Prioritizes ruthlessly. Kills darlings when the data says so. Operates at the intersection of user needs, business goals, and engineering reality. Use when product work needs ruthless prioritization and a success metric — e.g., turning vague stakeholder asks into a 2-page spec, or deciding which of three competing roadmap bets to fund this quarter. (For framework-heavy RICE/PRD tooling, see cs-product-manager.)
referrals coreyhaines31/marketingskills · score 63/100 (grade D)
When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' 'partner program,' 'referral incentive,' 'how to get referrals,' 'customers referring customers,' 'affiliate payout,' 'get more reviews,' 'G2 reviews,' 'review campaign,' or 'respond to a bad review.' Use this whenever someone wants existing users or partners to bring in new customers. For launch-specific virality, see launch.
research alirezarezvani/claude-skills · score 63/100 (grade D)
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research, deepread for evidence-first reading of supplied documents) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Use when the user makes any research request that doesn't obviously match a more-specific specialist skill (e.g., "research [topic]", "look into [topic]", "what do we know about [topic]", "investigate [topic]", "find me information on [topic]", "do some research on [topic]", "I need to understand [topic]"). Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
retro alirezarezvani/claude-skills · score 63/100 (grade D)
Analyze sprint retrospectives for patterns and action item tracking. Usage: /retro analyze <retro_data.json>
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.
validate-idea slavingia/skills · score 63/100 (grade D)
Validate a business idea using the minimalist entrepreneur framework. Use when someone has a business idea and wants to test if it's worth pursuing before building anything.
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.
asc-build-lifecycle rudrankriyam/app-store-connect-cli-skills · score 62/100 (grade D)
Track build processing, find latest builds, and clean up old builds with asc. Use when managing build retention or waiting on processing.
asc-id-resolver rudrankriyam/app-store-connect-cli-skills · score 62/100 (grade D)
Resolve App Store Connect IDs (apps, builds, app and digital-goods versions, groups, testers) from human-friendly names using asc. Use when commands require IDs.
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.
bio-clinical-databases-tumor-mutational-burden GPTomics/bioSkills · score 62/100 (grade D)
Calculates tumor mutational burden from WES/WGS/panel data with Friends of Cancer Research harmonization equations, per-assay calibration (FDA 10/Mb = 7.8 TSO500 = 8.4 OncomineTML), synonymous/indel/germline filtering, hypermutator tiering, blood TMB, and integration with HLA-LOH and neoantigen quality (Luksza 2017 fitness). Use when assessing ICI eligibility under tumor-specific cutoffs (McGrail 2021), comparing tissue vs bTMB, or auditing TMB-H reporting against ESMO 2024 and FDA pembrolizumab pan-tumor 2020.
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.
bio-comparative-genomics-ortholog-inference GPTomics/bioSkills · score 62/100 (grade D)
Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.
bio-comparative-genomics-synteny-analysis GPTomics/bioSkills · score 62/100 (grade D)
Detect syntenic blocks and structural rearrangements between genomes using MCScanX (Wang 2012), JCVI/MCScan (Tang 2008 Python), GENESPACE (Lovell 2022) for orthology-anchored riparian visualization, SyRI for structural variation, AnchorWave for sequence-level synteny, i-ADHoRe 3.0 for highly diverged species, SynNet for synteny networks, and ntSynt for multi-genome macrosynteny. Use when identifying collinear gene blocks across species, distinguishing macrosynteny from microsynteny, detecting inversions/translocations/duplications, anchoring orthology in WGD lineages, producing publication riparian plots, computing synteny block age via Ks (cross-references whole-genome-duplication), or running synteny-aware ortholog inference in polyploids.
bio-copy-number-cnv-visualization GPTomics/bioSkills · score 62/100 (grade D)
Visualize copy number profiles, segments, allele-specific tracks, and cohort patterns from CNVkit, GATK, ASCAT, FACETS, Sequenza, and other callers. Covers genome-wide and per-chromosome log2 scatter plots, B-allele-frequency/minor-allele-fraction tracks, ideograms, cohort heatmaps, circos views, and caller-native plots. Use when creating publication CNV figures, choosing which plot answers a given question, diagnosing a wrong diploid baseline visually, displaying loss of heterozygosity, or deciding what depth-only plots cannot reveal.
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.
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.
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.
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).
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).
cold-email coreyhaines31/marketingskills · score 62/100 (grade D)
Write and run B2B cold outbound that gets replies, from cold emails and follow-ups to sending setup, LinkedIn, multichannel cadences, and reply handling. Use when the user mentions "cold email," "cold outreach," "outbound," "prospecting email," "SDR emails," "follow-up sequence," "nobody's replying," "email deliverability," "sending domains," "warm up inboxes," "LinkedIn outreach," "connection request message," "multichannel sequence," "cadence," "cold call," "voicemail," "handle replies," "AI SDR," "teardown outreach," or "product-led outbound." Send from secondary domains, verify lists first, turn off open tracking, and stop every channel when a prospect replies. Copy avoids AI tells like 'it's not X, it's Y' reveals. For building the list and account research, see prospecting. For lifecycle email, see emails. For call scripts and sales collateral, see sales-enablement.
competitor-profiling coreyhaines31/marketingskills · score 62/100 (grade D)
When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement. For researching accounts you're selling to, see prospecting.
create-github-issue-feature-from-specification github/awesome-copilot · score 62/100 (grade D)
Create GitHub Issue for feature request from specification file using feature_request.yml template.
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",...}).
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.
freeze garrytan/gstack · score 62/100 (grade D)
Restrict file edits to a specific directory for the session. (gstack)
gke-ai-troubleshooting-handle-disruption-gpu-tpu google/skills · score 62/100 (grade D)
Diagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing node taints, or configuring workload protection strategies (graceful termination, opportunistic maintenance, PodDisruptionBudgets). Don't use for general GKE cluster creation, network policy configuration, or non-disruption workload deployment.
gke-custom-golden-image-discovery google/skills · score 62/100 (grade D)
Discovers golden base images for creating GKE custom node images based on technical specifications or context clues. Use when finding the golden base image for custom GKE node creation, mapping cluster configuration parameters (GKE version, OS, architecture, accelerators, gVisor, cgroups) to image names, or querying GKE base image maps. Don't use for general GKE cluster creation (use gke-cluster-creation) or standard node pool management (use gke-basics).
migrating-oracle-to-postgres-stored-procedures github/awesome-copilot · score 62/100 (grade D)
Migrates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL. Translates Oracle-specific syntax, preserves method signatures and type-anchored parameters, leverages orafce where appropriate, and applies explicit collation mapping (`COLLATE "C"` only when appropriate, locale collations when required). Use when converting Oracle stored procedures or functions to PostgreSQL equivalents during a database migration.
ponytail-gain DietrichGebert/ponytail · score 62/100 (grade D)
Show ponytail's measured savings (code, cost, speed) from the benchmark. One-shot display. Use for /ponytail-gain, "what does ponytail save", "ponytail impact".
press-and-pr Eronred/aso-skills · score 62/100 (grade D)
When the user wants to get press coverage, media mentions, or editorial features for their app — including writing press releases, pitching journalists, getting on "best apps" lists, or building an app press kit. Use when the user mentions "press", "PR", "media coverage", "TechCrunch", "journalist", "press release", "app press kit", "get featured in media", "editorial coverage", "review from a blogger", or "app launch announcement". For Apple editorial featuring, see app-store-featured. For launch strategy, see app-launch.
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.
react18-enzyme-to-rtl github/awesome-copilot · score 62/100 (grade D)
Provides exact Enzyme → React Testing Library migration patterns for React 18 upgrades. Use this skill whenever Enzyme tests need to be rewritten - shallow, mount, wrapper.find(), wrapper.simulate(), wrapper.prop(), wrapper.state(), wrapper.instance(), Enzyme configure/Adapter calls, or any test file that imports from enzyme. This skill covers the full API mapping and the philosophy shift from implementation testing to behavior testing. Always read this skill before rewriting Enzyme tests - do not translate Enzyme APIs 1:1, that produces brittle RTL tests.
article-writing affaan-m/ECC · score 61/100 (grade D)
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
article-writing affaan-m/everything-claude-code · score 61/100 (grade D)
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
bio-clinical-biostatistics-subgroup-analysis GPTomics/bioSkills · score 61/100 (grade D)
Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine claims.
bio-copy-number-focal-amplification-ecdna GPTomics/bioSkills · score 61/100 (grade D)
Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.
bio-differential-expression-deseq2-basics GPTomics/bioSkills · score 61/100 (grade D)
Performs differential expression on bulk RNA-seq count data with DESeq2's negative-binomial GLM, Wald and LRT testing, apeglm/ashr/normal LFC shrinkage, independent filtering, Cook's outlier handling, VST/rlog transforms, and design formulas including paired, batch, and interaction terms. Use when running bulk DE, choosing DESeq2 over edgeR or limma-voom, building a paired or interaction design, applying LFC shrinkage for ranking or GSEA, choosing Wald vs LRT, troubleshooting padj=NA, picking VST vs rlog, importing salmon/kallisto via tximport, or analyzing prokaryotic RNA-seq.
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.
bio-expression-matrix-gene-id-mapping GPTomics/bioSkills · score 61/100 (grade D)
Maps between gene identifier systems (Ensembl, Entrez, HGNC symbol, UniProt, RefSeq, MANE) using AnnotationDbi, biomaRt, mygene, pyensembl, and Ensembl REST. Encodes Ensembl version stripping with GENCODE _PAR_Y preservation, the Ziemann 2016 Excel autocorrect debacle and Bruford 2020 HGNC renames (SEPT*->SEPTIN*, MARCH*->MARCHF*, MARC*->MTARC*, DEC1->DELEC1), OCT4/POU5F1 alias resolution, biomaRt archive endpoints for release pinning, the `filters` (plural) gotcha, MANE Select for clinical reporting, cross-species orthology via Ensembl Compara / OMA / OrthoDB, and tx2gene construction for tximport. Use when converting gene IDs across systems, handling renamed symbols, building tx2gene, pinning to a specific Ensembl release for reproducibility, or mapping cross-species orthologs.
bio-flow-cytometry-clustering-phenotyping GPTomics/bioSkills · score 61/100 (grade D)
Unsupervised clustering and cell-type identification for high-dimensional flow, spectral, and mass cytometry - FlowSOM, PhenoGraph, FlowSOM-via-CATALYST, with UMAP/tSNE for visualization. Covers the type-vs-state marker distinction (cluster on lineage, test state within clusters), over-provision-then-metacluster, the Weber-Robinson benchmark, seed dependence and metacluster stability, why embeddings are for looking not measuring, and median-heatmap annotation/merging. Use when discovering populations without predefined gates, choosing a clustering algorithm, selecting the number of metaclusters, or annotating clusters into cell types.
bio-flow-cytometry-compensation-transformation GPTomics/bioSkills · score 61/100 (grade D)
Corrects fluorophore spillover (conventional compensation) or spectral overlap (spectral unmixing) and applies variance-stabilizing transforms (logicle/biexponential, arcsinh, log) for flow and mass cytometry. Covers spillover-matrix estimation from single-stain controls, AutoSpill, the spillover spreading matrix and why panel design (not compensation) bounds resolution, compensate-then-transform ordering, and arcsinh cofactor choice (5 for CyTOF, ~150 for fluorescence, per-channel via flowVS). Use when correcting spectral overlap, preparing data for gating/clustering, choosing logicle vs arcsinh, deciding a cofactor, or distinguishing compensation from spectral unmixing.
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.
bio-immunoinformatics-mhc-binding-prediction GPTomics/bioSkills · score 61/100 (grade D)
Predict peptide-MHC class I binding and natural presentation with MHCflurry, NetMHCpan-4.1, and MixMHCpred to nominate candidate CD8 T-cell epitopes. Covers the binding-affinity (BA) vs eluted-ligand (EL/presentation) distinction, why %Rank beats raw nM for cross-allele work, the MS abundance bias that misranks low-expression neoantigens, allele-coverage inequity, and length bias. Use when scanning a protein or peptide set for class I epitopes, scoring neoantigen candidates, or choosing a binding predictor. For CD4/HLA class II see mhc-class-ii-prediction.
bio-metagenomics-strain-tracking GPTomics/bioSkills · score 61/100 (grade D)
Resolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2, metaSNV, and StrainGE, plus genome-vs-genome ANI (skani/fastANI/MASH) for isolate/MAG comparison. Covers why a strain is a threshold not a thing, why ANI answers same-genome while popANI/nGD answer same-population-in-situ, the 99.999% popANI and per-species nGD definitions, the coverage detection limit (absence is not absence), why sharing is not transmission direction, and mapping to the dataset's own dRep MAGs. Use when detecting shared strains, tracking transmission, resolving within-host strain dynamics, or deconvoluting co-occurring strains. For pure-culture isolate outbreak SNP trees see epidemiological-genomics; for MAG assembly see genome-assembly/metagenome-assembly.
bio-microbiome-functional-prediction GPTomics/bioSkills · score 61/100 (grade D)
Predicts community functional POTENTIAL from 16S/ITS amplicon ASVs with PICRUSt2 (or q2-picrust2) by phylogenetic interpolation of reference-genome gene content - EPA-ng placement, gappa, castor hidden-state prediction of KO/EC/Pfam copy number, 16S copy-number normalization, and MinPath MetaCyc/KEGG pathways - gated by the NSTI quality index. Covers why predicted function is taxonomy re-encoded (never measured gene content and never activity), the mandatory NSTI report (--max_nsti 2 silently drops novel ASVs), why accuracy IS reference coverage (gut Spearman ~0.8, soil/marine collapse), the circularity trap, and Tax4Fun2/FAPROTAX/BugBase alternatives. Use when inferring KO/EC/MetaCyc potential from an ASV table, gating on NSTI, or choosing a prediction method. For MEASURED shotgun function see metagenomics/functional-profiling; for enrichment of KO lists see pathway-analysis/go-enrichment; for DA of predicted tables see differential-abundance.
bio-primer-design-qpcr-primers GPTomics/bioSkills · score 61/100 (grade D)
Co-designs qPCR/RT-qPCR primers and hydrolysis (TaqMan) or molecular-beacon probes with primer3-py (PRIMER_PICK_INTERNAL_OLIGO, PRIMER_INTERNAL_* tags), for assays whose deliverable is a quantitative measurement device. Covers why amplification efficiency (90-110%, slope -3.6 to -3.1) and single-product specificity make the 2^-ddCq / Pfaffl math valid, why the short amplicon (70-150 bp), tight Tm, and zero-dimer requirement exist, the coupled probe rules (probe Tm 8-10 C above primers so it is bound when Taq's exonuclease cleaves it; no 5' G as it quenches the reporter; C-rich strand; primer3 has NO no-5'-G tag so enforce PRIMER_INTERNAL_MUST_MATCH_FIVE_PRIME=HNNNN), gDNA exclusion by exon-junction spanning AND why pseudogenes defeat it, SYBR melt-curve QC, and reference-gene validation (geNorm/NormFinder). Use when designing TaqMan/SYBR assays, exon-spanning primers, probes, or matched-efficiency multiplex panels. Genome specificity is primer-specificity; dimers primer-validation; standard PCR primer-basics.
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.
bio-spatial-transcriptomics-spatial-preprocessing GPTomics/bioSkills · score 61/100 (grade D)
Quality control, filtering, and normalization for spatial transcriptomics (Visium, Visium HD, Xenium, MERFISH/MERSCOPE, CosMx, Slide-seq) with Squidpy and Scanpy. Use when setting QC floors that do NOT delete real low-count imaging cells (an scRNA min_counts=500 floor deletes nearly every Xenium cell, whose vector is tens-to-low-hundreds of transcripts); deciding whether to normalize at all when library size carries spatial biology rather than pure technical depth; choosing cell-volume/area normalization over Pearson residuals for skewed targeted panels; reading negative-control-probe / blank-barcode false-discovery rates; and inspecting QC spatially on the tissue rather than only in violins.
bio-tcr-bcr-analysis-repertoire-visualization GPTomics/bioSkills · score 61/100 (grade D)
Draws TCR/BCR repertoire figures - V-J chord/circos, CDR3 spectratype, clonal-space stratification, clonal tracking across timepoints, rarefaction/extrapolation curves, overlap heatmaps, and clonotype-similarity networks - and encodes how to read them. Use when choosing between a raw Shannon bar and a rarefaction curve for a diversity comparison; deciding a depth-robust overlap metric (Morisita-Horn) vs a set metric (Jaccard) for a heatmap; setting the distance threshold that defines a clonotype-similarity network; interpreting a Gaussian vs skewed spectratype as polyclonal vs clonally expanded; or laying out clonal-space and clone-tracking plots. Covers VDJtools PlotFancyVJUsage/RarefactionPlot, R circlize and iNEXT, and matplotlib/seaborn recipes.
bio-variant-calling-structural-variant-calling GPTomics/bioSkills · score 61/100 (grade D)
Call structural variants (>=50 bp deletions, insertions, inversions, duplications, translocations) from short- or long-read data by reconstructing four orthogonal signals (discordant pairs, split reads via the SA tag, read depth, local assembly). Covers Manta, DELLY, LUMPY/smoove, GRIDSS2, SvABA for short reads and Sniffles2, cuteSV, pbsv, dipcall/PAV for long reads, each mapped to the signals it fuses and the blind spots that follow. Use when choosing an SV caller from its signal set and failure modes, decoding the SVLEN-sign / symbolic-vs-BND / CIPOS VCF representation minefield, force-genotyping a cohort matrix instead of unioning discovery VCFs, merging populations with sequence-aware Truvari vs position-only SURVIVOR, parameterizing a Truvari benchmark, or deciding when short-read insertion recall forces a switch to long reads. Not for pure copy-number dosage (see copy-number/cnvkit-analysis).
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.
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.
connections-optimizer affaan-m/ECC · score 61/100 (grade D)
Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.
connections-optimizer affaan-m/everything-claude-code · score 61/100 (grade D)
Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.
deal-sourcing anthropics/financial-services · score 61/100 (grade D)
PE deal sourcing workflow — discover target companies, check CRM for existing relationships, and draft personalized founder outreach emails. Use when sourcing new deals, prospecting companies in a sector, or reaching out to founders. Triggers on "find companies", "source deals", "draft founder email", "check if we've seen this company", or "outreach to founder".
fluid-design kemiljk/fluid-design · score 61/100 (grade D)
Use this skill whenever building interfaces that should feel physically responsive, alive, and polished. Trigger for spring animations, gesture-driven UI, interruptible animations, physics-based motion, drag interactions, momentum scrolling, layout animations, shared element transitions, spatial UI, micro-interactions, haptic feel, or any request to make an interface feel alive, snappy, smooth, natural, polished, or less static. Also trigger when building interactive components (drawers, sheets, carousels, modals, accordions, reorderable lists) without specified animation, or any interactive prototype, component library, or design system.
marketing-council coreyhaines31/marketingskills · score 61/100 (grade D)
When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin, David Ogilvy, Eugene Schwartz, April Dunford, Rory Sutherland, Alex Hormozi, Byron Sharp, and more). Also use when the user mentions 'marketing council,' 'board of advisors,' 'advisory board,' 'what would Seth Godin say,' 'what would Ogilvy think,' 'channel Hormozi,' 'get multiple perspectives,' 'debate this,' 'have the council review,' 'marketing mentors,' or asks how a famous marketer would approach their problem. The council gives each advisor's take through their documented frameworks, surfaces where they disagree, and synthesizes a recommendation. For executing the winning direction, hand off to positioning, offers, copywriting, ads, or the relevant skill.
mobile-native emilkowalski/skills · score 61/100 (grade D)
Make a web app feel native on a phone — the small CSS and meta-tag fixes that separate "a website in a browser" from something that feels installed. Covers sticky hover states, tap highlight flashes, the 100vh bug, inputs that zoom the page, laggy taps, pull-to-refresh hijacking scroll, content under the notch, long-press selecting button text, carousels that scroll the wrong way, mismatched status bars, and the rule that you test on real hardware. Use when a web app is being built for or reviewed on mobile, when something "works in Chrome but feels wrong on my phone", when building a PWA, a bottom sheet, a carousel, a full-screen layout, or any touch interaction. For motion itself use animate; for React Native use animate-expo.
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。
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.
seam-craft heygen-com/hyperframes · score 61/100 (grade D)
Render-correctness doctrine for scene-to-scene seams in HyperFrames launch videos — the prerequisites that make transitions composite correctly on the master timeline. Load when assembling the master timeline / index.html, when a white flash appears at a cut or crossfade seam (especially on dark films), when reasoning about why a transition opacity dip shows through, or when verifying the render-side mechanics of how overlapping scene wrappers blend. Covers the opaque stage-ground (#root background) white-flash guard and how the injector overlaps wrappers, holds final frames, ping-pongs tracks, and stamps lint-clean template code onto the master timeline. Does NOT contain the per-transition catalog — see the transition registry for individual transition entries.
to-tickets mattpocock/skills · score 61/100 (grade D)
Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker (edges as text in one file per ticket locally, or native blocking links on a real tracker).
aso-audit Eronred/aso-skills · score 60/100 (grade D)
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
aso-router Eronred/aso-skills · score 60/100 (grade D)
Single entry point that routes any ASO, App Store, Google Play, app marketing, paid UA, monetization, retention, reviews, ratings, market-intel, or app-analytics question to the correct specialist skill in this library. Use FIRST whenever the user mentions an app, App Store, Play Store, keywords, ranking, downloads, revenue, subscriptions, screenshots, icon, reviews, competitors, charts, in-app events, launch, press, or ads — but the right specialized skill is not obvious. Triggers: "/aso-router", "/aso-skill", "/aso", "aso help", "help me with my app", "I need ASO", "which skill should I use", or any ambiguous app-marketing request. Skip this router only when the user explicitly invokes a specific skill (e.g. /aso-audit, /keyword-research).
bio-comparative-genomics-genome-distance-and-species-delineation GPTomics/bioSkills · score 60/100 (grade D)
Compute genome-to-genome distances (ANI, AAI, dDDH, k-mer Mash) and assign taxonomic classifications using skani (Shaw 2023), FastANI (Jain 2018), pyani / pyANI ANIb / ANIm, OrthoANI (Lee 2016), AAI (amino-acid identity), dDDH via TYGS / GGDC, GTDB-Tk (Chaumeil 2020 standard prokaryote taxonomy), and Mash MinHash (Ondov 2016). Use when delineating prokaryote species (95% ANI threshold; Jain 2018 Nat Commun 9:5114), assigning genomes to GTDB taxonomy with ANI radius, computing genome similarity matrices for clustering, classifying archaea, evaluating MAG (metagenome-assembled genome) species assignment, applying skani for fast metagenomic ANI screening, or reconciling 16S rRNA-based taxonomy with whole-genome ANI.
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.
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.
bio-copy-number-germline-cnv-interpretation GPTomics/bioSkills · score 60/100 (grade D)
Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, or distinguishing the automatable evidence from the case-specific evidence requiring manual input.
bio-differential-expression-de-visualization GPTomics/bioSkills · score 60/100 (grade D)
Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.
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.
bio-microbiome-taxonomy-assignment GPTomics/bioSkills · score 60/100 (grade D)
Assigns taxonomy to amplicon ASVs/OTUs (16S, ITS, 18S) with a classifier conditioned on a reference database and primer region - DADA2 assignTaxonomy + addSpecies (RDP naive Bayes), DECIPHER IDTAXA, and QIIME2 q2-feature-classifier (classify-sklearn naive Bayes, classify-consensus-vsearch alignment-consensus). Covers region-specific training (extract-reads, fit-classifier-naive-bayes), why a full-length classifier fabricates calls on a V4 read, the scikit-learn version-pinning trap on pre-trained .qza classifiers, confidence thresholds (classify-sklearn 0.7, assignTaxonomy minBoot 50), and choosing SILVA/GTDB/Greengenes2/UNITE/PR2/RDP. Use when classifying ASVs after DADA2, picking a reference database, training a region-matched classifier, setting a confidence threshold, or deciding whether a 16S species call is defensible (usually not - genus at best). For shotgun read classification see metagenomics/kraken-classification and metagenomics/metaphlan-profiling.
bond-relative-value anthropics/financial-services · score 60/100 (grade D)
Perform relative value analysis on bonds by combining pricing, yield curve context, credit spreads, and scenario stress testing. Use when analyzing bond richness/cheapness, computing spread decomposition, comparing bonds, assessing bond value vs curves, or running rate shock scenarios.
content-creator alirezarezvani/claude-skills · score 60/100 (grade D)
Deprecated redirect skill that routes legacy 'content creator' requests to the correct specialist. Use when a user invokes 'content creator', asks to write a blog post, article, guide, or brand voice analysis (routes to content-production), or asks to plan content, build a topic cluster, or create a content calendar (routes to content-strategy). Does not handle requests directly — identifies user intent and redirects to content-production for writing/SEO/brand-voice tasks or content-strategy for planning tasks.
etf-premium himself65/finance-skills · score 60/100 (grade D)
Calculate an ETF's premium or discount to NAV from Yahoo Finance data (yfinance), compare or screen ETFs by premium, explain why a gap exists, and decompose a sudden ETF move into NAV-driven vs structural components (dealer gamma exposure, blocked AP arbitrage, sentiment). Use this skill whenever the user asks whether an ETF trades above or below NAV, compares ETF premiums or discounts, screens for the biggest ones, asks about ETF arbitrage or premium convergence, or wants to know why an ETF jumped or diverged from its holdings — including gamma squeezes, dealer gamma exposure (GEX), and blocked creation/redemption. Especially relevant for leveraged, inverse, international, bond, commodity, and crypto ETFs (IBIT, BITO, HYG, KWEB).
finnish-humanizer github/awesome-copilot · score 60/100 (grade D)
Detect and remove AI-generated markers from Finnish text, making it sound like a native Finnish speaker wrote it. Use when asked to "humanize", "naturalize", or "remove AI feel" from Finnish text, or when editing .md/.txt files containing Finnish content. Identifies 26 patterns (12 Finnish-specific + 14 universal) and 4 style markers.
Growth Marketer alirezarezvani/claude-skills · score 60/100 (grade D)
Growth marketing specialist for bootstrapped startups and indie hackers. Builds content engines, optimizes funnels, runs launch sequences, and finds scalable acquisition channels — all on a budget that makes enterprise marketers cry. Use when growth has to come before budget — e.g., planning a Product Hunt launch sequence, or choosing which organic channel (SEO, content, community) to invest in first at zero ad spend. (For funnel diagnostics with paid budget, see cs-demand-gen-specialist.)
loop-me mattpocock/skills · score 60/100 (grade D)
Grill me about specs for the workflows I want to build, within this workspace.
postgresql-code-review github/awesome-copilot · score 60/100 (grade D)
PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).
public-relations coreyhaines31/marketingskills · score 60/100 (grade D)
When the user wants help with public relations, earned media, press coverage, journalist outreach, or media strategy (not pull requests). Also use when the user mentions 'PR,' 'press,' 'press release,' 'media outreach,' 'pitch a journalist,' 'get featured,' 'media list,' 'media kit,' 'press kit,' 'newsjacking,' 'news hijack,' 'HARO,' 'Qwoted,' 'Featured,' 'reporter request,' 'tech press,' 'TechCrunch,' 'thought leadership placement,' 'op-ed,' 'guest article,' 'press contacts,' 'podcast prep,' 'podcast guest,' 'prep me for this podcast,' 'how do I get press,' 'PR crisis,' 'crisis communications,' 'respond to backlash,' 'we got hacked,' 'data breach statement,' or 'holding statement.' Also covers crisis response when something goes wrong. For startup/SaaS/AI directory submissions, see directory-submissions. For product launches, see launch. For social-media engagement, see social. For cold-email outreach to prospects, see cold-email.
react18-batching-patterns github/awesome-copilot · score 60/100 (grade D)
Provides exact patterns for diagnosing and fixing automatic batching regressions in React 18 class components. Use this skill whenever a class component has multiple setState calls in an async method, inside setTimeout, inside a Promise .then() or .catch(), or in a native event handler. Use it before writing any flushSync call - the decision tree here prevents unnecessary flushSync overuse. Also use this skill when fixing test failures caused by intermediate state assertions that break after React 18 upgrade.
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.
bio-biomart-queries GPTomics/bioSkills · score 59/100 (grade D)
Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).
bio-clinical-biostatistics-multiplicity-graphical GPTomics/bioSkills · score 59/100 (grade D)
Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.
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.
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.
bio-epidemiological-genomics-amr-surveillance GPTomics/bioSkills · score 59/100 (grade D)
Detects acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance pipeline.
bio-epidemiological-genomics-pathogen-typing GPTomics/bioSkills · score 59/100 (grade D)
Assigns isolate identity at the right resolution for the question -- ANI/Mash species triage, 7-locus MLST historical comparability, cgMLST/wgMLST outbreak resolution (chewBBACA, BIGSdb, Ridom SeqSphere, EnteroBase HierCC), in-silico serotyping (SISTR/SeqSero2 Salmonella, SerotypeFinder E. coli, Kaptive Klebsiella, SeroBA pneumococcus, spa+SCCmec S. aureus), and lineage callers (TB-Profiler/Mykrobe barcode for MTBC, Pangolin + Nextclade for SARS-CoV-2, PopPUNK GPSC for S. pneumoniae). Use when typing bacterial isolates for surveillance or outbreak investigation, choosing between cgMLST allele distance and core-SNP distance for cluster definition, harmonising calls across schemas/database versions, assigning MTBC lineage with the Napier 90-SNP barcode, calling Salmonella serovar via SISTR with monophasic Typhimurium awareness, running Pangolin UShER mode with pangolin-data version pinning, or selecting a typing resolution to match the surveillance question.
bio-genome-annotation-annotation-transfer GPTomics/bioSkills · score 59/100 (grade D)
Transfers gene annotations between genome assemblies via coordinate liftover (UCSC liftOver, CrossMap for same-species version updates) or feature/sequence projection (Liftoff for same/close species, miniprot for protein-level cross-species, TOGA/GeMoMa/CAT for distant clades). Covers the coordinate-vs-projection decision by divergence, why a successful lift is not biological confirmation, reference bias, the silent-dropping of unmapped features, build/PAR/MHC/inversion hazards, and transfer-vs-de-novo validation. Use when annotating a new assembly of a species with an existing reference, harmonizing coordinates across builds, or mapping annotations across related species.
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.
competitor-analysis Eronred/aso-skills · score 59/100 (grade D)
When the user wants to analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
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.
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.
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".
Uploadcare Automation ComposioHQ/awesome-claude-skills · score 59/100 (grade D)
Automate Uploadcare file management including listing, storing, inspecting, downloading, and organizing file groups through natural language commands
bio-differential-expression-edger-basics GPTomics/bioSkills · score 58/100 (grade D)
Performs differential expression on bulk RNA-seq count data with edgeR's negative-binomial GLM and quasi-likelihood F-test framework. Covers DGEList construction, filterByExpr, TMM/TMMwsp normalization, robust dispersion estimation, glmQLFit/glmQLFTest, TREAT for magnitude-bounded hypotheses, contrasts via no-intercept designs, voom and voomWithQualityWeights for heterogeneous samples, and the edgeR v4 bias-corrected APL changes. Use when running bulk DE with edgeR, choosing edgeR over DESeq2 (small n, transcript DE via catchSalmon, large samples), needing TREAT for a fold-change-threshold hypothesis, troubleshooting v3-to-v4 reproducibility, building paired or interaction designs, or handling library-quality heterogeneity.
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.
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.
implement-spec mattpocock/skills · score 58/100 (grade D)
Implement the result of /to-spec and /to-tickets in code.
link-building coreyhaines31/marketingskills · score 58/100 (grade D)
When the user wants to earn backlinks or third-party mentions that lift rankings and AI citations. Also use when the user mentions 'link building,' 'linkbuilding,' 'backlinks,' 'get more backlinks,' 'link prospecting,' 'link gap,' 'competitor backlinks,' 'unlinked mentions,' 'link reclamation,' 'broken link building,' 'resource pages,' 'guest posting,' 'get into best-of lists,' 'listicle outreach,' 'domain rating,' 'referring domains,' 'anchor text,' or 'is this link vendor safe.' Use this whenever rankings stall on authority or someone wants off-site mentions that AI engines cite. Never recommend buying links that pass ranking credit: paid or exchanged placements get rel=sponsored or nofollow. For press coverage and journalist requests, see public-relations. For directories, see directory-submissions. For reviews, see referrals. For Reddit and communities, see community-marketing. For on-site AI citation work, see ai-seo.
notaire romainsimon/paperasse · score 58/100 (grade D)
Notaire IA pour le droit immobilier, les successions, les donations, le droit de la famille et le droit des sociétés en France. Copilote juridique pour la préparation d'actes, le conseil patrimonial, les calculs de frais et la vérification de conformité. Couvre le calcul des frais de notaire (DMTO, émoluments, débours, CSI), la plus-value immobilière, les droits de succession et donation, le démembrement, les contrats de mariage, les PACS, les SCI, et la rédaction de projets d'actes (compromis, statuts, testaments). Triggers: notaire, frais de notaire, acte de vente, compromis, succession, donation, héritage, testament, PACS, contrat de mariage, SCI, plus-value immobilière, droits de mutation, DMTO, usufruit, nue-propriété, partage successoral, réserve héréditaire, viager, donation-partage, diagnostics immobilier, droit de préemption, acte notarié, droit immobilier
remotion-video-creation affaan-m/ECC · score 58/100 (grade D)
Best practices for Remotion - Video creation in React. 29 domain-specific rules covering 3D, animations, audio, captions, charts, transitions, and more. Use when building video in React with Remotion — animations, audio, captions, charts, or transitions.
remotion-video-creation affaan-m/everything-claude-code · score 58/100 (grade D)
Best practices for Remotion - Video creation in React. 29 domain-specific rules covering 3D, animations, audio, captions, charts, transitions, and more. Use when building video in React with Remotion — animations, audio, captions, charts, or transitions.
surgical-patch JuliusBrussee/caveman · score 58/100 (grade D)
Fix bugs and small behavior changes at the narrowest responsible layer. Use when regression proof, preserved surrounding behavior, and task-relevant tests matter.
bio-clinical-databases-acmg-classification GPTomics/bioSkills · score 57/100 (grade D)
Applies ACMG/AMP 2015 framework with ClinGen SVI specifications, Tavtigian 2018/2020 Bayesian point system, Abou Tayoun 2018 PVS1 decision tree, Pejaver 2022 and Bergquist 2025 calibrated PP3/BP4 thresholds for REVEL/BayesDel/AlphaMissense, Brnich 2020 PS3/BS3 OddsPath, Walker 2023 SpliceAI splicing framework, and AMP/ASCO/CAP 2017 tumor tiers. Use when classifying germline variants P / LP / VUS / LB / B, applying VCEP-specific CSpec rules, computing Whiffin BS1, or assigning cancer Tier I-IV per Li 2017.
bio-rna-structure-secondary-structure-prediction GPTomics/bioSkills · score 57/100 (grade D)
Predicts RNA secondary structure with ViennaRNA, treating the Boltzmann ensemble (partition function, base-pair probabilities, centroid, MEA, stochastic samples) as the object rather than a single MFE fold. Covers consensus folding from alignments (RNAalifold), SHAPE-constrained folding, RNA-RNA interaction (RNAcofold/RNAduplex/RNAup), local and linear-time methods for long RNA, and pseudoknot-aware tools. Use when folding an RNA and choosing between MFE, centroid, MEA, or ensemble sampling; judging whether a single structure is well-defined; folding long RNAs where a global MFE is meaningless; handling suspected pseudoknots; or weighing thermodynamic versus comparative versus deep-learning prediction.
documentation-writer github/awesome-copilot · score 57/100 (grade D)
Diátaxis Documentation Expert. An expert technical writer specializing in creating high-quality software documentation, guided by the principles and structure of the Diátaxis technical documentation authoring framework.
market-pulse Eronred/aso-skills · score 57/100 (grade D)
When the user wants a comprehensive App Store market overview, daily/weekly market briefing, or combined view of chart movements, trending keywords, featured apps, and new releases. Also use when the user mentions "market overview", "what's happening on the App Store", "market briefing", "weekly report", "market trends", or "state of the market". For chart-specific rank changes only, see market-movers. For keyword trends only, see keyword-research.
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).
catalyst-calendar anthropics/financial-services · score 56/100 (grade D)
Build and maintain a calendar of upcoming catalysts across a coverage universe — earnings dates, conferences, product launches, regulatory decisions, and macro events. Helps prioritize attention and position ahead of events. Triggers on "catalyst calendar", "upcoming events", "what's coming up", "earnings calendar", "event calendar", or "catalyst tracker".
grilling mattpocock/skills · score 56/100 (grade D)
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
postgresql-optimization github/awesome-copilot · score 56/100 (grade D)
PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.
saas-health alirezarezvani/claude-skills · score 56/100 (grade D)
Calculate SaaS health metrics (ARR, MRR, churn, CAC, LTV, NRR) and benchmark against industry standards. Usage: /saas-health <metrics|quick-ratio|simulate> [options]
bio-differential-expression-batch-correction GPTomics/bioSkills · score 55/100 (grade D)
Handles batch effects in bulk RNA-seq via design-matrix inclusion (the correct path for DE), ComBat/ComBat-seq for visualization, SVA for unknown latent factors, RUVSeq for negative-control-gene-anchored unwanted variation, and limma::removeBatchEffect for plotting only. Encodes the Nygaard 2016 cardinal sin against testing on a batch-corrected matrix, the choice between SVA/RUVg/RUVs/RUVr, the confounding non-identifiability problem, the single-cell boundary (Harmony/MNN are NOT for bulk), and the Goh 2017 harmonization critique. Use when designing a DE analysis with batch structure, troubleshooting batch-dominated PCA, choosing ComBat vs ComBat-seq, handling unknown batch via SVA, integrating across studies, or deciding when (rarely) to subtract batch.
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.
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.
Jotform Automation ComposioHQ/awesome-claude-skills · score 55/100 (grade D)
Automate Jotform form listing, user management, activity history, folder organization, and plan inspection through natural language commands
playwright-explore-website github/awesome-copilot · score 55/100 (grade D)
Website exploration for testing using Playwright MCP
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.
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).
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.
morning-note anthropics/financial-services · score 54/100 (grade D)
Draft concise morning meeting notes summarizing overnight developments, trade ideas, and key events for coverage stocks. Designed for the 7am morning meeting format — tight, opinionated, actionable. Triggers on "morning note", "morning meeting", "what happened overnight", "trade idea", "morning call prep", or "daily note".
pytest-coverage github/awesome-copilot · score 54/100 (grade D)
Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.
Wave Accounting Automation ComposioHQ/awesome-claude-skills · score 54/100 (grade D)
Wave Accounting toolkit is not currently available as a native integration. No Wave-specific tools were found in the Composio platform. This skill is a placeholder pending future integration.
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.
hello-world luongnv89/asm · score 53/100 (grade D)
A minimal test skill that greets the user and demonstrates the ASM publish workflow.
playwright-automation-fill-in-form github/awesome-copilot · score 53/100 (grade D)
Automate filling in a form using Playwright MCP
controleur-fiscal romainsimon/paperasse · score 50/100 (grade D)
Inspecteur des finances publiques IA. Simule un contrôle fiscal DGFIP complet sur les comptes d'une entreprise française (SASU, EURL, SAS, SARL). Analyse le FEC, la liasse fiscale, les charges déduites, le compte courant d'associé, la TVA, l'IS selon 8 axes de vérification. Identifie les chefs de redressement potentiels avec montants, base légale et niveaux de risque. Triggers: contrôle fiscal, redressement, vérification comptabilité, DGFIP, FEC, déductibilité, audit fiscal, tax audit
implement mattpocock/skills · score 48/100 (grade F)
Implement a piece of work based on a spec or set of tickets.
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.
varied-search davidondrej/skills · score 47/100 (grade F)
Research a topic across the web, GitHub, and X/Twitter with DeepAPI and produce a concise Markdown report. Use for varied-search or requests to compare web coverage, relevant repositories, and social discussion.
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.)