Design Skills

UI/UX design and frontend styling. This page lists all 906 Design 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 Design.

dont-make-me-think luongnv89/skills · score 95/100 (grade A)
Review UI usability using Steve Krug's principles and produce a scannable report. Use for UX audits of screenshots, URLs, or code. Don't use for brand critique, WCAG audits, or backend/API review.
brand-name-checker luongnv89/skills · score 94/100 (grade A)
Check product and brand names for conflicts across trademarks, domains, social handles, and package registries. Returns a risk level and Proceed/Modify/Abandon verdict. Don't use for name brainstorming, logo design, or trademark filings.
ux-ax-review luongnv89/skills · score 94/100 (grade A)
Review website/app UX for humans and AX for AI/search; produce an evidence-backed audit and improvement plan across usability, brand, access, speed, conversion and discoverability. Don't use for UI builds, SEO-only edits, or legal certification.
frontend-design luongnv89/skills · score 93/100 (grade A)
Build production-grade frontend interfaces with distinctive aesthetics and working code. Use for UI components, pages, or frontend features. Don't use for backend/API work or usability-only audits.
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.
design-optimizer luongnv89/skills · score 92/100 (grade A)
Optimize a website or app design in one run: capture the page once, audit usability, UX/AX, virality and agent readiness, merge overlaps into one prioritized report, apply fixes on opt-in. Don't use for one lens (dont-make-me-think, ux-ax-review).
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.
logo-designer luongnv89/skills · score 92/100 (grade A)
Generate professional SVG logos from project context: 7 brand variants plus a showcase HTML page. Use for product marks, wordmarks, icons, and favicons. Don't use for raster-only logos, illustrations, or full brand guidelines.
tad-generator luongnv89/skills · score 92/100 (grade A)
Generate a Technical Architecture Document (TAD) from a PRD. Use when asked to design system architecture or define how a product is built. Updates tad.md and reports GitHub links. Don't use for PRD authoring, sprint tasks, or code implementation.
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.
logo-to-stickers sickn33/antigravity-awesome-skills · score 89/100 (grade B)
Turn a brand mark or existing IP into consistent, playful paper stickers with small visual stories and separate transparent images. Use for brand characters and website sticker sets.
product-design-harness sickn33/antigravity-awesome-skills · score 89/100 (grade B)
Use when a product direction, feature, workflow, experiment, launch, feedback signal, automation, or scale decision needs judgment before execution or the next iteration.
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\".
ai-logo-maker sickn33/antigravity-awesome-skills · score 87/100 (grade B)
Install and use the official AI Logo Maker package, pinned by digest, for paid hosted work on the Beatra service.
poster-design-studio sickn33/antigravity-awesome-skills · score 87/100 (grade B)
Install and use the official AI Poster Maker package, pinned by digest, for paid hosted work on the Beatra service.
shap K-Dense-AI/claude-scientific-skills · score 87/100 (grade B)
Explain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.
agent-architecture github/awesome-copilot · score 86/100 (grade B)
Design AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.
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.
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.
azure-developer-cli github/awesome-copilot · score 85/100 (grade B)
Design, create, review, migrate, or troubleshoot Azure Developer CLI (azd) projects using current Microsoft guidance. Use for azd, azure.yaml, AZD templates, Bicep or Terraform under infra, AZD environments and secrets, hooks, deployment workflows, and azd-managed CI/CD.
browser-harness sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Drive an existing browser through CDP for authenticated, visual, or interactive web automation.
design-token-contrast sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Checks WCAG 2.2 contrast between the color tokens of a project (light and dark theme) and suggests the closest passing color that keeps the hue.
find-and-verify-affiliate-program Affitor/affiliate-skills · score 85/100 (grade B)
Find affiliate programs in the OpenAffiliate registry, then confirm every term on the brand's own page and report each one with a verbatim quote and its source URL. Use this skill when the user wants affiliate terms they can rely on: before signing up, before publishing a review or comparison, when a listing looks outdated, or when two sources disagree. Also trigger for: "verify this affiliate program", "is X's affiliate commission still 30%", "what's the cookie length for X", "check the affiliate terms", "does X have an affiliate program", "find a recurring program and confirm the terms", "is this commission rate real", "source for X's affiliate terms", "fact-check this affiliate program", "what does X pay affiliates".
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.
md2video-audio sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Convert Markdown documents into narrated MP4 videos with synchronized visuals and voice narration.
uxkin-research sickn33/antigravity-awesome-skills · score 85/100 (grade B)
Research how real products handle a screen, flow or visual style before designing it: search UXKIN's real iOS screens, user journeys and website design systems, compare several and report what they share.
animated-github-profile sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Build high-impact, animated GitHub profile READMEs that play like mini-movies using pure SVG, CSS, and SMIL animations. Covers dark/light theme switching, swinging lanyard ID badges, tech orbits, local stat cards, and automated contribution graphs.
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.
etetoolkit K-Dense-AI/claude-scientific-skills · score 84/100 (grade B)
Analyzes, manipulates, compares, annotates, and visualizes phylogenetic or other hierarchical trees with ETE 4. Supports Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy, SmartView exploration, and publication rendering. Applies to existing trees after alignment and phylogenetic inference, rather than inferring trees from raw sequences.
loop-library sickn33/antigravity-awesome-skills · score 84/100 (grade B)
Find, compare, adapt, and design bounded AI-agent feedback loops with explicit checks, stop rules, guardrails, and handoffs.
ui-styling nextlevelbuilder/ui-ux-pro-max-skill · score 84/100 (grade B)
Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs. Use when building user interfaces, implementing design systems, creating responsive layouts, adding accessible components (dialogs, dropdowns, forms, tables), customizing themes and colors, implementing dark mode, generating visual designs and posters, or establishing consistent styling patterns across applications.
dali-short-address-commissioner sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Commissions DALI and DALI-2 (IEC 62386) lighting buses: short-address assignment (0-63), 24-bit binary search collision resolution, groups, and DT8 color control. Trigger phrases: commission dali, dali short address, dali collision resolution, dali bus addressing, dali-2 setup.
neuropixels-analysis K-Dense-AI/claude-scientific-skills · score 83/100 (grade B)
Analyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
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".
theme-factory sickn33/antigravity-awesome-skills · score 83/100 (grade B)
This skill provides a curated collection of professional font and color themes, each with carefully selected color palettes and font pairings. Once a theme is chosen, it can be applied to any artifact.
ui-states sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Design and build the UI states agents forget: first use, empty, loading, error, offline, no results, long content, permission denied and success.
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.
wp-guard sickn33/antigravity-awesome-skills · score 83/100 (grade B)
Review generated or changed WordPress plugins, themes, and blocks for security, internationalization, performance, and API correctness.
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.
azure-resource-visualizer github/awesome-copilot · score 82/100 (grade B)
Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. Use this skill when the user asks for a diagram of their Azure resources or help in understanding how the resources relate to each other.
design-system sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Mechanical implementation invariants for frontend design: token architecture, typography hierarchy, loading order, FOUT prevention, chrome stability, motion timing, color semantics. Use with design when building components, pages, or design systems.
generate-image K-Dense-AI/claude-scientific-skills · score 82/100 (grade B)
Generates or edits images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.
seo-programmatic sickn33/antigravity-awesome-skills · score 82/100 (grade B)
Plan and audit programmatic SEO pages generated at scale from structured data. Use when designing templates, URL systems, internal linking, quality gates, and index-bloat safeguards for pages at scale.
terraform-patterns alirezarezvani/claude-skills · score 82/100 (grade B)
Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state management strategies, provider configuration, security hardening, policy-as-code with Sentinel/OPA, and CI/CD plan/apply workflows. Use when: user wants to design Terraform modules, manage state backends, review Terraform security, implement multi-region deployments, or follow IaC best practices.
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.
api-and-interface-design sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
apify-influencer-discovery sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Find and evaluate influencers for brand partnerships, assess public authenticity signals, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
baoyu-infographic JimLiu/baoyu-skills · score 81/100 (grade B)
Generate professional infographics with 21 layout types and 22 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图".
brooks-lint sickn33/antigravity-awesome-skills · score 81/100 (grade B)
AI code reviewer grounded in classic software engineering books for catching design smells, coupling issues, and architectural risks.
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.
customer-psychographic-profiler sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Build an evidence-grounded customer profile of motivations, fears, identity, and trust barriers before positioning, copywriting, or funnel design.
deeptools K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
email-marketing-bible sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Data-backed email marketing for AI agents: automation flows, deliverability triage, copy de-slopping, AI email design, ESP control via MCP with send gates and compliance.
free-tier-strategy sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Design free tiers that convert to paid without creating resentment or abuse. Trigger phrases: free tier design, freemium model, free trial strategy, free tier limits, developer free plan, open source commercial, feature gating, upgrade triggers, free tier conversion
grand-slam-offer Affitor/affiliate-skills · score 81/100 (grade B)
Design irresistible affiliate offers using the Hormozi Grand Slam framework. Triggers on: "create an offer for", "design my offer", "grand slam offer", "make an irresistible offer", "why should someone buy through my link", "offer framework", "value proposition for", "Hormozi offer", "offer stack", "make my offer irresistible", "craft an offer", "what makes my offer different", "offer design", "increase perceived value".
hig-technologies sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Review Apple-platform technology UX against HIG patterns for payments, health data, identity, Siri, AR, cloud sync, and shared experiences. Use for integration flow design, permission planning, and accessibility checks.
hugging-face-trackio sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI).
imagen sickn33/antigravity-awesome-skills · score 81/100 (grade B)
AI image generation skill powered by Google Gemini, enabling seamless visual content creation for UI placeholders, documentation, and design assets.
improve-codebase-architecture sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
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.
mdpr-skill sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Review MDPR Markdown presentation workflows with semantic hints, visual checks, and deterministic renderer boundaries.
pro-motion sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Make a motion-graphics launch, brand or promo film audio first: plan the music, then render the film in code (canvas to MP4) cut to the track. Use for 发布视频, 宣传片, TVC, BGM, Suno prompts.
prometheus-grafana sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Set up metrics collection and visualization with Prometheus and Grafana.
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.
rayden-use sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Build and maintain Rayden UI components and screens in Figma via Figma MCP with full design token enforcement
scanpy sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.
scientific-visualization K-Dense-AI/claude-scientific-skills · score 81/100 (grade B)
Creates and audits truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use it for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.
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.
shadcn sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Manages shadcn/ui components and projects, providing context, documentation, and usage patterns for building modern design systems.
styleseed-design-review sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Reviews UI/frontend code and tells you exactly why it \"looks AI-generated\" — then how to fix it.
tastegate sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Build or fix a frontend so it looks designed, not AI-generated, then prove it in a real browser: renders at phone and desktop width and fails on overlap, low contrast and AI-slop defaults.
ui-score sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Score a UI file's design quality 0-100 against StyleSeed's design language — per-category breakdown, the worst offenders, and a prioritized fix list. A quantified version of /ss-review.
ui-setup sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Interactive setup wizard — guides you step-by-step to configure the design system for your project
visual-emotion-engineer sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Create a visual direction brief for color, typography, imagery, and hierarchy when design must support a defined emotion, culture, and accessibility needs.
write-design-md sickn33/antigravity-awesome-skills · score 81/100 (grade B)
Write or update a project's DESIGN.md from the colors, type, spacing and components it really uses, with rules agents follow so new screens match.
xlsx ComposioHQ/awesome-claude-skills · score 81/100 (grade B)
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
article-illustrations sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Generate hand-drawn 16:9 article illustrations with the Grav character IP, sparse annotations, and absurd but clear visual metaphors.
automated-triage sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
bonus-stack-builder Affitor/affiliate-skills · score 80/100 (grade B)
Design exclusive bonus packages that make YOUR affiliate link the obvious choice. Triggers on: "create bonuses for", "bonus stack", "what bonuses should I offer", "bonus ideas for", "exclusive bonuses", "differentiate my affiliate link", "why buy through my link", "affiliate bonuses", "bonus package", "what can I offer as a bonus", "design bonuses", "build a bonus stack".
brand-guidelines sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Write copy following Sentry brand guidelines. Use when writing UI text, error messages, empty states, onboarding flows, 404 pages, documentation, marketing copy, or any user-facing content. Covers both Plain Speech (default) and Sentry Voice tones.
brand-guidelines-anthropic sickn33/antigravity-awesome-skills · score 80/100 (grade B)
To access Anthropic's official brand identity and style resources, use this skill.
brand-guidelines-community sickn33/antigravity-awesome-skills · score 80/100 (grade B)
To access Anthropic's official brand identity and style resources, use this skill.
ckw-design sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Frontend design entry point: direction, design system, visual philosophy. Use whenever building or touching the look of any web UI (components, pages, dashboards, React/Vue/HTML-CSS) or when the user says \"make this look better\", \"fix the spacing/layout\", or mentions styling, color, type, or polish.
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.
design-ux sickn33/antigravity-awesome-skills · score 80/100 (grade B)
UX / usability audit — heuristic evaluation of INTERACTIVE UIs (not just visual polish). Load with design when a UI \"feels off\", \"sucks to use\", is hard to learn, needs an instruction wall, or before shipping an interactive tool/editor/app.
emil-design-eng sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Use when designing or reviewing polished product UI with Emil Kowalski-inspired animation, interaction, and component craft guidance.
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.
google-cloud-storage-bucket-architect google/skills · score 80/100 (grade B)
Creates Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.
infographics K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Creates and reviews infographics with Nano Banana 2 via OpenRouter. Use for statistical summaries, timelines, comparisons, processes, and visual explanations with supplied data or optional Sonar research. Supports ten layouts, eight style presets, reference images, and accessible palette starting points.
json-canvas sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Create and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
latex-posters K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Creates research posters in LaTeX using beamerposter, tikzposter, or baposter. Use for conference posters, academic presentations, multi-column scientific layouts, figure integration, typography, compilation, and PDF preflight.
lead-magnets sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Plan and optimize lead magnets for email capture and lead generation. Use when designing gated content, checklists, templates, downloadable resources, or other offers that convert visitors into subscribers.
mcp-builder sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
pakistan-payments-stack sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Design and implement production-grade Pakistani payment integrations (JazzCash, Easypaisa, bank/PSP rails, optional Raast) for SaaS with PKR billing, webhook reliability, and reconciliation.
privacy-by-design sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Use when building apps that collect user data. Ensures privacy protections are built in from the start—data minimization, consent, encryption.
prototype sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
recsys-pipeline-architect sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Designs composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework
scientific-slides K-Dense-AI/claude-scientific-skills · score 80/100 (grade B)
Builds slide decks and presentations for research talks. Used for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
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.
seo-image-gen sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Generate SEO-focused images such as OG cards, hero images, schema assets, product visuals, and infographics. Use when image generation is part of an SEO workflow or content publishing task.
shopify-development sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Build Shopify apps, extensions, themes using GraphQL Admin API, Shopify CLI, Polaris UI, and Liquid.
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.
ui-review sickn33/antigravity-awesome-skills · score 80/100 (grade B)
Review UI code for design system compliance, accessibility, and best practices
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.
ai-agent-tool-routing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Use when designing or reviewing an AI agent tool registry or MCP router: document parameter schemas, caller authorization, execution limits, replay-safe retries and verification evidence.
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.
baoyu-article-illustrator JimLiu/baoyu-skills · score 79/100 (grade C)
Analyzes article structure, identifies positions requiring visual aids, generates illustrations with Type × Style × Palette three-dimension approach. Use when user asks to "illustrate article", "add images", "generate images for article", or "为文章配图".
brand-perception-psychologist sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Audit visual, verbal, and behavioral brand signals and propose alignment changes when market perception differs from the intended position.
canva-automation sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Automate Canva tasks via Rube MCP (Composio): designs, exports, folders, brand templates, autofill. Always search tools first for current schemas.
code-showcase-core-components sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Core component library and design system patterns. Use when building UI, using design tokens, or working with the component library.
deployment-pipeline-design sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Architecture patterns for multi-stage CI/CD pipelines with approval gates and deployment strategies.
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.
developer-signup-flow sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design frictionless signup experiences for developers including GitHub OAuth, API key generation, and onboarding personalization.
fixing-accessibility sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Audit and fix HTML accessibility issues including ARIA labels, keyboard navigation, focus management, color contrast, and form errors. Use when adding interactive controls, forms, dialogs, or reviewing WCAG compliance.
fullstack-dev MiniMax-AI/skills · score 79/100 (grade C)
Full-stack backend architecture and frontend-backend integration guide. TRIGGER when: building a full-stack app, creating REST API with frontend, scaffolding backend service, building todo app, building CRUD app, building real-time app, building chat app, Express + React, Next.js API, Node.js backend, Python backend, Go backend, designing service layers, implementing error handling, managing config/auth, setting up API clients, implementing auth flows, handling file uploads, adding real-time features (SSE/WebSocket), hardening for production. DO NOT TRIGGER when: pure frontend UI work, pure CSS/styling, database schema only.
gpt-taste sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Use when generating elite GSAP-heavy frontend pages with strict AIDA structure, wide hero typography, and gapless bento grids.
mcp-builder warpdotdev/oz-skills · score 79/100 (grade C)
Build high-quality MCP (Model Context Protocol) servers that let LLMs interact with external services through well-designed tools. Use when creating MCP servers to integrate APIs or services in Python (FastMCP) or Node/TypeScript (MCP SDK).
meta-tag-generator sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Meta Tag Generator. Use when working with page summary, URL and optional brand or social image.
multi-agent-architect sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design and optimize production-grade multi-agent systems with LangGraph, LangChain, and DeepAgents for complex AI workflows.
multi-tenant-llm-hosting sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design secure, multi-tenant LLM hosting platforms with tenant isolation,
n8n-agents sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design n8n AI agents, chains, classifiers, extractors, tool calling, memory, RAG, structured output, and human-review flows.
n8n-error-handling sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design visible, structured, recoverable n8n failures using error outputs, retries, Error Trigger workflows, and HTTP error responses.
offers sickn33/antigravity-awesome-skills · score 79/100 (grade C)
When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure.
qrx sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Make branded, print-ready art QR codes to validate before use with QRX (qrx.codes). Use when a link needs a QR code that looks like artwork or matches a brand for print, packaging, signs, slides or event badges, and to list or re-point QRX codes. Not for plain QR codes the agent makes locally.
scanpy K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Performs Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or SingleCellExperiment RDS conversion to h5ad. Applies to established exploratory scRNA-seq workflows with explicit count and expression provenance; complementary skills cover scvi-tools models and AnnData format details.
scientific-critical-thinking K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Evaluates scientific claims and evidence quality. Applies to experimental design validity, biases and confounders, statistical interpretation, evidence grading frameworks (GRADE, Cochrane Risk of Bias), and teaching critical analysis. Supports evidence appraisal and identifying flaws; formal peer review writing belongs to peer-review.
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.
sre-dashboards sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design and operationalize SRE dashboards that surface reliability, latency,
supabase-postgres-best-practices sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.
threejs-skills sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Create 3D scenes, interactive experiences, and visual effects using Three.js. Use when user requests 3D graphics, WebGL experiences, 3D visualizations, animations, or interactive 3D elements.
tone-of-voice-analyzer sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Tone of Voice Analyzer. Use when working with text and optional brand voice sample.
tool-design sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Build tools that agents can use effectively, including architectural reduction patterns. Use when creating new tools for agent systems, debugging tool-related failures or misuse, or optimizing existing tool sets for better agent performance.
trending-keyword-visualizer sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Trending Keyword Visualizer. Use when working with dated keyword interest or volume series with source.
ui-component sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Generate a new UI component following the StyleSeed design conventions
uiverify-triage-visual-changes sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Triage a UI Verify visual regression build from your coding agent over MCP: sort changed screenshots into regressions, intended changes and noise, then accept baselines.
usage-based-pricing sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design pricing models that developers understand, accept, and can predict. Trigger phrases: usage-based pricing, API pricing, metered billing, developer pricing, pricing page, cost calculator, pay as you go, pricing transparency, competitive pricing, developer billing
ux-flow sickn33/antigravity-awesome-skills · score 79/100 (grade C)
Design user flows and navigation structure following proven UX patterns
vaex K-Dense-AI/claude-scientific-skills · score 79/100 (grade C)
Processes large tabular scientific datasets with Vaex expressions, filtered views, streamed statistics, binned visualizations, and file conversion. Use for larger-than-RAM HDF5, Arrow, CSV, or Parquet analysis, virtual feature engineering, or Vaex ML preprocessing; distinguishes these operations from estimators and conversions that materialize data.
xml-sitemap-visualizer sickn33/antigravity-awesome-skills · score 79/100 (grade C)
XML Sitemap Visualizer. Use when working with XML sitemap or sitemap index.
advanced-evaluation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Design LLM-as-judge rubrics, direct scores and pairwise comparisons. Use for judge models, evals, position bias and calibration against human labels.
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".
cirq sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.
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.
codebase-to-wordpress-converter sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Expert skill for converting any codebase (React/HTML/Next.js) into a pixel-perfect, SEO-optimized, and dynamic WordPress theme.
context-degradation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems.
create-implementation-plan github/awesome-copilot · score 78/100 (grade C)
Create a new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
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.
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.
developer-listening sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Monitor what developers say about your brand, competitors, and the problems they're solving. Track mentions and conversations across GitHub, Hacker News, Reddit, Stack Overflow, Twitter, and Discord.
docs-architect sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Creates comprehensive technical documentation from existing codebases. Analyzes architecture, design patterns, and implementation details to produce long-form technical manuals and ebooks.
emotional-arc-designer sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Map the emotional progression of a narrative, page, or campaign when content needs a coherent path from attention to action.
figma-automation sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Automate Figma tasks via Rube MCP (Composio): files, components, design tokens, comments, exports. Always search tools first for current schemas.
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.
google-no-code sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Design Google Forms and wire Apps Script triggers (onFormSubmit) for email alerts, spreadsheet logging, and dynamic questions — no code editor required.
hugging-face-datasets sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
inbox-triage alirezarezvani/claude-skills · score 78/100 (grade C)
Runs a full inbox triage using the knowledge base created by the 'inbox-setup' skill. Light-intake by design (most invocations skip questions and run with KB-default preferences); asks at most 2 grill-me override questions when invocation is outside normal cadence or includes category-skip intent. Searches recent emails, classifies them via the user's taxonomy, researches new senders, generates recommendations, drafts replies (NEVER sends), delivers a report in the user's preferred format, and updates the knowledge base with learnings. Designed to run on a recurring schedule (1-3x daily) or on demand. Use when the user wants their inbox processed, in any variation (e.g., 'triage my inbox', 'inbox triage', 'check my email', 'run email triage', 'process my inbox', 'what's new in my email', 'handle my email', 'email triage'). Requires the inbox-setup skill to have been run first.
machine-learning-ops-ml-pipeline sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Design and implement a complete ML pipeline for: $ARGUMENTS
matplotlib sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots.
multi-agent-patterns sickn33/antigravity-awesome-skills · score 78/100 (grade C)
This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.
plotly sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
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.
price-psychology-strategist sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Design pricing presentation, anchors, and tiers when an offer needs clearer value and fairness without misleading comparisons.
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.
revops sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Design and improve revenue operations, lead lifecycle rules, scoring, routing, handoffs, and CRM process automation. Use when marketing, sales, and customer success workflows need clearer operational structure.
seaborn K-Dense-AI/claude-scientific-skills · score 78/100 (grade C)
Creates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.
shader-dev MiniMax-AI/skills · score 78/100 (grade C)
Comprehensive GLSL shader techniques for creating stunning visual effects — ray marching, SDF modeling, fluid simulation, particle systems, procedural generation, lighting, post-processing, and more.
stitch-ui-design sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Expert guidance for crafting effective prompts in Google Stitch, the AI-powered UI design tool by Google Labs. This skill helps create precise, actionable prompts that generate high-quality UI designs for web and mobile applications.
team-composition-analysis sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Design optimal team structures, hiring plans, compensation strategies, and equity allocation for early-stage startups from pre-seed through Series A.
ui-pattern sickn33/antigravity-awesome-skills · score 78/100 (grade C)
Generate a composed UI pattern (card layout, list, form section, grid, etc.) using design system primitives
ui-tokens sickn33/antigravity-awesome-skills · score 78/100 (grade C)
View, add, or modify design tokens in the StyleSeed design system
value-ladder-architect Affitor/affiliate-skills · score 78/100 (grade C)
Design the complete free-to-premium value ladder for affiliate promotions. Triggers on: "value ladder", "customer journey", "upsell path", "ascension model", "free to paid funnel", "tripwire offer", "upsell strategy", "downsell", "product ladder", "price ladder", "customer ascension", "funnel architecture", "map my funnel", "design my funnel stages", "monetization path".
video-use browser-use/video-use · score 78/100 (grade C)
Edit any video by conversation. Transcribe, cut, color grade, generate overlay animations, burn subtitles — for talking heads, montages, tutorials, travel, interviews. No presets, no menus. Ask questions, confirm the plan, execute, iterate, persist. Production-correctness rules are hard; everything else is artistic freedom.
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.
anti-slop-design sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Autonomous Principal Design Technologist. Cures vibe-coded software from AI frontend slop using curated token archetypes and 7-axis quality gating.
api-integration sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Designs event-driven architectures, webhook systems, API chaining flows, ETL pipelines, and integration patterns between services.
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.
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.
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.
chro-advisor alirezarezvani/claude-skills · score 77/100 (grade C)
People leadership for scaling companies. Hiring strategy, compensation design, org structure, culture, and retention. Use when building hiring plans, designing comp frameworks, restructuring teams, managing performance, building culture, or when user mentions CHRO, HR, people strategy, talent, headcount, compensation, org design, retention, or performance management.
crewai sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Design role-based agents, tasks, crews, and flows with CrewAI.
design-thinking sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Direction and intent for frontend design. Use with design when defining purpose, tone, domain, color world, and review bar; includes cross-domain lens from cinema, architecture, marketing, UX, automotive, industrial design.
drizzle-orm-expert sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Expert in Drizzle ORM for TypeScript — schema design, relational queries, migrations, and serverless database integration. Use when building type-safe database layers with Drizzle.
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.
gif-sticker-maker MiniMax-AI/skills · score 77/100 (grade C)
Convert photos (people, pets, objects, logos) into 4 animated GIF stickers with captions. Use when: user wants to create cartoon stickers, GIF expressions, emoji packs, animated avatars, or convert photos to Funko Pop / Pop Mart blind box style animations. Triggers: sticker, GIF, cartoon, emoji, expression pack, avatar animation.
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.
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".
ios-design-review garrytan/gstack · score 77/100 (grade C)
Visual design audit for iOS apps on real hardware. (gstack)
json-canvas kepano/obsidian-skills · score 77/100 (grade C)
Create and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
lightning-architecture-review sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Review Bitcoin Lightning Network protocol designs, compare channel factory approaches, and analyze Layer 2 scaling tradeoffs. Covers trust models, on-chain footprint, consensus requirements, HTLC/PTLC compatibility, liveness, and watchtower support.
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.
makepad-font sickn33/antigravity-awesome-skills · score 77/100 (grade C)
CRITICAL: Use for Makepad font and text rendering. Triggers on: makepad font, makepad text, makepad glyph, makepad typography, font atlas, text layout, font family, font size, text shaping, makepad 字体, makepad 文字, makepad 排版, makepad 字形
marketing-context alirezarezvani/claude-skills · score 77/100 (grade C)
Create and maintain the marketing context document that all marketing skills read before starting. Use when the user mentions 'marketing context,' 'brand voice,' 'set up context,' 'target audience,' 'ICP,' 'style guide,' 'who is my customer,' 'positioning,' or wants to avoid repeating foundational information across marketing tasks. Run this at the start of any new project before using other marketing skills.
matplotlib K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Creates and customizes scientific plots with Matplotlib. Used for fine-grained control over plot elements, novel plot types, and scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
memory-systems sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Design short-term, long-term, and graph-based memory architectures. Use when building agents that must persist across sessions, needing to maintain entity consistency across conversations, or implementing reasoning over accumulated knowledge.
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.
openpiv K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Performs Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.
organization-design sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Org structure register: department, type, parent, head, location, approved against actual headcount, annual budget, cost centre code and establishment date. Use for org design.
pricing-strategist alirezarezvani/claude-skills · score 77/100 (grade C)
Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.
refactor github/awesome-copilot · score 77/100 (grade C)
Surgical code refactoring to improve maintainability without changing behavior. Covers extracting functions, renaming variables, breaking down god functions, improving type safety, eliminating code smells, and applying design patterns. Less drastic than repo-rebuilder; use for gradual improvements.
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).
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.
tamarind K-Dense-AI/claude-scientific-skills · score 77/100 (grade C)
Provides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.
ui-ux-pro-max sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Comprehensive design guide for web and mobile applications. Use when designing new UI components or pages, choosing color palettes and typography, or reviewing code for UX issues.
web-design-guidelines sickn33/antigravity-awesome-skills · score 77/100 (grade C)
Review files for compliance with Web Interface Guidelines.
workflow-builder alirezarezvani/claude-skills · score 77/100 (grade C)
Design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool. Use when a user wants to build, create, author, scaffold, or run a custom Claude Code workflow, orchestrate sub-agents (fan-out, pipeline, loop, judge-panel), or automate a repeatable multi-step task across fresh-context agents.
agent-memory-systems sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Design tenant-scoped memory, retrieval and retention for agents. Use when planning RAG, conversation history, vector stores or remembering across sessions.
ai-engineering-toolkit sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Overview of six AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
apify-brand-reputation-monitoring sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
attack-tree-construction sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
autonomous-agent-patterns sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Design patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
banner-design nextlevelbuilder/ui-ux-pro-max-skill · score 76/100 (grade C)
Design banners for social media, ads, website heroes, creative assets, and print. Multiple art direction options with optional generated or supplied visuals. Actions: design, create, generate banner. Platforms: Facebook, Twitter/X, LinkedIn, YouTube, Instagram, Google Display, website hero, print. Styles: minimalist, gradient, bold typography, photo-based, illustrated, geometric, retro, glassmorphism, 3D, neon, duotone, editorial, collage.
baoyu-xhs-images JimLiu/baoyu-skills · score 76/100 (grade C)
Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes. Breaks content into 1-10 cartoon-style image cards optimized for social media engagement. Use when user mentions "小红书图片", "小红书种草", "小绿书", "微信图文", "微信贴图", "image cards", "图片卡片", baoyu-xhs-images, or wants social media infographic series.
baseline-ui sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Quickly deslop UI code by fixing spacing, hierarchy, typography, and small layout issues. Use when the interface needs a fast cleanup or polish pass.
brand-growth-system-builder sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Route requests across 13 brand and growth modules. Use when an SME needs help choosing branding, website, local SEO, content, or cloud-planning workflows.
brooks-review sickn33/antigravity-awesome-skills · score 76/100 (grade C)
PR code review that surfaces decay risks, design smells, and maintainability issues with concrete Symptom → Source → Consequence → Remedy findings, drawing on twelve classic engineering books.
cmo-advisor alirezarezvani/claude-skills · score 76/100 (grade C)
Marketing leadership for scaling companies. Brand positioning, growth model design, marketing budget allocation, and marketing org design. Use when designing brand strategy, selecting growth models (PLG vs sales-led vs community-led), allocating marketing budgets, building marketing teams, or when user mentions CMO, brand strategy, growth model, CAC, LTV, channel mix, or marketing ROI.
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.
core-components sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Core component library and design system patterns. Use when building UI, using design tokens, or working with the component library.
culture-architect alirezarezvani/claude-skills · score 76/100 (grade C)
Build, measure, and evolve company culture as operational behavior — not wall posters. Covers mission/vision/values workshops, values-to-behaviors translation, culture code creation, culture health assessment, and cultural rituals by stage. Use when building company values, assessing culture health, designing cultural rituals, creating culture codes, handling culture clashes, or when user mentions culture, values, culture debt, founder culture, or culture code.
daily-gift sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Relationship-aware daily gift engine with five-stage creative pipeline — editorial judgment, synthesis, concept generation, visual strategy, and rendering in H5, image, or video
developer-sandbox sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Design and build interactive playgrounds that let developers experience your product without commitment. This skill covers playground architecture, pre-populated examples, embedding strategies, gating decisions, and converting playground users to signups.
devops-pipeline-builder sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Design and implement CI/CD pipelines, Docker configurations, deployment
diagram-design cathrynlavery/diagram-design · score 76/100 (grade C)
Create branded architecture, architecture delta, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, exploded axonometric, axonometric plan, Venn, pyramid/funnel, treemap and marimekko, heatmap, bar and dumbbell, waterfall, line (slopegraph, ridgeline, streamgraph, bump), Gantt and scatter charts (bubble, beeswarm), high-level, process, medallion, data flow, DP integration, DP security matrix, Sankey, fishbone, Wardley map, kanban, user journey, service blueprint, deployment, dependency graph, UML class, story map, or database schema diagrams as HTML/SVG/PNG, with .drawio, Mermaid, and .excalidraw import, plus lifecycle phase maps, block decomposition trees, and onboarding guidance.
engineering-advanced-skills alirezarezvani/claude-skills · score 76/100 (grade C)
Index of 37 advanced engineering agent skills for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Use when browsing or choosing among the POWERFUL-tier engineering skills: agent design, RAG, MCP servers, CI/CD, database design, observability, security auditing, changelog/release automation, reliability (SLO/chaos/flags/operators), platform ops.
frontend-design sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Design and implement a distinctive frontend within the product’s existing brand, accessibility, performance and framework constraints.
frontend-slides zarazhangrui/frontend-slides · score 76/100 (grade C)
Create stunning, animation-rich HTML presentations from scratch or by converting PowerPoint files. Use when the user wants to build a presentation, convert a PPT/PPTX to web, or create slides for a talk/pitch. Helps non-designers discover their aesthetic through visual exploration rather than abstract choices.
gcp-cloud-architect alirezarezvani/claude-skills · score 76/100 (grade C)
Design GCP architectures for startups and enterprises. Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure BigQuery pipelines, optimize GCP costs, or migrate to GCP. Covers Cloud Run, GKE, Cloud Functions, Cloud SQL, BigQuery, and cost optimization.
hig-project-context sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Create or update a shared Apple design context document that other HIG skills use to tailor guidance.
hugging-science K-Dense-AI/claude-scientific-skills · score 76/100 (grade C)
Discovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.
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.
loss-aversion-designer sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Compare gain and loss framing and describe credible costs of inaction when an offer needs urgency without fearmongering.
mcp-builder anthropics/skills · score 76/100 (grade C)
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
monopoly sickn33/antigravity-awesome-skills · score 76/100 (grade C)
MONOPOLY is a Senior System Design Engineer skill for architecting, reviewing, and scaling systems. Triggers on requests involving architecture, databases, scaling, microservices, or infrastructure design. Proactively engages to design resilient backend systems.
popup-cro sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Create and optimize popups, modals, overlays, slide-ins, and banners to increase conversions without harming user experience or brand trust.
programmatic-seo sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Design and evaluate programmatic SEO strategies for creating SEO-driven pages at scale using templates and structured data.
project-development sickn33/antigravity-awesome-skills · score 76/100 (grade C)
This skill covers the principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development.
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).
radix-ui-design-system sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Build accessible design systems with Radix UI primitives. Headless component customization, theming strategies, and compound component patterns for production-grade UI libraries.
seaborn sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Seaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.
software-architecture sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.
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.
workflow-orchestration-patterns sickn33/antigravity-awesome-skills · score 76/100 (grade C)
Master workflow orchestration architecture with Temporal, covering fundamental design decisions, resilience patterns, and best practices for building reliable distributed systems.
android-native-dev MiniMax-AI/skills · score 75/100 (grade C)
Android native application development and UI design guide. Covers Material Design 3, Kotlin/Compose development, project configuration, accessibility, and build troubleshooting. Read this before Android native application development.
api-integration-architect sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Design, implement, debug, and optimize API integrations with expert-level
api-security-best-practices sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities
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.
archify-tuning tt-a1i/archify · score 75/100 (grade C)
Improve Archify diagram accuracy, visual quality and complete authoring speed with fewer repairs. Use for generation experiments or evaluating changes to layout, routing, diagnostics, authoring instructions and acceptance rules against actual diagrams and agent traces.
architecture sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
asc-cli-usage rudrankriyam/app-store-connect-cli-skills · score 75/100 (grade C)
Guidance for using asc cli in this repo (flags, output formats, pagination, auth, and discovery). Use when asked to run or design asc commands or interact with App Store Connect via the CLI.
aws-solution-architect alirezarezvani/claude-skills · score 75/100 (grade C)
Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization.
brainstorming sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.
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.
business-operations-skills alirezarezvani/claude-skills · score 75/100 (grade C)
Use when running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms, SOP/runbook authoring, procurement spend. Triggers on "BizOps review", "where's the bottleneck", "vendor health", "internal SOP", "all-hands deck", "spend categorization", "capacity for Q3", "process mapping". Forks context to route to one of six BizOps sub-skills (process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizer) and returns a digest. Distinct from business-growth (external sales motion) and c-level-advisor (strategic, not operational).
canvas-design sickn33/antigravity-awesome-skills · score 75/100 (grade C)
These are instructions for creating design philosophies - aesthetic movements that are then EXPRESSED VISUALLY. Output only .md files, .pdf files, and .png files.
cc-skill-backend-patterns sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
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.
commercial-skills alirezarezvani/claude-skills · score 75/100 (grade C)
Use when reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on "review this deal", "should we discount", "pricing model", "partner economics", "RFP response", "bookings forecast", "channel mix". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth (sales execution) and c-level-advisor/cro-advisor (strategic CRO judgment).
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.
design-md sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Analyze Stitch projects and synthesize a semantic design system into DESIGN.md files
design-philosophy sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Visual philosophy and art-direction for frontend. Use when creating high-concept work, campaigns, or when the user asks for a visual philosophy, manifesto, or unmistakable art-like aesthetic.
dynamic-workflow-mode affaan-m/ECC · score 75/100 (grade C)
Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses. Use when building a task-local harness, adding eval gates, or extracting a reusable skill from ad-hoc work.
dynamic-workflow-mode affaan-m/everything-claude-code · score 75/100 (grade C)
Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses. Use when building a task-local harness, adding eval gates, or extracting a reusable skill from ad-hoc work.
efcore-d2-db-diagram github/awesome-copilot · score 75/100 (grade C)
Generate D2 database diagrams from Entity Framework Core models. USE FOR: EF Core database diagram, Entity Framework Core ERD, DbContext diagram, C# entity relationship diagram, PostgreSQL schema visualization, generate .d2 file from EF Core entities, Fluent API mapping diagram, migrations-based database diagram, table relationships, owned types, many-to-many join tables, indexes and constraints. DO NOT USE FOR: runtime debugging, database migration execution, schema deployment, SQL performance tuning, or draw.io diagrams.
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`.
frontend-dev MiniMax-AI/skills · score 75/100 (grade C)
Full-stack frontend development combining premium UI design, cinematic animations, AI-generated media assets, persuasive copywriting, and visual art. Builds complete, visually striking web pages with real media, advanced motion, and compelling copy. Use when: building landing pages, marketing sites, product pages, dashboards, generating media assets (image/video/audio/music), writing conversion copy, creating generative art, or implementing cinematic scroll animations.
frontend-ui-dark-ts sickn33/antigravity-awesome-skills · score 75/100 (grade C)
A modern dark-themed React UI system using Tailwind CSS and Framer Motion. Designed for dashboards, admin panels, and data-rich applications with glassmorphism effects and tasteful animations.
google-cloud-waf-security google/skills · score 75/100 (grade C)
Generates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate workloads, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.
k8s-manifest-generator sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims.
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.
makepad-basics sickn33/antigravity-awesome-skills · score 75/100 (grade C)
CRITICAL: Use for Makepad getting started and app structure. Triggers on: makepad, makepad getting started, makepad tutorial, live_design!, app_main!, makepad project setup, makepad hello world, "how to create makepad app", makepad 入门, 创建 makepad 应用, makepad 教程, makepad 项目结构
makepad-dsl sickn33/antigravity-awesome-skills · score 75/100 (grade C)
CRITICAL: Use for Makepad DSL syntax and inheritance. Triggers on: makepad dsl, live_design, makepad inheritance, makepad prototype, "<Widget>", "Foo = { }", makepad object, makepad property, makepad DSL 语法, makepad 继承, makepad 原型, 如何定义 makepad 组件
mcp-builder ComposioHQ/awesome-claude-skills · score 75/100 (grade C)
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
not-a-vibe-coder sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Turns vague prompts into 8 structured planning files for brand new projects. DO NOT use on existing codebases.
openrouter davidondrej/skills · score 75/100 (grade C)
Design, build, debug, and optimize OpenRouter API integrations. Use for any OpenRouter API work, including models, reasoning, routing, media, tools, structured output, cost, or performance.
pdf openai/skills · score 75/100 (grade C)
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
phylogenetics K-Dense-AI/claude-scientific-skills · score 75/100 (grade C)
Builds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein families, and cautiously interpreted dated phylogenies.
postgres-best-practices sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.
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.
referral-program alirezarezvani/claude-skills · score 75/100 (grade C)
When the user wants to design, launch, or optimize a referral or affiliate program. Use when they mention 'referral program,' 'affiliate program,' 'word of mouth,' 'refer a friend,' 'incentive program,' 'customer referrals,' 'brand ambassador,' 'partner program,' 'referral link,' or 'growth through referrals.' Covers program mechanics, incentive design, and optimization — not just the idea of referrals but the actual system.
saas-pricing-strategist sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Design, optimize, and test pricing strategies for SaaS products using
santa-method affaan-m/ECC · score 75/100 (grade C)
Multi-agent adversarial verification: two independent reviewers with the same rubric must both pass before output ships, with a fix-and-re-review convergence loop and human escalation cap. Use when gating publishing, production deploys, compliance or brand-sensitive content, or hallucination-prone claims before they ship.
santa-method affaan-m/everything-claude-code · score 75/100 (grade C)
Multi-agent adversarial verification: two independent reviewers with the same rubric must both pass before output ships, with a fix-and-re-review convergence loop and human escalation cap. Use when gating publishing, production deploys, compliance or brand-sensitive content, or hallucination-prone claims before they ship.
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.
snowflake-development sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks, Snowpipe), Cortex AI functions, Cortex Agents, Snowpark Python, dbt integration, performance tuning, and security hardening.
spline-3d-integration sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Use when adding interactive 3D scenes from Spline.design to web projects, including React embedding and runtime control API.
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.
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.
videodb sickn33/antigravity-awesome-skills · score 75/100 (grade C)
Video and audio perception, indexing, and editing. Ingest files/URLs/live streams, build visual/spoken indexes, search with timestamps, edit timelines, add overlays/subtitles, generate media, and create real-time alerts.
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.
wordpress sickn33/antigravity-awesome-skills · score 75/100 (grade C)
WordPress development workflow covering theme development, plugin creation, WooCommerce integration, performance optimization, and security hardening. Includes WordPress 7.0 features: Real-Time Collaboration, AI Connectors, Abilities API, DataViews, and PHP-only blocks.
a11y-audit alirezarezvani/claude-skills · score 74/100 (grade C)
Accessibility audit skill for scanning, fixing, and verifying WCAG 2.2 Level A and AA compliance across React, Next.js, Vue, Angular, Svelte, and plain HTML codebases. Use when auditing accessibility, fixing a11y violations, checking color contrast, generating compliance reports, or integrating accessibility checks into CI/CD pipelines.
agentflow sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and recoverable pipeline design.
analytics-tracking sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.
android-jetpack-compose-expert sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Expert guidance for building modern Android UIs with Jetpack Compose, covering state management, navigation, performance, and Material Design 3.
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?').
azure-cloud-architect alirezarezvani/claude-skills · score 74/100 (grade C)
Design Azure architectures for startups and enterprises. Use when asked to design Azure infrastructure, create Bicep/ARM templates, optimize Azure costs, set up Azure DevOps pipelines, or migrate to Azure. Covers AKS, App Service, Azure Functions, Cosmos DB, and cost optimization.
bio-read-qc-fastp-workflow GPTomics/bioSkills · score 74/100 (grade C)
Runs all-in-one FASTQ preprocessing with fastp in a single pass - adapter trimming via paired-end overlap analysis, quality/length filtering, 2-color poly-G removal, base correction, optional dedup/UMI/merge, and HTML/JSON reports. Use when preprocessing bulk Illumina data and wanting one fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps. For precise small-RNA/amplicon adapters use adapter-trimming; for molecule-accurate UMI dedup use umi-processing.
chatgpt-apps openai/skills · score 74/100 (grade C)
Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.
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.
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.
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.
coo-advisor alirezarezvani/claude-skills · score 74/100 (grade C)
Operations leadership for scaling companies. Process design, OKR execution, operational cadence, and scaling playbooks. Use when designing operations, setting up OKRs, building processes, scaling teams, analyzing bottlenecks, planning operational cadence, or when user mentions COO, operations, process improvement, OKRs, scaling, operational efficiency, or execution.
cosmosdb-datamodeling github/awesome-copilot · score 74/100 (grade C)
Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
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.
database-designer alirezarezvani/claude-skills · score 74/100 (grade C)
Use when the user asks to design database schemas, plan data migrations, optimize queries, choose between SQL and NoSQL, or model data relationships.
design-consultation garrytan/gstack · score 74/100 (grade C)
Design consultation: understands your product, researches the landscape, proposes a complete design system (aesthetic, typography, color, layout, spacing, motion), and generates font+color preview... (gstack)
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)
design-spatial sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design — spatial composition
design-theme-guide sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design-token register: colour, typography, spacing and radius tokens with light and dark values, contrast ratio and WCAG level. Use for design system documentation.
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.
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.
figma-code-connect-components openai/skills · score 74/100 (grade C)
Connects Figma design components to code components using Code Connect mapping tools. Use when user says "code connect", "connect this component to code", "map this component", "link component to code", "create code connect mapping", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.
free-tool-strategy sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are an expert in engineering-as-marketing strategy. Your goal is to help plan and evaluate free tools that generate leads, attract organic traffic, and build brand awareness.
gdpr-data-handling sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Practical implementation guide for GDPR-oriented data-processing design, consent management, and privacy controls.
github-actions-advanced sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design, debug, and harden GitHub Actions CI/CD workflows, including reusable workflows, matrix builds, self-hosted runners, OIDC authentication, caching, environments, secrets, and release automation.
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.
grpc-golang sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Build production-ready gRPC services in Go with mTLS, streaming, and observability. Use when designing Protobuf contracts with Buf or implementing secure service-to-service transport.
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.
hig-inputs sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design Apple-platform input interactions for touch, keyboard, pointer, Pencil, controllers, spatial gestures and supported device sensors, with accessible alternatives.
impeccable pbakaus/impeccable · score 74/100 (grade C)
Use when the user wants to design, redesign, shape, critique, audit, polish, simplify, harden, animate, or otherwise improve a frontend interface: websites, landing pages, dashboards, product UI, components, forms, settings, onboarding, empty states, and native iOS or Android screens. Handles UX review, hierarchy, layout, typography, color, motion, UX copy, accessibility, responsive behavior, edge cases, and capturing or documenting design systems (DESIGN.md, tokens). Also for making bland UI bolder, loud UI quieter, or ambitious visual effects. Not for backend-only or non-UI tasks.
iso13485-audit-prep alirezarezvani/claude-skills · score 74/100 (grade C)
/compliance-os:iso13485-audit-prep [scope] — ISO 13485 QMS audit 6-question forcing interrogation. Design controls + CAPA + post-market focused. Use before Clause 8.2.4 internal audit, MDR / FDA QSR alignment review, or product-launch DHF closure audit.
loop-library alirezarezvani/claude-skills · score 74/100 (grade C)
Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring agent workflow or automation cadence, turn an outcome into a bounded copy-ready loop, or review an existing loop for weak checks, unsafe authority, unbounded repetition, stale state, or unclear stopping behavior.
mcp-server-builder alirezarezvani/claude-skills · score 74/100 (grade C)
Design and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and TypeScript support, schema validation, safe evolution. Use when exposing an existing API as an MCP server, building tool integrations for Claude or Codex or Cursor, or scaffolding an MCP project from scratch.
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.
mobile-design sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design and review iOS, Android, React Native or Flutter interfaces for touch, accessibility, navigation, offline behavior and measured performance. Use for mobile app UI work; not a mobile compliance certification.
mybatis-patterns affaan-m/ECC · score 74/100 (grade C)
MyBatis and MyBatis-Spring patterns for mapper design, XML and annotation SQL, result mapping, dynamic SQL safety, transactions, batching, pagination, and query performance. Use when building or reviewing Java persistence code with MyBatis, Spring Boot, MyBatis-Spring, or MyBatis-based legacy applications.
mybatis-patterns affaan-m/everything-claude-code · score 74/100 (grade C)
MyBatis and MyBatis-Spring patterns for mapper design, XML and annotation SQL, result mapping, dynamic SQL safety, transactions, batching, pagination, and query performance. Use when building or reviewing Java persistence code with MyBatis, Spring Boot, MyBatis-Spring, or MyBatis-based legacy applications.
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.
pi-agent K-Dense-AI/claude-scientific-skills · score 74/100 (grade C)
Builds with and operates Pi, the minimal terminal coding harness. Use for installing Pi, configuring providers/models/settings/environment variables, creating Pi skills/extensions/packages/themes/prompt templates, embedding Pi through the SDK, integrating over RPC or JSON event streams, parsing sessions, running local models through the llama.cpp router, developing custom Pi providers and TUI components, or using ecosystem packages such as pi-subagents (delegation/orchestration), pi-mcp-adapter (MCP servers), pi-interview (interactive forms), and pi-web-access (web search, fetching, video understanding).
plan-design-review garrytan/gstack · score 74/100 (grade C)
Designer's eye plan review — interactive, like CEO and Eng review. (gstack)
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).
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.
referral-program sickn33/antigravity-awesome-skills · score 74/100 (grade C)
You are an expert in viral growth and referral marketing using only referral data and tools actually available and authorized. Your goal is to help design and optimize programs that turn customers into growth engines.
results-analysis Galaxy-Dawn/claude-scholar · score 74/100 (grade C)
This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.
rfp-responder alirezarezvani/claude-skills · score 74/100 (grade C)
Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.
scarcity-urgency-psychologist sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design honest scarcity and urgency messaging when verified inventory, capacity, or deadlines justify a timely decision.
schema-markup sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.
scientific-brainstorming K-Dense-AI/claude-scientific-skills · score 74/100 (grade C)
Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.
sdk-dx sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Design SDKs that developers love to use—APIs that feel native, error messages that guide, and experiences that reduce friction. This skill covers creating SDKs that drive adoption through exceptional developer experience rather than aggressive marketing.
seek-and-analyze-video sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Seek and analyze video content using Memories.ai Large Visual Memory Model for persistent video intelligence
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.
ui-lint sickn33/antigravity-awesome-skills · score 74/100 (grade C)
Quick automated lint — detects common design system violations in seconds
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.
vpe-advisor alirezarezvani/claude-skills · score 74/100 (grade C)
VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and production discipline (on-call, deployment cadence, postmortem culture). Use when sprint velocity is dropping, eng hiring is broken, team structure is unclear, or deciding when to add a tech-lead manager. NOT a CTO skill (which owns architecture) — VPE owns delivery operations and how the team ships.
agent-tool-builder sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Tools are how AI agents interact with the world. A well-designed
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.
api-and-interface-design addyosmani/agent-skills · score 73/100 (grade C)
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
autoplan garrytan/gstack · score 73/100 (grade C)
Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. (gstack)
backend-architect sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert backend architect specializing in scalable API design, microservices architecture, and distributed systems.
bio-codon-usage GPTomics/bioSkills · score 73/100 (grade C)
Analyze codon usage and calculate CAI (Codon Adaptation Index), RSCU, and Nc with Biopython, and produce naive max-CAI codon-optimized sequences. Use when scoring a gene's codon bias against a host, optimizing a CDS for heterologous expression, or studying synonymous codon selection.
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.
cdk-patterns sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Common AWS CDK patterns and constructs for building cloud infrastructure with TypeScript, Python, or Java. Use when designing reusable CDK stacks and L3 constructs.
churn-prevention alirezarezvani/claude-skills · score 73/100 (grade C)
Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing a cancel flow, building save offers, setting up dunning emails, or reducing failed-payment churn. Trigger keywords: cancel flow, churn reduction, save offers, dunning, exit survey, payment recovery, win-back, involuntary churn, failed payments, cancel page. NOT for customer health scoring or expansion revenue — use customer-success-manager for that.
cirq K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
commercial-policy alirezarezvani/claude-skills · score 73/100 (grade C)
Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under. Covers discount matrix design (ARR band x term length x payment terms x strategic value), commercial policy design, exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces). For Head of Commercial, Head of Deal Desk, VP Sales, or RevOps at the policy-design moment — NOT per-deal application (that is deal-desk) and NOT pricing model selection (that is pricing-strategist).
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.
database sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.
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.
design-shotgun garrytan/gstack · score 73/100 (grade C)
Design shotgun: generate multiple AI design variants, open a comparison board, collect structured feedback, and iterate. (gstack)
documentation-and-adrs addyosmani/agent-skills · score 73/100 (grade C)
Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
event-sourcing-architect sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use PROACTIVELY for event-sourced systems, audit trail requirements, or complex domain modeling with temporal queries.
event-store-design sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
excalidraw-diagram-generator github/awesome-copilot · score 73/100 (grade C)
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
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.
free-tool-strategy alirezarezvani/claude-skills · score 73/100 (grade C)
When the user wants to build a free tool for marketing — lead generation, SEO value, or brand awareness. Use when they mention 'engineering as marketing,' 'free tool,' 'calculator,' 'generator,' 'checker,' 'grader,' 'marketing tool,' 'lead gen tool,' 'build something for traffic,' 'interactive tool,' or 'free resource.' Covers idea evaluation, tool design, and launch strategy. For pure SEO content strategy (no tool), use seo-audit or content-strategy instead.
game-audio sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Game audio principles. Sound design, music integration, adaptive audio systems.
game-design sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Game design principles. GDD structure, balancing, player psychology, progression.
game-development sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Game development orchestrator. Routes by platform, dimension, and engine fit (web 2D/3D, hybrid DOM+canvas, narrative tools). Use when starting or structuring a game project, choosing frameworks, or picking among Phaser, PixiJS, Kaplay, Canvas/WebGL, Three.js, Babylon.js, Godot, Unity, or Ink/Twine.
gan-style-harness affaan-m/ECC · score 73/100 (grade C)
GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper. Use when a feature should be built autonomously through generator and evaluator iteration until it clears a quality bar.
gan-style-harness affaan-m/everything-claude-code · score 73/100 (grade C)
GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper. Use when a feature should be built autonomously through generator and evaluator iteration until it clears a quality bar.
google-cloud-waf-cost-optimization google/skills · score 73/100 (grade C)
Evaluates Google Cloud workloads for cost efficiency and FinOps alignment using the Google Cloud Well-Architected Framework Cost Optimization pillar. Use when the user asks to analyze Google Cloud spend, reduce cloud bills, rightsize resources (for example, Compute, GKE, Storage, Databases), evaluate discount options (for example, CUDs, SUDs, Spot VMs), or eliminate idle capacity. Do not use for standalone product pricing lookups or non-cost architecture design.
google-cloud-waf-operational-excellence google/skills · score 73/100 (grade C)
Generates operational guidance for CI/CD deployment pipelines, observability, monitoring, logging, and incident management on Google Cloud based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks about operations-related topics like capacity management, change management, incident and problem management, configuration management, deployment automation using infrastructure as code (IaC), or operational health checks for Google Cloud workloads.
google-cloud-waf-reliability google/skills · score 73/100 (grade C)
Evaluates, designs, and improves the reliability, resilience, availability, fault tolerance, and disaster recovery (DR) of Google Cloud workloads based on the design principles and recommendations in the Reliability pillar of the Google Cloud Well-Architected Framework. Use when the user asks about reliability-related topics like workload uptime, designing for high availability (HA) or DR, setting and meeting RTO/RPO targets, SRE best practices, backup strategies, multi-region failover, or fault-tolerant architecture on Google Cloud. Don't use for other Well-Architected Framework pillars such as Cost Optimization, Operational Excellence, or Security, or for hands-on resource deployment and live incident troubleshooting.
graphql-architect sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Master modern GraphQL with federation, performance optimization, and enterprise security. Build scalable schemas, implement advanced caching, and design real-time systems.
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".
gtm-operating-cadence github/awesome-copilot · score 73/100 (grade C)
Design meeting rhythms, metric reporting, quarterly planning, and decision-making velocity for scaling companies. Use when decisions are slow, planning is broken, the company is growing but alignment is worse, or leadership meetings consume all time without producing decisions.
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.
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.
lab-hardware-cad K-Dense-AI/claude-scientific-skills · score 73/100 (grade C)
Designs custom laboratory hardware as parametric build123d models and exports fabrication artifacts as STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.
macos-golden-gate-design github/awesome-copilot · score 73/100 (grade C)
Design, implement, review, or refactor native macOS 27 Golden Gate interfaces in SwiftUI or AppKit. Use when a Mac app must match Apple''s current macOS 27 UI kit and restrained Liquid Glass language: integrated windows, full-height sidebars, native toolbars, flat lists, tables, and forms, clear pane boundaries, accessible materials, and removal of unnecessary nested cards, framed panels, or glassmorphism. Also use for Figma macOS 27 design-to-code work and audits of interfaces that feel too boxed.
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.
observability-designer alirezarezvani/claude-skills · score 73/100 (grade C)
Design production-ready observability strategies combining metrics, logs, and traces. Includes SLI/SLO design, golden-signals monitoring, alert optimization. Use when adding observability to a new service, refactoring alerting that is too noisy, or designing an SLO program before scaling production load.
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.
prisma-expert sickn33/antigravity-awesome-skills · score 73/100 (grade C)
You are an expert in Prisma ORM with deep knowledge of schema design, migrations, query optimization, relations modeling, and database operations across PostgreSQL, MySQL, and SQLite.
redesign-existing-projects sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Use when upgrading existing websites or apps by auditing generic UI patterns and applying premium design fixes without rewrites.
resx-source-generator-migration github/awesome-copilot · score 73/100 (grade C)
Migrates a project that uses checked-in .designer.cs files behind .resx to using a source-generator instead
robius-state-management sickn33/antigravity-awesome-skills · score 73/100 (grade C)
CRITICAL: Use for Robius state management patterns. Triggers on: AppState, persistence, theme switch, 状态管理, Scope::with_data, save state, load state, serde, 状态持久化, 主题切换
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").
threejs-postprocessing sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Three.js post-processing - EffectComposer, bloom, DOF, screen effects. Use when adding visual effects, color grading, blur, glow, or creating custom screen-space shaders.
threejs-shaders sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Three.js shaders - GLSL, ShaderMaterial, uniforms, custom effects. Use when creating custom visual effects, modifying vertices, writing fragment shaders, or extending built-in materials.
update-implementation-plan github/awesome-copilot · score 73/100 (grade C)
Update an existing implementation plan file with new or update requirements to provide new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
web-project-brainstorming sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Masterclass framework for brainstorming web development projects and page designs. Outlines structural phases for concept, UX flow, styling aesthetics, technical architecture, and SEO.
wiki-vitepress sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Transform generated wiki Markdown files into a polished VitePress static site with dark theme and interactive Mermaid diagrams. Use when user asks to \"build a site\" or \"package as VitePress\", user runs the /deep-wiki, or user wants a browsable HTML output from generated wiki pages.
winui-app openai/skills · score 73/100 (grade C)
Bootstrap, develop, and design modern WinUI 3 desktop applications with C# and the Windows App SDK using official Microsoft guidance, WinUI Gallery patterns, Windows App SDK samples, and CommunityToolkit components. Use when creating a brand new app, preparing a machine for WinUI, reviewing, refactoring, planning, troubleshooting, environment-checking, or setting up WinUI 3 XAML, controls, navigation, windowing, theming, accessibility, responsiveness, performance, deployment, or related Windows app design and development work.
yann-lecun sickn33/antigravity-awesome-skills · score 73/100 (grade C)
Persona fictícia inspirada em temas públicos associados a Yann LeCun, para diálogo criativo sobre redes neurais e aprendizagem preditiva.
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.
adobe-illustrator-scripting github/awesome-copilot · score 72/100 (grade C)
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
ai-agents-architect sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Expert in designing and building autonomous AI agents. Masters tool
aws-vpc sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Design and implement VPCs and networking. Configure subnets, route tables,
baoyu-markdown-to-html JimLiu/baoyu-skills · score 72/100 (grade C)
Converts Markdown to styled HTML with WeChat-compatible themes. Supports code highlighting, math, Mermaid (rendered to PNG via headless Chrome), PlantUML, footnotes, alerts, infographics, and optional bottom citations for external links. Use when user asks for "markdown to html", "convert md to html", "md 转 html", "微信外链转底部引用", or needs styled HTML output from markdown.
batch-script-progress github/awesome-copilot · score 72/100 (grade C)
Design and verify runtime output when creating or modifying Python, PowerShell, or Node.js scripts that process multiple files, records, or API requests. Use for batch scripts, bulk operations, silent long-running loops, progress reporting, per-item failures, final counts, stdout separation, or exit-status consistency. Not for UI progress bars, monitoring infrastructure, or progress updates in the AI conversation.
bio-batch-downloads GPTomics/bioSkills · score 72/100 (grade C)
Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.
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-protac-degraders GPTomics/bioSkills · score 72/100 (grade C)
Designs PROTACs, molecular glues, and bivalent degraders with explicit handling of E3 ligase choice (VHL, CRBN, IAP, MDM2, KEAP1), linker design (length, composition, rigidity), ternary complex prediction (PRosettaC, DeepTernary, AlphaFold3), cooperativity (alpha), DC50 / Dmax characterization, hook effect, and prediction-experiment reconciliation. Use when designing targeted protein degraders, planning linker SAR, predicting ternary complex stability, or building generative degrader workflows.
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-reporting-figure-export GPTomics/bioSkills · score 72/100 (grade C)
Exports publication-ready figures with the correct vector/raster split, embedded editable fonts, color-space-robust palettes, and journal-correct sizing and resolution in matplotlib and ggplot2. Use when preparing figures for journal submission, exporting a dense single-cell or GWAS plot without producing an unopenable vector file, or fixing fonts and colors that break in print.
brandfetch-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
Automate Brandfetch tasks via Rube MCP (Composio). Always search tools first for current schemas.
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.
canvas-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
Automate Canvas tasks via Rube MCP (Composio). Always search tools first for current schemas.
cro-advisor alirezarezvani/claude-skills · score 72/100 (grade C)
Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity.
design-html garrytan/gstack · score 72/100 (grade C)
Design finalization: generates production-quality Pretext-native HTML/CSS. (gstack)
design-system alirezarezvani/claude-skills · score 72/100 (grade C)
Captures the user's brand identity once via a 10-question onboarding wizard (primary/accent HEX + heading + body Google Fonts + design style editorial/technical/minimal/playful + default output directory + syntax theme + TOC behavior + optional logo/company), validates body-text and link contrast against WCAG 2.2 AA, derives 12 CSS custom properties in HSL space, and stores the result for every markdown-html converter to consume. Use before any markdown-html conversion. Triggers on first-run onboarding ("set up the brand", "configure markdown-html", "run onboarding"), on explicit reset ("reset the design system", "re-onboard"), and is checked by every converter via config_loader.py before rendering. Refuses to save if body-text contrast fails AA 4.5:1 or the output dir isn't writable. Precedence is project (./.markdown-html/), then global (~/.config/markdown-html/), then built-in defaults; MARKDOWN_HTML_NO_CONFIG=1 bypasses.
domain-driven-design sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Plan and route Domain-Driven Design work from strategic modeling to tactical implementation and evented architecture patterns.
email-systems sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Design transactional and marketing email delivery, queues, templates, authentication, suppression and monitoring.
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.
free-design-resources sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Design resource register: resource and provider, licence type, commercial-use and attribution rules, export format, lock-in risk, free tier limit and accessibility notes. Use for tool vetting.
frontend-slides affaan-m/ECC · score 72/100 (grade C)
Create stunning, animation-rich HTML presentations from scratch or by converting PowerPoint files. Use when the user wants to build a presentation, convert a PPT/PPTX to web, or create slides for a talk/pitch. Helps non-designers discover their aesthetic through visual exploration rather than abstract choices.
frontend-slides affaan-m/everything-claude-code · score 72/100 (grade C)
Create stunning, animation-rich HTML presentations from scratch or by converting PowerPoint files. Use when the user wants to build a presentation, convert a PPT/PPTX to web, or create slides for a talk/pitch. Helps non-designers discover their aesthetic through visual exploration rather than abstract choices.
geo-brand-mentions sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Brand mention and authority scanner for AI visibility.
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).
gstack-openclaw-office-hours garrytan/gstack · score 72/100 (grade C)
Use when asked to brainstorm, evaluate whether an idea is worth building, run office hours, or think through a new product idea or design direction before any code is written.
gtm-developer-ecosystem github/awesome-copilot · score 72/100 (grade C)
Build and scale developer-led adoption through ecosystem programs. Use when deciding open vs curated ecosystems, building developer programs, scaling platform adoption, or designing student program pipelines.
gtm-technical-product-pricing github/awesome-copilot · score 72/100 (grade C)
Pricing strategy for technical products. Use when choosing usage-based vs seat-based, designing freemium thresholds, structuring enterprise pricing conversations, deciding when to raise prices, or using price as a positioning signal.
haskell-pro sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Design and review Haskell types, pure domain logic, parsing, exception-safe concurrency, Cabal/Stack builds and measured performance.
hig-platforms sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Apple Human Interface Guidelines for platform-specific design.
iconsax-library sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Extensive icon library and AI-driven icon generation skill for premium UI/UX design.
imaging-data-commons K-Dense-AI/claude-scientific-skills · score 72/100 (grade C)
Queries and downloads public cancer imaging data from NCI Imaging Data Commons. Supports IDC collection discovery, DICOM access, radiology (CT, MR, PET) and pathology AI datasets, metadata SQL, visualization, licensing, and citations. Uses public metadata and download routes without authentication; optional BigQuery and Google Healthcare routes require Google credentials.
iqair-airvisual-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
Automate Iqair Airvisual tasks via Rube MCP (Composio). Always search tools first for current schemas.
jira-expert alirezarezvani/claude-skills · score 72/100 (grade C)
Atlassian Jira expert for creating and managing projects, planning, product discovery, JQL queries, workflows, custom fields, automation, reporting, and all Jira features. Use when setting up or configuring Jira projects, writing JQL and advanced searches, creating dashboards, designing workflows, or performing technical Jira operations.
kpi-dashboard-design sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions.
logo-dev-automation ComposioHQ/awesome-claude-skills · score 72/100 (grade C)
Automate Logo Dev tasks via Rube MCP (Composio). Always search tools first for current schemas.
loop-design-check affaan-m/ECC · score 72/100 (grade C)
Design a goal-oriented agent loop or review one for failure modes: spinning, Goodhart-gaming the verifier, or running a wrong answer to completion. Covers machine-decidable goals, loop types, plan/build/judge skeletons, and runaway prevention; mechanism wiring lives in autonomous-loops. Use when designing, writing, or checking an agent loop. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。
loop-design-check affaan-m/everything-claude-code · score 72/100 (grade C)
Design a goal-oriented agent loop or review one for failure modes: spinning, Goodhart-gaming the verifier, or running a wrong answer to completion. Covers machine-decidable goals, loop types, plan/build/judge skeletons, and runaway prevention; mechanism wiring lives in autonomous-loops. Use when designing, writing, or checking an agent loop. 中文触发：写 loop、设计 loop、做一个 loop、检查 loop 对不对、loop 体检、loop 会不会跑飞、可判定目标、五个崩法、plan build judge。
magic-animator sickn33/antigravity-awesome-skills · score 72/100 (grade C)
AI-powered animation tool for creating motion in logos, UI, icons, and social media assets.
new-grok-bot davidondrej/skills · score 72/100 (grade C)
Design a Grok Bot role and create its setup prompt. Use only when the user explicitly invokes /new-grok-bot.
onboarding-psychologist sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Design first-use and onboarding experiences that bring an early win, cut setup friction, build ownership and form habits through stable cues. Use when onboarding loses users early, time-to-value is long, or the first session should build confidence, momentum and a lasting habit.
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.
owasp-audit briiirussell/cybersecurity-skills · score 72/100 (grade C)
Audit application source code against the OWASP Top 10 (2021) vulnerability categories — broken access control, cryptographic failures, injection, insecure design, security misconfiguration, vulnerable components, authentication failures, data integrity, logging failures, SSRF. Use when the user mentions 'OWASP,' 'OWASP Top 10,' 'security audit,' 'security review,' 'secure code review,' 'code security review,' 'vulnerability audit,' 'find vulnerabilities,' 'appsec review,' 'application security audit,' 'check for security issues,' 'broken access control,' 'IDOR,' 'SQL injection,' 'XSS,' 'SSRF,' or wants to check their codebase for common security weaknesses.
post-acceptance Galaxy-Dawn/claude-scholar · score 72/100 (grade C)
This skill should be used when the user asks to "prepare conference presentation", "create presentation slides", "design poster", "make academic poster", "write promotion content", "create Twitter thread", or mentions post-acceptance conference preparation. Provides comprehensive workflow for presentation, poster, and promotion content creation.
power-bi-model-design-review github/awesome-copilot · score 72/100 (grade C)
Comprehensive Power BI data model design review prompt for evaluating model architecture, relationships, and optimization opportunities.
redis-patterns affaan-m/ECC · score 72/100 (grade C)
Redis data structure patterns, caching strategies, distributed locks, rate limiting, pub/sub, and connection management for production applications. Use when adding caching, a distributed lock, rate limiting, or pub/sub with Redis, or when key design needs review.
redis-patterns affaan-m/everything-claude-code · score 72/100 (grade C)
Redis data structure patterns, caching strategies, distributed locks, rate limiting, pub/sub, and connection management for production applications. Use when adding caching, a distributed lock, rate limiting, or pub/sub with Redis, or when key design needs review.
saas-multi-tenant sickn33/antigravity-awesome-skills · score 72/100 (grade C)
Design and implement multi-tenant SaaS architectures with row-level security, tenant-scoped queries, shared-schema isolation, and safe cross-tenant admin patterns in PostgreSQL and TypeScript.
security-threat-model openai/skills · score 72/100 (grade C)
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design work.
vizcom sickn33/antigravity-awesome-skills · score 72/100 (grade C)
AI-powered product design tool for transforming sketches into full-fidelity 3D renders.
wordpress-theme-development sickn33/antigravity-awesome-skills · score 72/100 (grade C)
WordPress theme development workflow covering theme architecture, template hierarchy, custom post types, block editor support, responsive design, and WordPress 7.0 features: DataViews, Pattern Editing, Navigation Overlays, and admin refresh.
adaptyv K-Dense-AI/claude-scientific-skills · score 71/100 (grade C)
Uses the Adaptyv Bio Foundry API and Python SDK to design protein characterization experiments, estimate costs, submit sequences, monitor laboratory progress, and retrieve results. Applies to Adaptyv Foundry, its target catalog, binding screening and affinity assays, thermostability, expression, fluorescence, epitope binning, and enzyme activity workflows, including code using adaptyv or FoundryClient.
agent-workflow-designer alirezarezvani/claude-skills · score 71/100 (grade C)
Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.
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.
azure-architecture-autopilot github/awesome-copilot · score 71/100 (grade C)
Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
bb-plugins davidondrej/skills · score 71/100 (grade C)
Build, install, and debug bb plugins. Use when the user wants a bb plugin, a sidebar panel, a bb CLI subcommand, an agent tool, a theme, a provider, or to extend bb itself. For running threads and the core bb CLI, use bb-cli instead.
bio-data-visualization-circos-plots GPTomics/bioSkills · score 71/100 (grade C)
Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.
bio-generative-design GPTomics/bioSkills · score 71/100 (grade C)
Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.
bio-read-qc-quality-filtering GPTomics/bioSkills · score 71/100 (grade C)
Filters reads by quality, length, N content, and complexity with Trimmomatic, fastp, and Cutadapt, including sliding-window trimming, per-read unqualified-base filtering, and 2-color poly-G removal. Use when reads have poor-quality tails, when an assembly or k-mer workflow needs clean input, or when a junk read subpopulation must be dropped. For adapter removal use adapter-trimming; for all-in-one preprocessing use fastp-workflow.
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.
bio-workflows-splicing-pipeline GPTomics/bioSkills · score 71/100 (grade C)
Orchestrates the end-to-end bulk short-read alternative-splicing pipeline from FASTQ to differential splicing, chaining fastp QC, cohort-consistent STAR 2-pass alignment (one shared junction DB), junction QC, event-level differential splicing (rMATS-turbo + leafcutter, optional MAJIQ V3), parallel isoform-level DTU (Salmon -> tximport dtuScaledTPM -> DRIMSeq/DEXSeq -> stageR), and sashimi visualization. Use when committing the annotation GTF and a shared 2-pass junction database for the whole cohort, keeping the analysis at splice-aware resolution (never collapsing to gene), choosing event-level vs isoform-level DTU and reconciling them, applying the stageR two-stage gene->transcript FDR, or off-ramping to splice-variant / outlier / long-read / single-cell splicing. Hands mechanism to the alternative-splicing component skills; not a re-teach of any single step.
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).
category-designer Affitor/affiliate-skills · score 71/100 (grade C)
Define a new category where your product wins by default. Reframe the buying decision. Triggers on: "create a category", "category design", "define my category", "category of one", "reframe the market", "position as category king", "new category", "category creation", "own a category", "category strategy", "competitive positioning", "strategic positioning", "market reframing", "be the only option", "change the buying criteria", "category king".
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.
claude-d3js-skill sickn33/antigravity-awesome-skills · score 71/100 (grade C)
This skill provides guidance for creating sophisticated, interactive data visualisations using d3.js.
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.
doc-and-modernize github/awesome-copilot · score 71/100 (grade C)
Two related workflows for a locally-cloned codebase, in one skill. Documentation mode produces a single, comprehensive, verifiable architecture document primarily by reading files on disk (local-first) — use it whenever the user wants to understand, map, document, research, or onboard onto a codebase ("research this repo", "write up the architecture", "do an architecture deep dive", "document how this codebase works", "map the system design", "create an onboarding doc"). Modernization mode generates a phased plan to modernize, migrate, upgrade, or rewrite a legacy system ("modernize this", "plan the migration", "how would we rewrite this", "how do we get off this legacy stack"); if no architecture document exists yet it first runs Documentation mode, then continues straight through to the plan. It assumes the legacy stack may be dead, runs a time-boxed feasibility spike, and picks the highest achievable rung on a safety ladder instead of demanding a fully-green legacy CI gate up front.
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.
hig-components-menus sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Design Apple-platform menus, buttons, toolbars and disclosure controls using the appropriate platform conventions, command hierarchy and accessible interactions.
hig-foundations sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Apple Human Interface Guidelines design foundations.
information-security-manager-iso27001 alirezarezvani/claude-skills · score 71/100 (grade C)
ISO 27001 ISMS implementation and cybersecurity governance for HealthTech and MedTech companies. Use when designing an ISMS, running security risk assessments, implementing controls, pursuing ISO 27001 certification, preparing security audits, responding to security incidents, or verifying compliance. Covers ISO 27001, ISO 27002, healthcare security, and medical device cybersecurity.
kubernetes-patterns affaan-m/ECC · score 71/100 (grade C)
Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.
kubernetes-patterns affaan-m/everything-claude-code · score 71/100 (grade C)
Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.
landing alirezarezvani/claude-skills · score 71/100 (grade C)
Generates a premium single-page HTML landing page with 3D CSS animations, GSAP scroll effects, and mouse-parallax depth. Forcing intake (product + elevator pitch, audience register, brand overrides, tone) locks down positioning before any copy or markup is written, so the page reflects the actual product rather than generic boilerplate. Use whenever the user says 'landing for X', 'create a landing page', 'build a landing page', 'make a landing page for X', 'I need a web page for Y', or provides product/service details and wants a polished website. Also triggers on 'promotional page', 'product page', 'one-pager', 'web presence', 'sales page'. Outputs a single self-contained HTML file (Claude Code) or HTML artifact (Claude.ai). Supports configurable brand colors via CSS custom property overrides.
lookdev-auto sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Automated visual tuning: a vision or video model rates rendered variants in a loop. Render several labeled variants into one artifact, ask the model to rate them and suggest better values, render the suggestions, ask it to pick the best, repeat until good — the model is the eye, you run the loop.
mysql-patterns affaan-m/ECC · score 71/100 (grade C)
MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends. Use when designing MySQL or MariaDB schemas and indexes, or when a query, transaction, or replica lags.
mysql-patterns affaan-m/everything-claude-code · score 71/100 (grade C)
MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends. Use when designing MySQL or MariaDB schemas and indexes, or when a query, transaction, or replica lags.
nosql-expert sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.
obsidian-cli sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Use the Obsidian CLI to read, create, search, and manage vault content, or to develop and debug Obsidian plugins and themes from the command line.
penpot-uiux-design github/awesome-copilot · score 71/100 (grade C)
Comprehensive guide for creating professional UI/UX designs in Penpot using MCP tools. Use this skill when: (1) Creating new UI/UX designs for web, mobile, or desktop applications, (2) Building design systems with components and tokens, (3) Designing dashboards, forms, navigation, or landing pages, (4) Applying accessibility standards and best practices, (5) Following platform guidelines (iOS, Android, Material Design), (6) Reviewing or improving existing Penpot designs for usability. Triggers: "design a UI", "create interface", "build layout", "design dashboard", "create form", "design landing page", "make it accessible", "design system", "component library".
product-design sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Design de produto nivel Apple — sistemas visuais, UX flows, acessibilidade, linguagem visual proprietaria, design tokens, prototipagem e handoff. Cobre Figma, design systems, tipografia, cor, espacamento, motion design e principios de design cognitivo.
product-inventor sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Product Inventor e Design Alchemist de nivel maximo — combina Product Thinking, Design Systems, UI Engineering, Psicologia Cognitiva, Storytelling e execucao impecavel nivel Jobs/Apple.
prototype emilkowalski/skills · score 71/100 (grade C)
Build multiple genuinely different versions of a UI piece you describe, rendered behind a visual picker so you can flip through them live and promote the one that feels right. Only runs when explicitly invoked; it does not trigger on its own.
quality-manager-qms-iso13485 alirezarezvani/claude-skills · score 71/100 (grade C)
ISO 13485 Quality Management System implementation and maintenance for medical device organizations. Provides QMS design, documentation control, internal auditing, CAPA management, and certification support. Use when working with medical device quality systems, preparing for ISO 13485 audits, managing regulatory compliance documentation, setting up corrective actions, or building audit preparation programs. Useful for quality management, audit preparation, regulatory compliance, medical device documentation, and corrective action workflows.
security-ownership-map openai/skills · score 71/100 (grade C)
Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.
senior-data-engineer alirezarezvani/claude-skills · score 71/100 (grade C)
Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.
simplify-codebase tt-a1i/archify · score 71/100 (grade C)
Simplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity. Use for evidence-backed deletion or consolidation of dead code, duplicate state, redundant APIs or layers, ownerless abstractions, obsolete compatibility or design records, and over-engineering in any language; also use for 代码简化 or 熵回收. Do not use for general code review, onboarding, style-only refactoring, or performance tuning.
steve-jobs sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Agente que simula Steve Jobs — cofundador da Apple, CEO da Pixar, fundador da NeXT, o maior designer de produtos tecnologicos da historia e o mais influente apresentador de produtos do mundo.
tailwind-patterns sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Tailwind CSS v4 principles. CSS-first configuration, container queries, modern patterns, design token architecture.
ui-ux-designer sickn33/antigravity-awesome-skills · score 71/100 (grade C)
Create interface designs, wireframes, and design systems. Masters user research, accessibility standards, and modern design tools.
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.
ai-product sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Design and evaluate LLM product features, retrieval, validated outputs, latency, and cost controls.
api-design affaan-m/ECC · score 70/100 (grade C)
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs. Use when designing or reviewing REST endpoints, resource names, status codes, pagination, or versioning.
api-design affaan-m/everything-claude-code · score 70/100 (grade C)
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs. Use when designing or reviewing REST endpoints, resource names, status codes, pagination, or versioning.
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.
api-design-reviewer alirezarezvani/claude-skills · score 70/100 (grade C)
Comprehensive REST API design review with automated linting, breaking-change detection, and design scorecards. Catches inconsistent conventions, missing versioning, and design smells before APIs ship. Use when reviewing a PR that adds or changes API endpoints, auditing an existing API for v2 migration, or establishing API standards for a team.
api-patterns sickn33/antigravity-awesome-skills · score 70/100 (grade C)
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
architecture-blueprint-generator github/awesome-copilot · score 70/100 (grade C)
Comprehensive project architecture blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks and architectural patterns, generates visual diagrams, documents implementation patterns, and provides extensible blueprints for maintaining architectural consistency and guiding new development.
architecture-design Galaxy-Dawn/claude-scholar · score 70/100 (grade C)
Use only when creating new registrable ML components that require Factory or Registry patterns.
baoyu-diagram JimLiu/baoyu-skills · score 70/100 (grade C)
Create professional, dark-themed SVG diagrams of any type — architecture diagrams, flowcharts, sequence diagrams, structural diagrams, mind maps, timelines, illustrative/conceptual diagrams, and more. Use this skill whenever the user asks for any kind of technical or conceptual diagram, visualization of a system, process flow, data flow, component relationship, network topology, decision tree, org chart, state machine, or any visual representation of structure/logic/process. Also trigger when the user says "画个图" "画一个架构图" "diagram" "flowchart" "sequence diagram" "draw me a ..." or uploads content and asks to visualize it. Output is always a standalone .svg file.
bio-alignment-multiple GPTomics/bioSkills · score 70/100 (grade C)
Perform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee. Guides tool and algorithm selection based on dataset size, sequence divergence, and downstream application. Use when aligning three or more homologous sequences for phylogenetics, conservation analysis, or evolutionary studies.
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-data-visualization-volcano-and-ma-plots GPTomics/bioSkills · score 70/100 (grade C)
Build volcano and MA plots from differential-expression / association results with LFC shrinkage, FDR-adjusted thresholds, sensible label placement, and axis-truncation conventions. Covers EnhancedVolcano, ggplot2, matplotlib, and the apeglm/ashr/normal shrinkage decision. Use when visualizing differential-expression results (RNA-seq, ChIP-seq, ATAC-seq, proteomics) or any per-feature effect-size + p-value table.
bio-hi-c-analysis-tad-detection GPTomics/bioSkills · score 70/100 (grade C)
Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track, valley-prominence boundary_strength, and Li/Otsu-thresholded is_boundary flags across a list of window sizes. Covers the multi-scale window sweep (sub-TAD to compartment-domain), why the boundary is reproducible but the domain partition is not, cross-condition comparison via differential SCORE not differential partition, and the insulation-vs-compartment orthogonality. Use when calling TADs or domain boundaries, computing insulation scores, choosing a window size, ranking boundary strength, comparing boundaries across conditions, or annotating CTCF-backed boundaries; route domain rendering to hic-visualization and boundary-feature overlap to genome-intervals.
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-retrosynthesis GPTomics/bioSkills · score 70/100 (grade C)
Performs retrosynthetic planning using AiZynthFinder (template-based MCTS), maintained or version-pinned template-free models, ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, configurable MCTS rewards, building-block availability, and forward-prediction checks. Use when assessing synthetic feasibility of generated or selected molecules, planning multi-step syntheses, building synthesis-aware design pipelines, or screening libraries for retro-route feasibility.
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.
brand-guidelines alirezarezvani/claude-skills · score 70/100 (grade C)
When the user wants to apply, document, or enforce brand guidelines for any product or company. Also use when the user mentions 'brand guidelines,' 'brand colors,' 'typography,' 'logo usage,' 'brand voice,' 'visual identity,' 'tone of voice,' 'brand standards,' 'style guide,' 'brand consistency,' or 'company design standards.' Covers color systems, typography, logo rules, imagery guidelines, and tone matrix for any brand — including Anthropic's official identity.
company-os alirezarezvani/claude-skills · score 70/100 (grade C)
The meta-framework for how a company runs — the connective tissue between all C-suite roles. Covers operating system selection (EOS, Scaling Up, OKR-native, hybrid), accountability charts, scorecards, meeting pulse, issue resolution, and 90-day rocks. Use when setting up company operations, selecting a management framework, designing meeting rhythms, building accountability systems, implementing OKRs, or when user mentions EOS, Scaling Up, operating system, L10 meetings, rocks, scorecard, accountability chart, or quarterly planning.
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.
convex sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Convex reactive backend expert: schema design, TypeScript functions, real-time subscriptions, auth, file storage, scheduling, and deployment.
cs-senior-engineer alirezarezvani/claude-skills · score 70/100 (grade C)
Senior Engineer agent for architecture decisions, code review, DevOps, and API design. Orchestrates engineering and engineering-team skills for technical implementation work. Spawn when users need system design, code quality review, CI/CD pipeline setup, or infrastructure decisions.
deep-research Imbad0202/academic-research-skills · score 70/100 (grade C)
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, WHY HOW WHAT papers, 3W literature scan, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 三段式文獻掃描, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題, 심층 연구, 문헌 조사, 체계적 문헌고찰, 메타분석, 사실 확인, 연구 방향을 잡아줘, 연구 주제 정하는 것을 도와줘, revisión de literatura, metaanálisis
design-orchestration sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order.
design-spells sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Curated micro-interactions and design details that add "magic" and personality to websites and apps.
design-taste-frontend sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Use when building high-agency frontend interfaces with strict design taste, calibrated color, responsive layout, and motion rules.
figma-generate-library openai/skills · score 70/100 (grade C)
Build or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.
free-tools coreyhaines31/marketingskills · score 70/100 (grade C)
When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," "free resource," "ROI calculator," "grader tool," "audit tool," "should I build a free tool," or "tools for lead gen." Use this whenever someone wants to build something useful and give it away to attract leads or earn links. For downloadable content lead magnets (ebooks, checklists, templates), see lead-magnets.
frontend-design anthropics/skills · score 70/100 (grade C)
Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
google-cloud-solution-agentic-ai-data-science-workflow google/skills · score 70/100 (grade C)
Designs a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code.
google-cloud-waf-performance-optimization google/skills · score 70/100 (grade C)
Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.
grill-me sickn33/antigravity-awesome-skills · score 70/100 (grade C)
A relentless interview to sharpen a plan or design.
grill-with-docs sickn33/antigravity-awesome-skills · score 70/100 (grade C)
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
hallmark Nutlope/hallmark · score 70/100 (grade C)
Design skill for websites and new pages that look designed, not generated. Use when the user asks to build or design something new, or names Hallmark. Never use it on an existing design unless the user names Hallmark, as in `/hallmark redesign <path>`.
industrial-brutalist-ui sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Use when creating raw industrial or tactical telemetry UIs with rigid grids, stark typography, CRT effects, and high-density data.
memory-engineering alirezarezvani/claude-skills · score 70/100 (grade C)
Use when designing, reviewing, or paying for an agent memory system — adding memory to an agent, choosing between long-context / RAG / graph / agentic memory, auditing what a CLAUDE.md or memory directory actually holds, deciding what to keep and what to expire, or when a memory store keeps growing and nobody has said what leaves it. Prices the write path, picks which cost to pay, classifies records as facts / skills / logs, and refuses a design that has no forgetting policy.
monetization-strategy Eronred/aso-skills · score 70/100 (grade C)
When the user wants to design or optimize their app's monetization — pricing, paywalls, subscriptions, or in-app purchases. Also use when the user mentions "pricing", "paywall", "subscription", "IAP", "how to monetize", "revenue optimization", "free trial", or "conversion to paid". For retention impact, see retention-optimization. For competitive pricing, see competitor-analysis.
nerdzao-elite sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Software engineering and product design workflow and Senior Product Designer. Full workflow with planning, architecture, TDD, clean code, and pixel-perfect UX validation.
nexrad-radar-visualization sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Plot NEXRAD Level II/III site scans and decoded radar mosaics with correct radar geometry, map grids, units, quality masks, timestamps, and provenance.
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.
osterwalder-canvas-architect sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Iterative consultant agent for building and validating logically consistent 9-block Business Model Canvases.
plan-canvas affaan-m/ECC · score 70/100 (grade C)
Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.
plan-canvas affaan-m/everything-claude-code · score 70/100 (grade C)
Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.
power-bi-report-design-consultation github/awesome-copilot · score 70/100 (grade C)
Power BI report visualization design prompt for creating effective, user-friendly, and accessible reports with optimal chart selection and layout design.
pricing-strategy alirezarezvani/claude-skills · score 70/100 (grade C)
Design, optimize, and communicate SaaS pricing — tier structure, value metrics, pricing pages, and price increase strategy. Use when building a pricing model from scratch, redesigning existing pricing, planning a price increase, or improving a pricing page. Trigger keywords: pricing tiers, pricing page, price increase, packaging, value metric, per seat pricing, usage-based pricing, freemium, good-better-best, pricing strategy, monetization, pricing page conversion, Van Westendorp. NOT for broader product strategy — use product-strategist for that. NOT for customer success or renewals — use customer-success-manager for expansion revenue.
robius-widget-patterns sickn33/antigravity-awesome-skills · score 70/100 (grade C)
CRITICAL: Use for Robius widget patterns. Triggers on: apply_over, TextOrImage, modal, 可复用, 模态, collapsible, drag drop, reusable widget, widget design, pageflip, 组件设计, 组件模式
site-architecture alirezarezvani/claude-skills · score 70/100 (grade C)
When the user wants to audit, redesign, or plan their website's structure, URL hierarchy, navigation design, or internal linking strategy. Use when the user mentions 'site architecture,' 'URL structure,' 'internal links,' 'site navigation,' 'breadcrumbs,' 'topic clusters,' 'hub pages,' 'orphan pages,' 'silo structure,' 'information architecture,' or 'website reorganization.' Also use when someone has SEO problems and the root cause is structural (not content or schema). NOT for content strategy decisions about what to write (use content-strategy) or for schema markup (use schema-markup).
stitch-design-taste sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Use when generating Google Stitch DESIGN.md systems for premium typography, color, layout, motion intent, and anti-generic UI rules.
threat-modeling-expert sickn33/antigravity-awesome-skills · score 70/100 (grade C)
Expert in threat modeling methodologies, security architecture review, and risk assessment. Masters STRIDE, PASTA, attack trees, and security requirement extraction. Use PROACTIVELY for security architecture reviews, threat identification, or building secure-by-design systems.
threejs-image-generator majidmanzarpour/threejs-game-skills · score 70/100 (grade C)
Generate and edit 2D image assets for Three.js games with Google's Gemini image API: concept sheets, image-to-3D inputs, texture and material references, sky and background plates, decals, logos, icons, GUI art, title and menu art, and marketing stills. Also use for direct image editing when the user supplies an image path.
ui-design-system alirezarezvani/claude-skills · score 70/100 (grade C)
UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use when creating design systems, generating design tokens, maintaining visual consistency, or facilitating design-dev collaboration and developer handoff.
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.
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.
agent-designer alirezarezvani/claude-skills · score 69/100 (grade C)
Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
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
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-data-visualization-matplotlib-fundamentals GPTomics/bioSkills · score 69/100 (grade C)
Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small gotchas that distinguish reproducible matplotlib from notebook scratch. Use when producing publication figures in Python — RNA-seq scatter, single-cell embeddings, generic biological plotting.
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-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-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.
brand-discovery affaan-m/ECC · score 69/100 (grade C)
Run a structured, resumable multi-session brand identity interview across 8 modules (purpose, positioning, audience, personality, voice, narrative, founder tension) using laddering, 5 Whys, and projective techniques, persisting answers to disk and producing a master brandbook (90_SYNTHESIS.md). Use when creating or repositioning a brand, briefing designers or writers, or making implicit founder knowledge explicit.
brand-discovery affaan-m/everything-claude-code · score 69/100 (grade C)
Run a structured, resumable multi-session brand identity interview across 8 modules (purpose, positioning, audience, personality, voice, narrative, founder tension) using laddering, 5 Whys, and projective techniques, persisting answers to disk and producing a master brandbook (90_SYNTHESIS.md). Use when creating or repositioning a brand, briefing designers or writers, or making implicit founder knowledge explicit.
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.
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.
confluence-expert alirezarezvani/claude-skills · score 69/100 (grade C)
Atlassian Confluence expert for creating and managing spaces, knowledge bases, and documentation. Configures space permissions and hierarchies, creates page templates with macros, sets up documentation taxonomies, designs page layouts, and manages content governance. Use when users need to build or restructure a Confluence space, design page hierarchies with permission structures, author or standardise documentation templates, embed Jira reports in pages, run knowledge base audits, or establish documentation standards and collaborative workflows.
content-management-systems github/awesome-copilot · score 69/100 (grade C)
Workflow for building and modifying content management systems across WordPress, Shopify, Wix, Squarespace, Drupal, WooCommerce, Joomla, HubSpot CMS Hub, Webflow, Adobe Experience Manager, and similar platforms. Use when working on CMS themes, plugins, apps, modules, admin panels, media uploads, content models, editors, markdown pipelines, or static export workflows.
create-canvas-extension github/awesome-copilot · score 69/100 (grade C)
Create or register a canvas extension in the awesome-copilot repository. Use when asked to scaffold a new canvas extension, create its plugin.json, add a reusable extension to one or more plugins, or migrate extension metadata. Extensions are reusable source under extensions/; shippable plugin manifests belong under plugins/.
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-schema-designer alirezarezvani/claude-skills · score 69/100 (grade C)
Use when the user asks to create ERD diagrams, normalize database schemas, design table relationships, or plan schema migrations.
figma heygen-com/hyperframes · score 69/100 (grade C)
Bring Figma into a HyperFrames video - rendered assets, brand tokens, components, storyboard frames as reconstructed motion (frames read as states, not slides), shaders and connector-assisted motion. Use when the person pastes a figma.com link or asks to use a Figma design, frame, logo or brand.
figma openai/skills · score 69/100 (grade C)
Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
figma-create-new-file openai/skills · score 69/100 (grade C)
Create a new blank Figma file. Use when the user wants to create a new Figma design or FigJam file, or when you need a new file before calling use_figma. Handles plan resolution via whoami if needed. Usage — /figma-create-new-file [editorType] [fileName] (e.g. /figma-create-new-file figjam My Whiteboard)
figma-generate-design openai/skills · score 69/100 (grade C)
Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code'. This is the preferred workflow skill whenever the user wants to build or update a full page, screen, or view in Figma from code or a description. Discovers design system components, variables, and styles via search_design_system, imports them, and assembles screens incrementally section-by-section using design system tokens instead of hardcoded values.
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.
frontend-design bytedance/deer-flow · score 69/100 (grade C)
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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.
google-cloud-solution-multi-agent-security google/skills · score 69/100 (grade C)
Designs, deploys, and secures Google Cloud Agent Gateway solutions. Use when the user needs to configure multi-agent security, ingress (CLIENT_TO_AGENT), or egress (AGENT_TO_ANYWHERE) patterns involving Model Armor, IAP, and Agent Registry. Don't use for general Cloud Load Balancing or basic VPC setup not related to Agent Gateways.
image-annotations github/awesome-copilot · score 69/100 (grade C)
Annotate screenshots, diagrams, and images with callout rectangles, arrows, labels, and color-coded highlights using PIL. Includes rules for animated GIF annotations with timing and pacing.
image-generation bytedance/deer-flow · score 69/100 (grade C)
Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided generation.
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.
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.
manim-video browser-use/video-use · score 69/100 (grade C)
Production pipeline for mathematical and technical animations using Manim Community Edition. Creates 3Blue1Brown-style explainer videos, algorithm visualizations, equation derivations, architecture diagrams, and data stories. Use when users request: animated explanations, math animations, concept visualizations, algorithm walkthroughs, technical explainers, 3Blue1Brown style videos, or any programmatic animation with geometric/mathematical content.
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.
music-generation bytedance/deer-flow · score 69/100 (grade C)
Use this skill when the user requests to generate, create, compose, or produce music or songs — background music, theme songs, jingles, or instrumental tracks. Generates a song from a style/mood prompt and optional lyrics via the MiniMax music API.
noob-mode github/awesome-copilot · score 69/100 (grade C)
Plain-English translation layer for non-technical Copilot CLI users. Translates every approval prompt, error message, and technical output into clear, jargon-free English with color-coded risk indicators.
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.
pricing-strategy sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Design pricing, packaging, and monetization strategies based on value, customer willingness to pay, and growth objectives.
referral-program Eronred/aso-skills · score 69/100 (grade C)
When the user wants to design, launch, or optimize an in-app referral / invite / share-to-earn program — including reward structure, mechanics, fraud prevention, deep link setup, and viral coefficient measurement. Use when the user mentions "referral program", "invite a friend", "refer and earn", "share to earn", "viral loop", "viral coefficient", "K-factor", "double-sided rewards", "give X get X", "referral rewards", "invite link", "share sheet", "Branch referrals", "in-app invites", or "how to make my app go viral". For deep link infrastructure that referrals depend on, see attribution-setup. For organic content-driven virality (UGC, creator), see creator-ugc-marketing.
salesforce-flow-design github/awesome-copilot · score 69/100 (grade C)
Salesforce Flow architecture decisions, flow type selection, bulk safety validation, and fault handling standards. Use this skill when designing or reviewing Record-Triggered, Screen, Autolaunched, Scheduled, or Platform Event flows to ensure correct type selection, no DML/Get Records in loops, proper fault connectors on all data-changing elements, and appropriate automation density checks before deployment.
senior-architect alirezarezvani/claude-skills · score 69/100 (grade C)
This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design". Use for architecture decision records (ADRs), tech stack evaluation, system design reviews, dependency analysis, and generating architecture diagrams in Mermaid, PlantUML, or ASCII format.
senior-computer-vision alirezarezvani/claude-skills · score 69/100 (grade C)
Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.
soc-operations briiirussell/cybersecurity-skills · score 69/100 (grade C)
Build, run, and improve a Security Operations Center — alert prioritization, runbook authoring, escalation criteria, on-call structure, alert tuning workflow, MTTD / MTTR / fidelity KPIs, analyst tiering, and shift handoffs. Use when the user mentions 'SOC,' 'security operations,' 'SOC analyst,' 'alert triage workflow,' 'runbook,' 'escalation,' 'on-call,' 'SOC tiering,' 'tier 1 / tier 2,' 'MTTD,' 'MTTR,' 'alert fatigue,' 'alert tuning,' 'shift handoff,' 'SOAR,' or wants to design or improve a security operations team.
tailwind-design-system sickn33/antigravity-awesome-skills · score 69/100 (grade C)
Build production-ready design systems with Tailwind CSS, including design tokens, component variants, responsive patterns, and accessibility.
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).
antigravity-design-expert sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Core UI/UX engineering skill for building highly interactive, spatial, weightless, and glassmorphism-based web interfaces using GSAP and 3D CSS.
apple-design emilkowalski/skills · score 68/100 (grade C)
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
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).
bigtable-basics google/skills · score 68/100 (grade C)
Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration.
bio-crispr-screens-perturb-seq-analysis GPTomics/bioSkills · score 68/100 (grade C)
Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.
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-data-visualization-sequence-logos GPTomics/bioSkills · score 68/100 (grade C)
Build sequence logos from aligned DNA, RNA, or protein motifs using ggseqlogo (R), Logomaker (Python), or WebLogo with explicit bits vs probability encoding, background-frequency correction, custom alphabets, and multi-logo stacking. Use when visualizing motif PWMs (TF binding, splice sites, CRISPR spacers), aligned-position composition, or comparing two motif sets.
bio-data-visualization-upset-plots GPTomics/bioSkills · score 68/100 (grade C)
Build UpSet plots to visualize set intersections beyond 4 sets (where Venn fails) using ComplexUpset (modern, ggplot2-grammar) or the unmaintained UpSetR, with explicit cardinality vs degree sorting, attribute panels, and query highlighting. Use when comparing overlap across many gene sets, peak sets, variant lists, or any set membership matrix where Venn diagrams become illegible.
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-multi-omics-data-harmonization GPTomics/bioSkills · score 68/100 (grade C)
Harmonizes already-normalized per-omic matrices onto a common footing before joint integration - assembling a MultiAssayExperiment, choosing the per-omic variance-stabilizing transform, deciding per-view versus per-feature scaling, picking a cross-omic batch strategy, and triaging missing data (feature, value, or whole sample; MAR versus MNAR). Covers why a shared-latent integrator is blind to what an omic is so scaling silently decides which block dominates, why batch confounded with biology is irrecoverable and should be modeled as a covariate not scrubbed, and why stacking blocks and running one ComBat erases cross-omic signal. Use when preparing two or more omics for MOFA2, mixOmics, or SNF, deciding a transform or scaling, correcting batch across modalities, or handling missing omics per sample. For deep per-omic normalization see differential-expression, methylation-analysis, proteomics, metabolomics; for the method decision see integration-design; for fusion see mofa-integration, mixomics-analysis.
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-phylo-tree-manipulation GPTomics/bioSkills · score 68/100 (grade C)
Edit phylogenetic tree structure with Biopython Bio.Phylo, and treat rooting as a separate statistical inference rather than a display choice. Covers why most inference returns an unrooted tree so placing the root creates every ancestor/descendant and basal claim; why a distant or lonely outgroup misroots inside the ingroup via long-branch attraction; the outgroup/midpoint/MAD/MinVar/non-reversible-likelihood rooting tradeoffs; why pruning must suppress degree-2 nodes and sum their branch lengths or all patristic distances silently corrupt; and why collapsing by support makes SOFT (uncertainty) polytomies, not HARD (radiation) ones. Use when rooting, re-rooting, pruning or subsetting taxa, extracting a clade or induced subtree, collapsing low-support branches, resolving polytomies, or ladderizing. Routes clock-based rooting to divergence-dating, inference to modern-tree-inference, and reading/plotting to tree-io and tree-visualization.
capture alirezarezvani/claude-skills · score 68/100 (grade C)
Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed ideas — even without the exact phrase — the intent is the same. Fast-to-action by design: no upfront intake. Output is four sections (Projects/Ideas, Tasks, Connections, How I Can Help) ending with a directive question. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project.
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).
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-design sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
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.
gke-networking google/skills · score 68/100 (grade C)
Plans, configures, and manages core GKE cluster networking. Covers private clusters, VPC-native configurations, DNS, node egress, Dataplane V2, and IP planning. Use when designing GKE networking layouts, configuring private clusters, setting up Dataplane V2, planning GKE IP ranges, or managing VPC- native cluster modes. Don't use for application ingress, load balancing, or service networking (use gke-service-networking instead).
globestudio github/awesome-copilot · score 68/100 (grade C)
Creates, edits and embeds dotted world maps and animated 3D globes with Globestudio (globestudio.app), a free open source studio with 21 looks. Use when the user wants a dotted map, a dotted or 3D globe, a spinning earth or a stylized world map for a website hero, background, slide, social post or video; when they paste a globestudio.app link or a ?c= config; or when code uses @globestudio/react, @globestudio/element, the globe-studio web component or globestudio.app/embed. Also use it to highlight a country, continent or region, plot points and arcs, match brand colors, or prepare PNG, SVG, GLB, MP4, WebM or GIF exports. Not for interactive tiled maps, routing, geocoding or GIS analysis (Mapbox, MapLibre, deck.gl), or for ordinary charts.
google-cloud-solution-build-deploy-agents google/skills · score 68/100 (grade C)
Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.
google-cloud-solution-n-tier-serverless-web-app google/skills · score 68/100 (grade C)
Assists in designing and implementing secure n-tier serverless web applications and microservices on Google Cloud. Use when users need architecture designs, security checklists, Terraform code, or deployment guidance for multi-tier serverless apps, regional data residency / European sovereignty compliance, zero-trust private VPC networking, or Private Service Connect. Don't use for VM, GKE, or non-Google Cloud architectures.
iam-audit briiirussell/cybersecurity-skills · score 68/100 (grade C)
Audit, design, and migrate Identity and Access Management — cloud provider IAM (AWS, GCP, Azure), identity providers (Okta, Entra ID / Azure AD, Auth0, Google Workspace), application authorization (RBAC, ABAC, ReBAC), and federated identity. Use when the user mentions 'IAM,' 'identity,' 'access management,' 'least privilege,' 'role design,' 'SSO,' 'SAML,' 'OIDC,' 'OAuth,' 'JIT access,' 'just-in-time access,' 'break-glass,' 'service accounts,' 'RBAC,' 'ABAC,' 'privilege creep,' 'role explosion,' 'identity governance,' 'IAM strategy,' 'identity migration,' 'Okta,' 'Entra ID,' 'Azure AD,' 'Auth0,' 'Cognito,' or needs identity consultant-level guidance.
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.
improve-codebase-architecture mattpocock/skills · score 68/100 (grade C)
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
llm-application-dev-ai-assistant sickn33/antigravity-awesome-skills · score 68/100 (grade C)
Design and implement conversational AI assistants with context management, integration boundaries, and validation.
mantis-pipeline-adapter google/mantis · score 68/100 (grade C)
Interactively guides the design and implementation of custom deterministic orchestrator harnesses. Use when a user wants to build their own pipeline to wrap and run Mantis skills reliably. Don't use for executing the default pipeline directly.
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).
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.
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
powerbi-modeling github/awesome-copilot · score 68/100 (grade C)
Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
product-marketing coreyhaines31/marketingskills · score 68/100 (grade C)
When the user wants to create or update their product marketing context document. Also use when the user mentions 'product context,' 'marketing context,' 'set up context,' 'positioning,' 'who is my target audience,' 'describe my product,' 'ICP,' 'ideal customer profile,' 'brand voice,' 'tone of voice,' 'brand guidelines,' 'what have we learned,' 'log this learning,' or wants to avoid repeating foundational information across marketing tasks. Use this at the start of any new project before using other marketing skills — it creates `.agents/product-marketing.md` that all other skills reference for product, audience, and positioning context.
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.
social coreyhaines31/marketingskills · score 68/100 (grade C)
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, or Facebook, or wants to do social listening and engagement triage. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' 'viral content,' 'what should I post,' 'repurpose this content,' 'tweet ideas,' 'LinkedIn carousel,' 'social media strategy,' 'grow my following,' 'TikTok video,' 'Reels,' 'Shorts,' 'video script,' 'video hook,' 'short-form video,' 'create a reel,' 'social listening,' 'brand mentions,' 'competitor monitoring,' 'top posts to comment on,' 'find people asking for,' 'carousel,' 'slide-by-slide,' or 'document post.' Use this for social content, repurposing, scheduling, video scripts, and listening. Posts avoid AI tells like 'it's not X, it's Y' reveals and broetry. For broader content strategy, see content-strategy. For paid ads, see ad-creative. For earned media, see public-relations.
threat-modeling briiirussell/cybersecurity-skills · score 68/100 (grade C)
Run a structured threat-modeling session for a new feature, system, or architecture — STRIDE, attack trees, data flow diagrams, abuse cases. Use when the user mentions 'threat model,' 'threat modeling,' 'STRIDE,' 'attack tree,' 'abuse case,' 'data flow diagram,' 'DFD,' 'security architecture review,' 'security review,' 'design review,' 'pre-implementation security,' 'shift left,' 'what could go wrong,' or needs strategic security thinking before code is written.
threejs-gameplay-systems majidmanzarpour/threejs-game-skills · score 68/100 (grade C)
Build and iterate playable Three.js game systems: starter scaffold, architecture, design briefs, core loops, level and encounter design, entities, input, camera, collision and physics, scoring, objectives, and game feel. Use for first playable slices, new Vite/TypeScript/Three.js setups, level/arena/track/wave/hole/puzzle design, combat encounters, difficulty tuning, and juice.
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.
agent-dx-cli-scale google-labs-code/design.md · score 67/100 (grade C)
A scoring scale for evaluating how well a CLI is designed for AI agents, based on the "Rewrite Your CLI for AI Agents" principles.
azure-smart-city-iot-solution-builder github/awesome-copilot · score 67/100 (grade C)
Design and plan end-to-end Azure IoT and Smart City solutions: requirements, architecture, security, operations, cost, and a phased delivery plan with concrete implementation artifacts.
bigquery-troubleshooting google/skills · score 67/100 (grade C)
Provides diagnostic workflows and step-by-step root-cause analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when interpreting symptoms, isolating bottlenecks, diagnosing cost spikes (on-demand query spend, capacity slot autoscaling, storage growth), execution graph stages or substep variables, identifying root causes, and determining remediation steps. Don't use for writing or optimizing SQL, proactive capacity planning, or storage layout design (use bigquery-optimization), or when the user already knows which telemetry they want and just needs the query (use bigquery-observability).
bio-crispr-screens-drugz-chemogenomic GPTomics/bioSkills · score 67/100 (grade C)
Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Colic et al. 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving greater sensitivity to small-effect hits than MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).
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-expression-matrix-metadata-joins GPTomics/bioSkills · score 67/100 (grade C)
Aligns sample metadata with count matrices and constructs design matrices for downstream DE, handling the alphabetical-reference-level trap (relevel BEFORE DESeq), LRT reduced-model rules, the interaction-term resultsNames trap, continuous-covariate scaling and splines, repeated measures via duplicateCorrelation or dream, high-cardinality categorical pseudo-singular designs, sample swap detection via XIST/RPS4Y1 expression and somalier/NGSCheckMate genotypes, SABV (sex-as-biological-variable) mandate, Simpson's-paradox collapsing of technical replicates, and the `~ 0 + group` parameterization for clean contrasts. Use when building a design matrix, troubleshooting reversed fold-change direction, encoding paired or repeated-measures designs, detecting sample swaps, deciding sex-as-covariate, or aggregating technical replicates.
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-methylation-cell-type-deconvolution GPTomics/bioSkills · score 67/100 (grade C)
Estimates cell-type composition from bulk DNA methylation and uses it to defuse the single biggest EWAS confounder. Covers reference-based deconvolution (Houseman constrained-projection, minfi estimateCellCounts2 with FlowSorted.Blood.EPIC + IDOL-optimized libraries, EpiDISH RPC/CBS/CP, 12-cell extended, cord-blood nRBC references, EpiSCORE/hepidish for solid tissue), reference-free correction (ReFACTor, RefFreeEWAS, SVA), using fractions as covariates vs the compositionality/collinearity trap, and cell-type-resolved EWAS (CellDMC, TCA, TOAST, omicwas, HIRE). Use when estimating blood/tissue cell fractions, adjusting an EWAS for composition, choosing a deconvolution reference, or attributing a methylation signal to a cell type. For the EWAS confounder-vs-mediator decision see ewas-design; for the IEAA cell-count adjustment of DNAm age see epigenetic-clocks; for clean beta input see array-preprocessing.
bio-multi-omics-integration-design GPTomics/bioSkills · score 67/100 (grade C)
Chooses a bulk multi-omics integration strategy before any tool runs by mapping the biological question (subtype discovery, shared axis of variation, predictive signature, pairwise correlation) to a method class, naming the sample correspondence (paired-vertical, horizontal, mosaic, diagonal), enforcing the n<<p discipline that makes a held-out cohort the endpoint instead of in-cohort cross-validation, and running the per-view variance-imbalance diagnostic. Covers the early/mixed/intermediate/late taxonomy, why vertical and horizontal integration are different problems, and why a shared factor dominated by one omic is not integration. Use when deciding which integration method fits a question, whether data is paired or mosaic, supervised or unsupervised, or how to validate an integrated result. For unsupervised factors see mofa-integration; for supervised signatures see mixomics-analysis; for stratification see similarity-network; for single-cell see single-cell/multimodal-integration.
bio-multi-omics-mixomics-analysis GPTomics/bioSkills · score 67/100 (grade C)
Builds supervised and unsupervised multivariate integration across bulk omics blocks with mixOmics - sPLS for sparse pairwise correlation, DIABLO (block.splsda) for a multi-block discriminant signature, rCCA for regularized canonical correlation, and MINT for multi-study integration. Covers why these projection methods maximize covariance or correlation and not truth, why DIABLO's design matrix is the central correlation-versus-discrimination decision, why cross-validation must wrap keepX selection or the reported error is leaked, why balanced error rate is required under class imbalance, and why DIABLO needs matched samples while MINT handles multiple cohorts. Use when finding a cross-omic discriminant signature for a known outcome, selecting correlated features between two omics, tuning keepX, or integrating one omic across studies. For unsupervised factors see mofa-integration; for the method decision see integration-design; for cross-validation theory see machine-learning/model-validation.
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-systems-biology-strain-design GPTomics/bioSkills · score 67/100 (grade C)
Computes metabolic-engineering strain designs on genome-scale models with StrainDesign (OptKnock, RobustKnock, minimal cut sets, OptCouple) and cameo (heuristic knockout and FSEOF over/under-expression targets), finding gene/reaction interventions that couple product formation to growth. Use when designing knockouts to overproduce a target chemical, choosing between OptKnock and RobustKnock, growth-coupling a product so evolution maintains it, computing minimal cut sets, finding amplification targets with FSEOF, or understanding why MILP strain design needs a strong solver and why a design is only a hypothesis.
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-timecourse-pipeline GPTomics/bioSkills · score 67/100 (grade C)
End-to-end bulk time-course analysis from an expression matrix to temporal gene modules and per-cluster pathway enrichment. Orchestrates temporal DE (limma splines or DESeq2 LRT), Mfuzz/tslearn soft clustering of expression-profile shapes, GAM trajectory fitting, per-cluster GO enrichment against a temporal-gene background, and an OPTIONAL circadian rhythm-detection branch (MetaCycle/CosinorPy) that runs only when the design covers >=2 full cycles with >=6-8 evenly spaced samples per cycle. Use when analyzing a bulk time-series expression experiment from any omics platform and deciding limma-splines vs DESeq2-LRT for temporal DE, soft vs hard clustering, whether the sampling design even licenses rhythm detection, and which background to use for enrichment. Not for single-cell pseudotime (see temporal-genomics/trajectory-modeling for the bulk-vs-pseudotime boundary) or unknown-period discovery (see temporal-genomics/periodicity-detection).
brand nextlevelbuilder/ui-ux-pro-max-skill · score 67/100 (grade C)
Brand voice, visual identity, messaging frameworks, asset management, brand consistency. Activate for branded content, tone of voice, marketing assets, brand compliance, style guides.
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.
consulting-analysis bytedance/deer-flow · score 67/100 (grade C)
Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.
cpo-advisor alirezarezvani/claude-skills · score 67/100 (grade C)
Product leadership for scaling companies. Product vision, portfolio strategy, product-market fit, and product org design. Use when setting product vision, managing a product portfolio, measuring PMF, designing product teams, prioritizing at the portfolio level, reporting to the board on product, or when user mentions CPO, product strategy, product-market fit, product organization, portfolio prioritization, or roadmap strategy.
DevOps Engineer alirezarezvani/claude-skills · score 67/100 (grade C)
Builds infrastructure that scales without babysitting. Automates everything worth automating. Monitors before it breaks. Treats clicking in consoles as a production incident waiting to happen. Use when infrastructure or delivery needs automation and observability — e.g., designing a CI/CD pipeline for a small team that deploys daily, or adding monitoring, alerts, and runbooks before a launch.
dotnet-design-pattern-review github/awesome-copilot · score 67/100 (grade C)
Review the C#/.NET code for design pattern implementation and suggest improvements.
error-handling affaan-m/ECC · score 67/100 (grade C)
Patterns for robust error handling across TypeScript, Python, and Go. Covers typed errors, error boundaries, retries, circuit breakers, and user-facing error messages. Use when designing error types, retries, circuit breakers, or user-facing failure messages in TypeScript, Python, or Go.
error-handling affaan-m/everything-claude-code · score 67/100 (grade C)
Patterns for robust error handling across TypeScript, Python, and Go. Covers typed errors, error boundaries, retries, circuit breakers, and user-facing error messages. Use when designing error types, retries, circuit breakers, or user-facing failure messages in TypeScript, Python, or Go.
frontend-design Galaxy-Dawn/claude-scholar · score 67/100 (grade C)
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
game-engine github/awesome-copilot · score 67/100 (grade C)
Expert skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.
gdpr-compliant github/awesome-copilot · score 67/100 (grade C)
Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
gke-multitenancy google/skills · score 67/100 (grade C)
Plans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE teams. Don't use for single-tenant cluster configuration or general deployment instructions (use gke-basics or gke-app-onboarding instead).
google-cloud-solution-agentic-ai-bidirectional-streaming google/skills · score 67/100 (grade C)
Guides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements.
google-cloud-solution-agentic-ai-borderless-data-lakehouse google/skills · score 67/100 (grade C)
Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).
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).
google-cloud-solution-guided-gke-ai-migration google/skills · score 67/100 (grade C)
Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
google-cloud-solution-hybrid-search-alloydb google/skills · score 67/100 (grade C)
Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.
influencer-marketing coreyhaines31/marketingskills · score 67/100 (grade C)
When the user wants to run influencer, creator, or ambassador partnerships to promote their product — finding and vetting partners, structuring deals, briefing creators, disclosure compliance, and measuring ROI. Also use when the user mentions 'influencer marketing,' 'creator partnerships,' 'sponsorships,' 'YouTube sponsorships,' 'podcast sponsorships,' 'newsletter sponsorship,' 'newsletter ad,' 'sponsor a newsletter,' 'brand ambassador,' 'ambassador program,' 'creator program,' 'UGC creators,' 'tech UGC,' 'UGC creator program,' 'creator network,' 'B2B influencers,' 'thought leader ads,' 'gifting,' 'product seeding,' 'whitelisting creator content,' 'Telegram channel ads,' 'buy a post in a Telegram channel,' 'how much to pay an influencer,' or 'FTC disclosure.' For affiliate/referral payout mechanics, see referrals. For community-led advocacy, see community-marketing. For turning creator content into paid ads, see ad-creative.
napkin github/awesome-copilot · score 67/100 (grade C)
Visual whiteboard collaboration for Copilot CLI. Creates an interactive whiteboard that opens in your browser — draw, sketch, add sticky notes, then share everything back with Copilot. Copilot sees your drawings and text, and responds with analysis, suggestions, and ideas.
prototype mattpocock/skills · score 67/100 (grade C)
Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
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.
remotion-to-hyperframes heygen-com/hyperframes · score 67/100 (grade C)
Bring existing video code or footage into HyperFrames and verify it frame by frame against the original - Remotion first, also Motion Canvas, Lottie, Three.js, p5.js, canvas or plain HTML/CSS animation, or renders from Manim, After Effects or Blender. Use to port, convert, migrate or reuse work made with another tool.
skill-comply affaan-m/ECC · score 67/100 (grade C)
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.
skill-comply affaan-m/everything-claude-code · score 67/100 (grade C)
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.
spanner-basics google/skills · score 67/100 (grade C)
Assists in provisioning instances and databases, designing performant schemas, and querying data in Cloud Spanner on Google Cloud. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues.
technology-stack-blueprint-generator github/awesome-copilot · score 67/100 (grade C)
Comprehensive technology stack blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks, programming languages, and implementation patterns across multiple platforms (.NET, Java, JavaScript, React, Python). Generates configurable blueprints with version information, licensing details, usage patterns, coding conventions, and visual diagrams. Provides implementation-ready templates and maintains architectural consistency for guided development.
threejs-textures cloudai-x/threejs-skills · score 67/100 (grade C)
Three.js textures: image loading, color spaces, UV channels and transforms, texture types from canvas to HDR and KTX2, render targets, texture memory. Use when working with images on materials, UV coordinates, cubemaps, render targets or texture optimization; on WebGL or with WebGPU and TSL.
understand-figma Egonex-AI/Understand-Anything · score 67/100 (grade C)
Analyze a Figma file via the Figma REST API and generate an interactive design knowledge graph (pages, screens, components, component sets, instances, design tokens) with a kind:"design" dashboard.
analysis-artifacts warpdotdev/oz-skills · score 66/100 (grade C)
Generate reproducible analysis artifacts — SQL queries, Python visualizations, and summary tables — as you work through a BigQuery data analysis. Use when asked to conduct a deep dive, exploratory analysis, or investigation that goes beyond a simple data lookup.
arduino-azure-iot-edge-integration github/awesome-copilot · score 66/100 (grade C)
Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.
backend-patterns affaan-m/ECC · score 66/100 (grade C)
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes. Use when building or reviewing Node.js, Express, or Next.js API routes and their data access.
backend-patterns affaan-m/everything-claude-code · score 66/100 (grade C)
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes. Use when building or reviewing Node.js, Express, or Next.js API routes and their data access.
bio-atac-seq-nucleosome-positioning GPTomics/bioSkills · score 66/100 (grade C)
Map nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter. Use when characterizing nucleosome organization at promoters and enhancers, calling +1/-1 nucleosomes flanking NFRs, generating V-plots for chromatin structure visualization, or comparing nucleosome positioning between conditions.
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-covalent-design GPTomics/bioSkills · score 66/100 (grade C)
Designs covalent inhibitors and warheads targeting cysteine, lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, boronate, nitrile), reversibility (kinact/Ki, t_residence), glutathione (GSH) stability, intrinsic reactivity assays, and covalent docking (DOCKovalent, GOLD, HCovDock). Use when designing covalent inhibitors for targeted covalent inhibition (TCI), KRAS G12C-style approaches, or rationalizing covalent SAR.
bio-crispr-screens-library-design GPTomics/bioSkills · score 66/100 (grade C)
Designs pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TSS windows, deciding control-guide proportions, or diagnosing library skew and dropout in a freshly cloned pool.
bio-data-visualization-manhattan-qq-locuszoom GPTomics/bioSkills · score 66/100 (grade C)
Build Manhattan, Miami, QQ, and locuszoom-style regional plots from GWAS, TWAS, PWAS, and QTL summary statistics with correct genomic-inflation diagnostics, multi-trait overlays, lead-SNP labeling, and LD-aware regional rendering. Use when visualizing association results across the genome, comparing two traits, computing genomic inflation lambda, or zooming into a locus with LD coloring.
bio-data-visualization-oncoprint-mutation-matrices GPTomics/bioSkills · score 66/100 (grade C)
Build OncoPrint and co-mutation matrix plots from somatic-variant cohorts using ComplexHeatmap, maftools, and comut.py with alteration-type stacking, sample ordering by mutational burden, mutual-exclusivity overlays, and clinical annotation tracks. Use when visualizing per-sample mutation patterns across recurrent driver genes, comparing alteration classes, or identifying mutually-exclusive / co-occurring driver pairs.
bio-experimental-design-sample-size GPTomics/bioSkills · score 66/100 (grade C)
Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.
bio-flow-cytometry-bead-normalization GPTomics/bioSkills · score 66/100 (grade C)
Bead-based signal normalization and cross-batch harmonization for CyTOF and high-parameter cytometry - EQ four-element bead normalization of instrument sensitivity drift (CATALYST normCytof, premessa), and reference-anchor cross-batch normalization (CytoNorm, per-cluster quantile splines). Covers the distinction between within-run drift correction and between-batch correction, the mandatory anchor/reference sample, why normalization is per-cluster with many quantiles, and the over-correction risk. Use when correcting CyTOF signal drift, harmonizing multi-batch or multi-site studies, or deciding whether to normalize data versus model batch in the design.
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-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-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-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-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-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-workflows-crispr-editing-pipeline GPTomics/bioSkills · score 66/100 (grade C)
Orchestrates an end-to-end CRISPR editing experiment design from target gene to delivery-ready, validatable constructs. Sequences guide design, off-target assessment, edit-modality selection (knockout, base editing, prime editing, HDR knock-in), and template/donor design, with a QC checkpoint at each handoff. Use when designing a complete CRISPR experiment for knockout, point correction, or tagging and the order of operations, the modality decision, and the cross-cutting traps are needed rather than a single step. Defers each step's mechanics to the genome-engineering skills.
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-expression-to-pathways GPTomics/bioSkills · score 66/100 (grade C)
Orchestrates the full path from differential expression results to redundancy-collapsed functional enrichment: choose ORA vs GSEA, convert gene IDs per method, run enrichGO/enrichKEGG/enrichPathway/enrichWP or gseGO/gseKEGG (clusterProfiler, ReactomePA, rWikiPathways), and visualize. Use when a DESeq2/edgeR/limma result must become enriched GO terms, KEGG/Reactome/WikiPathways pathways, or a GSEA leading edge; when the input is a full ranking for all genes (GSEA, named decreasing vector) or only a pre-selected list (ORA plus a defensible background universe); or when assembling DE-to-pathway end to end. The DE list and ranking statistic come from differential-expression/de-results; per-method nuance lives in the pathway-analysis skills.
brand-voice affaan-m/ECC · score 66/100 (grade C)
Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.
brand-voice affaan-m/everything-claude-code · score 66/100 (grade C)
Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.
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.
community-marketing coreyhaines31/marketingskills · score 66/100 (grade C)
Build and leverage online communities to drive product growth and brand loyalty. Use when the user wants to create a community strategy, grow a Discord or Slack community, manage a forum or subreddit, build brand advocates, increase word-of-mouth, drive community-led growth, engage users post-signup, or turn customers into evangelists. Trigger phrases: \"build a community,\" \"community strategy,\" \"Discord community,\" \"Slack community,\" \"community-led growth,\" \"brand advocates,\" \"user community,\" \"forum strategy,\" \"community engagement,\" \"grow our community,\" \"ambassador program,\" \"community flywheel.\"
creative-portfolio-resume Paramchoudhary/ResumeSkills · score 66/100 (grade C)
Balance visual design with ATS compatibility for creative roles
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-content-creator alirezarezvani/claude-skills · score 66/100 (grade C)
Long-form marketing content producer orchestrating the content-production skill (research → brief → draft → optimize → gate). Use when content must be written, scored, or made publish-ready — e.g., drafting a 2,000-word blog post against a target keyword and blocking publish until content_quality_gates.py passes, or auditing a draft for brand-voice drift with brand_voice_analyzer.py before it ships. Routes planning requests (topic clusters, calendars) to content-strategy. Supersedes the deprecated content-creator skill.
ddd-strategic-design sickn33/antigravity-awesome-skills · score 66/100 (grade C)
Design DDD strategic artifacts including subdomains, bounded contexts, and ubiquitous language for complex business domains.
django-patterns affaan-m/ECC · score 66/100 (grade C)
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps. Use when building or reviewing Django apps, DRF APIs, ORM queries, or caching.
django-patterns affaan-m/everything-claude-code · score 66/100 (grade C)
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps. Use when building or reviewing Django apps, DRF APIs, ORM queries, or caching.
emil-design-eng emilkowalski/skills · score 66/100 (grade C)
This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.
google-cloud-waf-sustainability google/skills · score 66/100 (grade C)
Provides recommendations for environmental sustainability, carbon footprint reduction, and energy efficiency based on the Sustainability pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks to assess, design, or optimize Google Cloud workloads for sustainability—including the shared responsibility model, selecting low-carbon regions (CFE%), reducing resource and AI/ML energy waste, designing efficient software and storage lifecycles, or measuring and tracking emissions using Google Cloud Carbon Footprint. Don't use for financial cost reduction (use google-cloud-waf-cost-optimization), latency and throughput tuning (use google-cloud-waf-performance-optimization), or high availability and disaster recovery (use google-cloud-waf-reliability).
high-end-visual-design sickn33/antigravity-awesome-skills · score 66/100 (grade C)
Use when designing expensive agency-grade interfaces with premium fonts, spatial rhythm, soft depth, and fluid microinteractions.
md-review alirezarezvani/claude-skills · score 66/100 (grade C)
Converts a markdown PR writeup or code review (one with ```diff fenced blocks and severity-tagged GFM callouts [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer. Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs-md-review. Refuses without explicit --reviewer (a code review must name a human), refuses if no diff hunks present (route to md-document instead), and refuses to encode severity in color only (every badge ships color + icon + aria-label per WCAG 1.4.1). Use after orchestrator routing.
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.
rag-architect alirezarezvani/claude-skills · score 66/100 (grade C)
Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for this corpus', 'evaluate my retriever against ground truth'. NOT for general LLM cost tuning (use llm-cost-optimizer) or agent loops over retrieval (use agenthub).
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.
threejs-aaa-graphics-builder majidmanzarpour/threejs-game-skills · score 66/100 (grade C)
Upgrade Three.js games from prototype visuals to premium browser graphics: art-direction critique, procedural model building, material and texture libraries, world prop kits, shaders, VFX, lighting and render pipeline, LOD and instancing, render budgets, and a 10-category visual scorecard. Use when screenshots still look basic or the user asks for premium, AAA, high-fidelity, showcase, or less-basic graphics.
understand-dashboard Egonex-AI/Understand-Anything · score 66/100 (grade C)
Launch the interactive web dashboard to visualize a codebase's knowledge graph
web-design-guidelines bytedance/deer-flow · score 66/100 (grade C)
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".
2d-games sickn33/antigravity-awesome-skills · score 65/100 (grade C)
2D game development principles. Sprites, atlases, tilemaps, physics, cameras, and genre patterns (platformer, top-down). Use for canvas/Phaser/Kaplay/Pixi 2D games or guest viewports inside hybrid web apps.
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.
bio-analytical-validation GPTomics/bioSkills · score 65/100 (grade C)
Treats a ctDNA assay as a molecule-counting experiment at the Poisson edge and builds its analytical-validation case the measurement-science way. Covers the genome-equivalent currency (~330 haploid copies/ng), the lambda = input_GE x VAF sampling ceiling (lambda>=3 for ~95% detection), the error-suppression ladder (raw NGS ~1e-3 -> single-strand UMI ~1e-4/1e-5 -> duplex <1e-7), the CLSI EP17 LoB/LoD/LoD95/LoQ framework, the per-locus-vs-panel-integrated LoD distinction that lets bespoke MRD reach ppm, contrived/SEQC2 reference standards, and honest LoD reporting conditioned on input mass + consensus depth + replicate detection rate. Use when stating or trusting a sensitivity claim, designing a dilution-series validation, deciding how many genome equivalents are needed at a target VAF, choosing a single-locus vs panel-integrated LoD, or auditing a "detects 0.1% VAF" claim.
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-crispr-screens-combinatorial-screens GPTomics/bioSkills · score 65/100 (grade C)
Designs and analyzes combinatorial CRISPR screens covering paired-Cas9 (Big Papi, Najm 2018), enhanced AsCas12a multiplex (enCas12a, DeWeirdt 2021), in4mer 4-guide-array Cas12a (Esmaeili Anvar N et al 2024 Nat Commun 15:3577) and the Inzolia paralog-pair library, paralog-buffering detection (Dede 2020 Genome Biol; Thompson 2021 Nat Commun 12:1302), genetic-interaction (GI) scoring as observed_double_LFC minus expected_additive_double_LFC, synthetic-lethal and synthetic-rescue interaction interpretation, the half-of-essentiality buffered by paralogs phenomenon, multiplex screen statistical analysis with MAGeCK MLE interaction terms, and the relationship to single-cell combinatorial Perturb-seq. Use when designing a paralog or pathway-pair screen, choosing between paired-Cas9 (Big Papi) and Cas12a multiplex (Inzolia), interpreting genetic interaction scores, identifying synthetic-lethal targets for drug development, or scaling beyond single-gene CRISPR screens.
bio-crispr-screens-crispresso-editing GPTomics/bioSkills · score 65/100 (grade C)
Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-frequency tables; and failure modes from amplicon misalignment or contamination. Use when quantifying editing from amplicon sequencing, choosing CRISPResso mode by design, distinguishing intended edits from bystanders and indel byproducts, debugging low-alignment runs, or generating publication-grade editing reports.
bio-data-visualization-flow-and-transition-plots GPTomics/bioSkills · score 65/100 (grade C)
Build Sankey, alluvial, river, and CONSORT-style flow diagrams to visualize cohort transitions, cell-state changes, or pipeline filtering using ggalluvial, networkD3, plotly, and consort. Use when showing how entities move between categories across timepoints (cell states, drug response classes, patient flow through a trial) or filtering pipelines (variants filtered through QC stages).
bio-data-visualization-interactive-visualization GPTomics/bioSkills · score 65/100 (grade C)
Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.
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-expression-matrix-normalization GPTomics/bioSkills · score 65/100 (grade C)
Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (scran deconvolution, scanpy normalize_total). Encodes the composition-bias rationale, the "most genes not DE" assumption and its catastrophic failure modes (MYC amplification, apoptosis, viral host shutoff, prokaryotic stress), the "lengthScaledTPM is not TPM" naming trap, the "TPM is not for DE" rule, the blind=TRUE vs FALSE decision, ERCC spike-in normalization (SBN), and the single-cell zero-inflation breakdown of TMM/RLE. Use when choosing or applying normalization, debugging shifted-MA-plot diagnostics, handling zero-heavy single-cell data, or correcting GC bias.
bio-hi-c-analysis-hic-visualization GPTomics/bioSkills · score 65/100 (grade C)
Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.
bio-immunoinformatics-epitope-prediction GPTomics/bioSkills · score 65/100 (grade C)
Predict B-cell and T-cell epitopes for vaccine antigen design and epitope mapping with BepiPred-3.0, DiscoTope-3.0, the IEDB tools, and EL-mode MHC presentation. Encodes the load-bearing asymmetry that T-cell epitope prediction is mature (it reduces to MHC presentation, AUC>0.9) while B-cell prediction is unreliable (linear predictors ~AUC 0.6 because ~90% of real epitopes are conformational) — so structure-based DiscoTope-3.0 on AlphaFold models is the only defensible B-cell path, propensity scales are obsolete, and NetChop is largely redundant on EL-trained models. Use when mapping epitopes or selecting vaccine antigens. MHC binding lives in mhc-binding-prediction.
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-phylo-tree-visualization GPTomics/bioSkills · score 65/100 (grade C)
Draw and export phylogenetic trees with Bio.Phylo plus matplotlib, and route rich figures to ggtree, ETE4, or iTOL. Covers why a tree figure is an argument not a neutral picture, the cladogram-vs-phylogram-vs-chronogram choice that hides or reveals rate and time, how ladderization manufactures a false arrow of progress, why an unlabeled support number always flatters the result (bootstrap vs posterior vs SH-aLRT vs UFBoot are different scales), why Bio.Phylo silently drops BEAST HPD bars so annotated Bayesian trees must go through treeio plus ggtree, and the tip-count and raster-vs-vector thresholds for legible publication figures. Use when drawing a tree, choosing a layout, coloring branches, showing or labeling support, exporting vector figures, or deciding a drawing tool. Routes annotation-preserving reads to tree-io, and rooting and ladderizing to tree-manipulation.
bio-restriction-golden-gate-assembly GPTomics/bioSkills · score 65/100 (grade C)
Design and validate Type IIS scarless DNA assembly (Golden Gate, MoClo) using Biopython Bio.Restriction. Screens parts for internal BsaI/BsmBI/BbsI/SapI sites (domestication), previews the fusion overhangs a digest exposes, and validates a fusion-overhang set for distinctness and fidelity. Use when designing a Golden Gate or MoClo assembly, domesticating a part by removing internal Type IIS sites, or choosing and checking fusion overhangs for one-pot assembly.
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.
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.
google-cloud-solution-rag-enterprise-search-gke-sqldb google/skills · score 65/100 (grade C)
Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.
minimax-pdf MiniMax-AI/skills · score 65/100 (grade C)
Use this skill when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal", "create a resume", "beautiful PDF", "professional document", "cover page", "polished PDF", "client-ready document". FILL (complete form fields): "fill in the form", "fill out this PDF", "complete the form fields", "write values into PDF", "what fields does this PDF have". REFORMAT (apply design to an existing doc): "reformat this document", "apply our style", "convert this Markdown/text to PDF", "make this doc look good", "re-style this PDF". This skill uses a token-based design system: color, typography, and spacing are derived from the document type and flow through every page. The output is print-ready. Prefer this skill when appearance matters, not just when any PDF output is needed.
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.
springboot-patterns affaan-m/ECC · score 65/100 (grade C)
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work. Use when building or reviewing a Spring Boot backend — REST layer, services, data access, caching, or async work.
springboot-patterns affaan-m/everything-claude-code · score 65/100 (grade C)
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work. Use when building or reviewing a Spring Boot backend — REST layer, services, data access, caching, or async work.
swiftui-liquid-glass Dimillian/Skills · score 65/100 (grade C)
Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
threejs-debug-profiler majidmanzarpour/threejs-game-skills · score 65/100 (grade C)
Debug and profile Three.js browser games: blank canvases, render and runtime bugs, asset and audio loading, animation, resize, mobile input, plus performance profiling of draw calls, triangles, textures, memory, shader and post-processing cost, and bundle size.
tradingview-reader himself65/finance-skills · score 65/100 (grade C)
Read the user's local TradingView desktop app through opencli: quotes, options chains with greeks and per-strike IV, options expiries, screener results across stocks, crypto, forex, futures, and bonds, gainers and losers, news headlines and full stories, alerts (active, fired, offline fires), watchlists including colored flag lists, symbol search, chart state, and chart screenshots. Use this skill whenever the user asks for any of these from TradingView ("TV") — for example an options chain, puts, or IV skew for a ticker, an oversold-stock screen, their red flag list, which alerts fired, or a screenshot of their chart. For plain quotes, TA readouts, scans, or futures without the desktop app, prefer tradingview-mcp. Read-only: it never places trades or edits watchlists, alerts, or layouts.
agent-harness-construction affaan-m/ECC · score 64/100 (grade D)
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's tool set, action space, or observation format.
agent-harness-construction affaan-m/everything-claude-code · score 64/100 (grade D)
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's tool set, action space, or observation format.
algorithmic-art anthropics/skills · score 64/100 (grade D)
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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-crispr-screens-in-vivo-screens GPTomics/bioSkills · score 64/100 (grade D)
Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.
bio-data-visualization-ggplot2-fundamentals GPTomics/bioSkills · score 64/100 (grade D)
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
bio-data-visualization-heatmaps-clustering GPTomics/bioSkills · score 64/100 (grade D)
Build clustered heatmaps for expression matrices and other features-by-samples data with rigorous distance/linkage/scaling choices, robust color mapping, optimal leaf ordering, and ComplexHeatmap/pheatmap/seaborn rendering. Covers the ward.D vs ward.D2 trap, the row-vs-column scaling decision, multi-track annotations, oncoPrint, and raster rendering for large matrices. Use when visualizing expression patterns across samples or identifying co-regulated clusters.
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-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-epitranscriptomics-m6a-differential GPTomics/bioSkills · score 64/100 (grade D)
Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).
bio-metabolomics-normalization-qc GPTomics/bioSkills · score 64/100 (grade D)
Designs QC, corrects signal drift, removes batch effects, filters features, normalizes samples, and imputes missing values for untargeted LC-MS/GC-MS metabolomics, framing each step as a measurement model that can create or erase biological signal. Use when processing a peak/feature table before statistical analysis, choosing a drift-correction or sample-normalization method, deciding QC RSD vs D-ratio filtering, or handling left-censored missing values. The feature table is produced by metabolomics/xcms-preprocessing or metabolomics/msdial-preprocessing; transformation/scaling for modeling defers to metabolomics/statistical-analysis; cross-study design issues link to experimental-design/batch-design.
bio-metabolomics-targeted-analysis GPTomics/bioSkills · score 64/100 (grade D)
Designs and validates quantitative targeted metabolomics assays (MRM/SRM on triple-quadrupole, PRM on high-resolution instruments) to report absolute concentrations. Covers the internal-standard strategy (external cal -> global IS -> standard addition -> stable-isotope-labeled IS), weighted calibration judged by back-calculated %RE not R-squared, ion-ratio quantifier/qualifier confirmation, matrix-effect/recovery characterization, and ICH M10 method validation. Use when quantifying a closed panel of known metabolites with units, building or validating an LC-MS/MS assay, choosing an IS or calibration weighting, or judging whether a reported concentration is trustworthy. For untargeted feature detection see metabolomics/xcms-preprocessing; for group statistics see metabolomics/statistical-analysis; for flux/MID/tracing see metabolomics/isotope-tracing.
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-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-workflows-merip-pipeline GPTomics/bioSkills · score 64/100 (grade D)
Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation curves, exomePeak2 (transcript-aware, GC-bias-aware negative-binomial GLM) peak calling, optional MACS3 broad-peak cross-check, DRACH motif confirmation as a sanity check (NOT a per-peak filter), exomePeak2 differential calling via the four-BAM-vector interface (bam_ip + bam_input control; bam_treated_ip + bam_treated_input treatment), ChIPseeker annotation, and the canonical Guitar metagene with stop-codon enrichment as the biological QC anchor. Use when running a complete MeRIP analysis from raw reads, when chaining the constituent epitranscriptomics skills (merip-preprocessing -> m6a-peak-calling -> m6a-differential -> modification-visualization), or when wrapping the pipeline in Snakemake / Nextflow.
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".
canvas-design ComposioHQ/awesome-claude-skills · score 64/100 (grade D)
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
canvas-design anthropics/skills · score 64/100 (grade D)
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
cloud-design-patterns github/awesome-copilot · score 64/100 (grade D)
Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.
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.
fluentui-blazor github/awesome-copilot · score 64/100 (grade D)
Guide for using the Microsoft Fluent UI Blazor component library (Microsoft.FluentUI.AspNetCore.Components NuGet package) in Blazor applications. Use this when the user is building a Blazor app with Fluent UI components, setting up the library, using FluentUI components like FluentButton, FluentDataGrid, FluentDialog, FluentToast, FluentNavMenu, FluentTextField, FluentSelect, FluentAutocomplete, FluentDesignTheme, or any component prefixed with "Fluent". Also use when troubleshooting missing providers, JS interop issues, or theming.
folder-structure-blueprint-generator github/awesome-copilot · score 64/100 (grade D)
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
gem-devops-guidelines github/awesome-copilot · score 64/100 (grade D)
Design or review infrastructure, deployment, CI/CD, Docker, Kubernetes, health checks, rollback, feature flags, production readiness, and mobile release workflows. Use for DevOps, platform, container, pipeline, or release tasks.
gsap-framer-scroll-animation github/awesome-copilot · score 64/100 (grade D)
Use this skill whenever the user wants to build scroll animations, scroll effects, parallax, scroll-triggered reveals, pinned sections, horizontal scroll, text animations, or any motion tied to scroll position — in vanilla JS, React, or Next.js. Covers GSAP ScrollTrigger (pinning, scrubbing, snapping, timelines, horizontal scroll, ScrollSmoother, matchMedia) and Framer Motion / Motion v12 (useScroll, useTransform, useSpring, whileInView, variants). Use this skill even if the user just says "animate on scroll", "fade in as I scroll", "make it scroll like Apple", "parallax effect", "sticky section", "scroll progress bar", or "entrance animation". Also triggers for Copilot prompt patterns for GSAP or Framer Motion code generation. Pairs with the premium-frontend-ui skill for creative philosophy and design-level polish.
image-prompt davidondrej/skills · score 64/100 (grade D)
Write four distinct prompts for AI image models. Use for image, thumbnail, banner, logo, or illustration prompts. Produces prompt text only.
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.
linkedin-post-formatter github/awesome-copilot · score 64/100 (grade D)
Format and draft compelling LinkedIn posts using Unicode bold/italic styling, visual separators, structured sections, and engagement-optimized patterns. USE FOR: draft LinkedIn post, format text for LinkedIn, create social media post, write thought leadership post, convert content to LinkedIn format, LinkedIn carousel text, Unicode bold italic formatting.
obsidian-literature-workflow Galaxy-Dawn/claude-scholar · score 64/100 (grade D)
Use this skill for project-scoped literature review built on Sources/Papers, with synthesis landing in Knowledge, writing handoff in Writing, and the default literature canvas under Maps/literature.canvas.
orch-add-feature affaan-m/ECC · score 64/100 (grade D)
Orchestrate building a brand-new feature end to end — research, plan, TDD implementation, review, and gated commit — by delegating each phase to the matching ECC agent. Use when adding a capability that does not exist yet.
orch-add-feature affaan-m/everything-claude-code · score 64/100 (grade D)
Orchestrate building a brand-new feature end to end — research, plan, TDD implementation, review, and gated commit — by delegating each phase to the matching ECC agent. Use when adding a capability that does not exist yet.
postgres-patterns affaan-m/ECC · score 64/100 (grade D)
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices. Use when designing PostgreSQL schemas, indexes, or RLS policies, or when a query is too slow.
postgres-patterns affaan-m/everything-claude-code · score 64/100 (grade D)
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices. Use when designing PostgreSQL schemas, indexes, or RLS policies, or when a query is too slow.
ppt-generation bytedance/deer-flow · score 64/100 (grade D)
Use this skill when the user requests to generate, create, or make presentations (PPT/PPTX). Creates visually rich slides by generating images for each slide and composing them into a PowerPoint file.
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.
recsys-pipeline-architect affaan-m/ECC · score 64/100 (grade D)
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm. Use this skill whenever the user is building any system that picks "the top K items for a (user, context)" — social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.
recsys-pipeline-architect affaan-m/everything-claude-code · score 64/100 (grade D)
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm. Use this skill whenever the user is building any system that picks "the top K items for a (user, context)" — social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.
review-animations emilkowalski/skills · score 64/100 (grade D)
Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.
theme-factory ComposioHQ/awesome-claude-skills · score 64/100 (grade D)
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
theme-factory anthropics/skills · score 64/100 (grade D)
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
threat-hunting sickn33/antigravity-awesome-skills · score 64/100 (grade D)
Blue-team threat hunting: detection engineering with Sigma/YARA, SIEM query design, and validation of incident detections against known technique patterns.
accessibility affaan-m/ECC · score 63/100 (grade D)
Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android — semantic ARIA roles and labels, accessibility traits and hints, focus management, contrast, target size, and screen-reader support. Use when building or auditing UI for accessibility compliance, keyboard navigation, or screen-reader support.
accessibility affaan-m/everything-claude-code · score 63/100 (grade D)
Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android — semantic ARIA roles and labels, accessibility traits and hints, focus management, contrast, target size, and screen-reader support. Use when building or auditing UI for accessibility compliance, keyboard navigation, or screen-reader support.
ai-seo coreyhaines31/marketingskills · score 63/100 (grade D)
When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'llms-full.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' 'agent-readable site,' 'agent readiness,' 'is my site agent-ready,' 'WebMCP,' 'do listicles still work for AI,' 'ChatGPT stopped citing comparison pages,' 'how do LLMs see our brand,' 'LinkedIn for AEO,' or 'AI citation format shift.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.
bio-crispr-screens-copy-number-correction GPTomics/bioSkills · score 63/100 (grade D)
Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.
bio-data-visualization-dimensionality-reduction-plots GPTomics/bioSkills · score 63/100 (grade D)
Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.
bio-data-visualization-network-visualization GPTomics/bioSkills · score 63/100 (grade D)
Visualize biological networks (PPI, gene-regulatory, co-expression, pathway) with layout algorithm choice (ForceAtlas2, Fruchterman-Reingold, Kamada-Kawai, hive plots), edge bundling, community-based coloring, and reproducible seeds using NetworkX, PyVis, igraph, and Cytoscape automation. Use when rendering biological networks for static publication, interactive HTML exploration, or Cytoscape-format export.
bio-experimental-design-batch-design GPTomics/bioSkills · score 63/100 (grade D)
Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.
bio-metabolomics-isotope-tracing GPTomics/bioSkills · score 63/100 (grade D)
Designs and analyzes stable-isotope-resolved metabolomics (SIRM / isotope tracing / fluxomics) experiments that measure metabolic ACTIVITY via 13C/15N/2H tracers, distinct from steady-state pool profiling. Covers tracer choice, isotopologue vs isotopomer, mass-isotopomer distributions (MID), fractional enrichment, the mandatory natural-abundance + tracer-purity correction (IsoCor, AccuCor), and the metabolic/isotopic steady-state vs non-stationary (INST-MFA) distinction. Use when feeding a labeled tracer and interpreting labeling patterns, correcting raw isotopologue intensities, computing or plotting an MID, or deciding tracing vs abundance profiling. For absolute pool concentration and MRM mechanics see metabolomics/targeted-analysis; for constraint-based genome-scale flux (FBA, not empirical tracing) see systems-biology/flux-balance-analysis; for feature detection see metabolomics/xcms-preprocessing; for pathway enrichment that ignores the pool-vs-flux caveat see metabolomics/pathway-mapping.
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-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.
fabric-lakehouse github/awesome-copilot · score 63/100 (grade D)
Use this skill to get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using best practices.
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".
ib-check-deck anthropics/financial-services · score 63/100 (grade D)
Investment banking presentation quality checker. Reviews a pitch deck or client-ready presentation for (1) number consistency across slides, (2) data-narrative alignment, (3) language polish against IB standards, (4) visual and formatting QC. Use whenever the user asks to review, check, QC, proof, or do a final pass on a deck, pitch, or client materials — including requests like "check my numbers", "reconcile figures across slides", "is this client-ready", or "what am I missing before I send this out".
jpa-patterns affaan-m/ECC · score 63/100 (grade D)
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot. Use when designing JPA entities or relationships, or when a Hibernate query, transaction, or N+1 problem needs fixing.
jpa-patterns affaan-m/everything-claude-code · score 63/100 (grade D)
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot. Use when designing JPA entities or relationships, or when a Hibernate query, transaction, or N+1 problem needs fixing.
premium-frontend-ui github/awesome-copilot · score 63/100 (grade D)
A comprehensive guide for GitHub Copilot to craft immersive, high-performance web experiences with advanced motion, typography, and architectural craftsmanship.
prisma-patterns affaan-m/ECC · score 63/100 (grade D)
Prisma ORM patterns for TypeScript backends — schema design, query optimization, transactions, pagination, and critical traps like updateMany returning count not records, $transaction timeouts, migrate dev resetting the DB, @updatedAt skipped on bulk writes, and serverless connection exhaustion. Use when writing a Prisma schema or query, or debugging transactions, migrations, or serverless connection limits.
prisma-patterns affaan-m/everything-claude-code · score 63/100 (grade D)
Prisma ORM patterns for TypeScript backends — schema design, query optimization, transactions, pagination, and critical traps like updateMany returning count not records, $transaction timeouts, migrate dev resetting the DB, @updatedAt skipped on bulk writes, and serverless connection exhaustion. Use when writing a Prisma schema or query, or debugging transactions, migrations, or serverless connection limits.
threejs-game-ui-designer majidmanzarpour/threejs-game-skills · score 63/100 (grade D)
Design premium Three.js game UI: HUDs, menus, overlays, pause/win/lose screens, settings, icon controls, touch UI, typography, responsive layout, safe areas, text fit, and UI/world cohesion.
ui-ux-pro-max Galaxy-Dawn/claude-scholar · score 63/100 (grade D)
This skill should be used when the user asks to design or review a UI, create a landing page or dashboard, choose colors or typography, improve accessibility, or implement polished frontend interfaces with a clear design system.
web-to-app-funnel Eronred/aso-skills · score 63/100 (grade D)
When the user wants to design or optimize the funnel that takes web visitors into installing and onboarding the app — including smart app banners, web-to-app deep links, deferred deep links, web onboarding (Stripe-paid web flow before app install), QR codes, "open in app" CTAs, and the trade-off between paying on web vs in-app. Use when the user mentions "web to app", "smart app banner", "Stripe before app", "web paywall before install", "Branch web SDK", "web funnel for app", "AppsFlyer OneLink web", "Universal Links", "App Links", "QR code to app", "open in app", "deferred deep link from web", or "should I sell on web first then push to app". For pure in-app onboarding, see onboarding-optimization. For deep link infra, see attribution-setup.
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.
animation-vocabulary emilkowalski/skills · score 62/100 (grade D)
Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.
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-data-visualization-lollipop-protein-maps GPTomics/bioSkills · score 62/100 (grade D)
Plot per-gene mutation distributions on a protein-domain map (lollipop / needle plots) showing mutation position, recurrence count, and variant classification with maftools, g3-lollipop, trackViewer, and ProteinPaint. Use when visualizing recurrent mutation hotspots on a single gene's protein, marking domain boundaries from UniProt/Pfam, comparing missense vs truncating distributions, or contrasting two cohorts on the same lollipop.
bio-epitranscriptomics-modification-visualization GPTomics/bioSkills · score 62/100 (grade D)
Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot; MetaPlotR; deepTools computeMatrix scale-regions), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (log2 IP/input bigWig via deepTools bamCompare; pyGenomeTracks; Gviz; IGV/UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), feature-distribution stacked bars, and volcano/MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012; Meyer 2012). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features, generating DRACH motif logos as sanity checks, rendering volcano plots of differential m6A, or reproducing the stop-codon enrichment plot.
bio-genome-engineering-hdr-template-design GPTomics/bioSkills · score 62/100 (grade D)
Designs donor/repair templates for precise CRISPR knock-ins -- choosing the format (ssODN, long-ssDNA/Easi-CRISPR, dsDNA/plasmid, AAV6), sizing homology arms, placing the cut within ~10 bp of the edit, and adding a mandatory codon-checked blocking (PAM/seed) mutation so the edited allele is not re-cut. Frames the HDR-vs-NHEJ-vs-MMEJ pathway competition, the MMEJ (PITCh) and homology-independent (HITI/HMEJ) alternatives for post-mitotic cells, ssODN strand/asymmetry choice, phosphorothioate end-protection, and ranked HDR enhancers. Use when designing a donor for a point mutation, epitope/fluorophore tag, allele replacement, or knock-in, or when HDR efficiency is low. Guide design and base/prime editing are separate skills.
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).
brand-guidelines ComposioHQ/awesome-claude-skills · score 62/100 (grade D)
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
brand-guidelines anthropics/skills · score 62/100 (grade D)
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
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",...}).
offers coreyhaines31/marketingskills · score 62/100 (grade D)
When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.
product-strategist alirezarezvani/claude-skills · score 62/100 (grade D)
Strategic product leadership toolkit for Head of Product covering OKR cascade generation, quarterly planning, competitive landscape analysis, product vision documents, and team scaling proposals. Use when creating quarterly OKR documents, defining product goals or KPIs, building product roadmaps, running competitive analysis, drafting team structure or hiring plans, aligning product strategy across engineering and design, or generating cascaded goal hierarchies from company to team level.
site-architecture coreyhaines31/marketingskills · score 62/100 (grade D)
When the user wants to plan, map, or restructure their website's page hierarchy, navigation, URL structure, or internal linking. Also use when the user mentions "sitemap," "site map," "visual sitemap," "site structure," "page hierarchy," "information architecture," "IA," "navigation design," "URL structure," "breadcrumbs," "internal linking strategy," "website planning," "what pages do I need," "how should I organize my site," "site navigation," "which website builder should I use," "migrate my website," or "add a blog to my existing site." Use this whenever someone is planning what pages a website should have, how they connect, and where to build them. NOT for XML sitemaps (that's technical SEO — see seo-audit). For SEO audits, see seo-audit. For structured data, see schema.
agentic-workflows github/awesome-copilot · score 61/100 (grade D)
Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
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-chipseq-chromatin-state-segmentation GPTomics/bioSkills · score 61/100 (grade D)
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
bio-data-visualization-color-palettes GPTomics/bioSkills · score 61/100 (grade D)
Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.
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-epitranscriptomics-merip-preprocessing GPTomics/bioSkills · score 61/100 (grade D)
Aligns and QCs methylated-RNA-immunoprecipitation (MeRIP / m6A-seq) IP and input libraries using STAR or HISAT2 splice-aware mapping, samtools sort/index, IP/input matched-pair tracking, antibody-lot metadata recording, replicate concordance via deepTools multiBamSummary + plotCorrelation, IP enrichment QC via plotFingerprint and per-transcript IP/input ratio distributions, library-complexity saturation curves via PreSeq, and the explicit do-NOT-deduplicate convention for standard non-UMI MeRIP. Use when preparing paired IP and input BAM files for exomePeak2 / MeTPeak / MACS3 peak calling, evaluating MeRIP replicate concordance and IP enrichment, deciding whether to deduplicate (standard MeRIP typically NOT), choosing genome-vs-transcriptome alignment for downstream peak vs m6Anet workflows, recording antibody clone and lot metadata for cross-batch reconciliation, detecting failed IPs via saturation curves and IP/input distribution shape, or generating IP-over-Input bigWig tracks for visualisation.
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-engineering-prime-editing-design GPTomics/bioSkills · score 61/100 (grade D)
Designs pegRNAs and nicking guides for prime editing (PE) -- choosing the nick/strand, tuning the primer-binding site (PBS) and reverse-transcription template (RTT) as a per-locus panel, selecting the PE system (PE2/PE3/PE3b/PE4/PE5/PEmax/PE7), adding MMR-evading and PAM-disrupting silent edits, appending epegRNA 3' motifs (tevopreQ1/mpknot), and ranking with PRIDICT/DeepPrime. Covers twinPE/PASTE for large insertions and the prime-vs-base-editing decision. Use when designing a scarless point mutation, small insertion/deletion, or any of the 12 base conversions without a double-strand break, when efficiency is low and MMR inhibition or pegRNA stabilization is needed, or when routing a large insertion to an integrase method. Generic guide scoring and base editing are separate skills.
bio-pathway-enrichment-visualization GPTomics/bioSkills · score 61/100 (grade D)
Turns an enrichResult or gseaResult from clusterProfiler/enrichplot into a figure that collapses or shows gene-set redundancy, using dotplot, barplot, cnetplot, emapplot, treeplot, ridgeplot, gseaplot2, and upsetplot. Covers why a default top-20 GO dotplot is one biological theme drawn twenty times (the DAG/nesting guarantees redundant overlapping terms), so the figure is a modeling choice between SHOWING redundancy (pairwise_termsim -> emapplot/treeplot) and DELETING it (simplify/REVIGO); why cnetplot/emapplot/treeplot need pairwise_termsim first; why enrichplot ships no barplot for gseaResult (a bar cannot carry a signed NES); why GeneRatio is not fold enrichment; and why showCategory silently truncates. Use when plotting ORA or GSEA results, collapsing redundant GO terms visually, encoding a dotplot, or building a publication enrichment figure. Statistics come from go-enrichment and gsea; generic ggplot -> data-visualization/ggplot2-fundamentals.
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-single-cell-batch-integration GPTomics/bioSkills · score 61/100 (grade D)
Integrate multiple scRNA-seq samples or batches with Harmony, scVI/scANVI, Seurat (CCA/RPCA), fastMNN, Scanorama, or BBKNN. Resolves which method to use for the dataset size and design, how strongly to correct, when integration is the wrong move (confounded batch/biology), how to score integration with scIB metrics without gaming them, and why corrected expression must not be used for differential expression. Use when integrating batches or datasets, choosing an integration method, diagnosing over-correction, or judging integration quality.
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.
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.
google-cloud-global-frontend-configuration google/skills · score 61/100 (grade D)
Guides agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
hyperframes-registry heygen-com/hyperframes · score 61/100 (grade D)
About 450 ready-made HyperFrames blocks and components installed as editable source - transitions, overlays, titles, kinetic type, captions, charts, map overlays, 3D, camera moves. Use it before hand-building any named visual (CRT scanlines, glitch, film grain, a chart); also for hyperframes add and catalog.
make-interfaces-feel-better affaan-m/ECC · score 61/100 (grade D)
Apply concrete design-engineering details that make interfaces feel polished. Use when reviewing or improving UI spacing, typography, borders, shadows, motion, hit areas, icons, text wrapping, and interaction states.
make-interfaces-feel-better affaan-m/everything-claude-code · score 61/100 (grade D)
Apply concrete design-engineering details that make interfaces feel polished. Use when reviewing or improving UI spacing, typography, borders, shadows, motion, hit areas, icons, text wrapping, and interaction states.
obsidian-kb-artifacts Galaxy-Dawn/claude-scholar · score 61/100 (grade D)
Use this skill for Obsidian-native formatting and derived artifacts such as Markdown formatting, wikilinks, registry tables, canvas files, optional Bases, CLI operations, and link repair. This skill does not decide knowledge routing.
slides nextlevelbuilder/ui-ux-pro-max-skill · score 61/100 (grade D)
Create strategic HTML presentations with Chart.js, design tokens, responsive layouts, copywriting formulas, and contextual slide strategies.
subscription-lifecycle Eronred/aso-skills · score 61/100 (grade D)
When the user wants to optimize their subscription business end-to-end — from trial start through renewal, cancellation, and win-back. Use when the user mentions "subscription lifecycle", "trial conversion", "churn", "cancellation", "win-back", "lapsed subscribers", "dunning", "billing retry", "grace period", "renewal rate", "subscriber LTV", or "resubscribe". For paywall design and pricing strategy, see monetization-strategy. For subscription analytics dashboards, see app-analytics.
bio-clinical-biostatistics-power-sample-size GPTomics/bioSkills · score 60/100 (grade D)
Computes sample size and power for clinical trials including continuous, binary, and time-to-event endpoints; superiority, non-inferiority, and equivalence designs; FDA 2016 non-inferiority margin selection with M1/M2 framework; Schoenfeld 1981 and Lakatos 1988 for survival; Schuirmann TOST and 80-125% bioequivalence; minimum clinically important difference (MCID) vs δ distinction. Use when justifying trial size in protocol or SAP per CONSORT 2025 item 16a.
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.
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.
daily-focus-board github/awesome-copilot · score 60/100 (grade D)
Spin up a personal, motivating daily focus board that renders in a browser canvas and that the user drives by talking to their AI partner. Tasks track status (to-do → in progress → done) with timestamped progress notes and roll up into a "today''s momentum" feed; numeric-goal tasks (pages, pomodoros, reps) render as progress-bar counters. Executive-function / neurodivergent-friendly by design: Focus mode, kind "not today" carryover (no overdue-shaming), a brain-dump box, reduced-motion, and gentle deadline countdowns. Add, reorder, and relabel tasks live, assign Eisenhower priority (Do first / Schedule / Delegate / Later), open with an above/below-the-line check-in and a daily mantra, and save an end-of-day recap. Use when someone wants to plan their day, stay focused, kick off a work session, or track progress. Progress persists in the browser (localStorage).
persona alirezarezvani/claude-skills · score 60/100 (grade D)
Generate data-driven user personas for UX research and product design. Usage: /persona generate [options]
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).
bio-clinical-biostatistics-adaptive-designs GPTomics/bioSkills · score 59/100 (grade D)
Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.
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-data-visualization-distribution-plots GPTomics/bioSkills · score 59/100 (grade D)
Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and N-aware encoding choices. Use when comparing distributions across a small number of groups — expression per cluster, biomarker per arm, scores per condition — and the bar-of-mean default is misleading.
bio-epidemiological-genomics-variant-surveillance GPTomics/bioSkills · score 59/100 (grade D)
Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
bio-genome-engineering-base-editing-design GPTomics/bioSkills · score 59/100 (grade D)
Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors are separate skills.
design-system affaan-m/ECC · score 59/100 (grade D)
Generate a design system from an existing codebase or audit one for visual consistency: extract tokens (colors, typography, spacing, shadows) into design-tokens.json and CSS custom properties with DESIGN.md rationale and an interactive HTML preview, score the UI across 10 dimensions, and flag AI-slop patterns. Use when starting a design system, auditing visual consistency before a redesign, or reviewing a PR that touches styling.
design-system affaan-m/everything-claude-code · score 59/100 (grade D)
Generate a design system from an existing codebase or audit one for visual consistency: extract tokens (colors, typography, spacing, shadows) into design-tokens.json and CSS custom properties with DESIGN.md rationale and an interactive HTML preview, score the UI across 10 dimensions, and flag AI-slop patterns. Use when starting a design system, auditing visual consistency before a redesign, or reviewing a PR that touches styling.
liquid-glass-design affaan-m/ECC · score 59/100 (grade D)
iOS 26 Liquid Glass design system — dynamic glass material with blur, reflection, and interactive morphing for SwiftUI, UIKit, and WidgetKit. Use when building iOS 26 Liquid Glass UI in SwiftUI, UIKit, or WidgetKit.
liquid-glass-design affaan-m/everything-claude-code · score 59/100 (grade D)
iOS 26 Liquid Glass design system — dynamic glass material with blur, reflection, and interactive morphing for SwiftUI, UIKit, and WidgetKit. Use when building iOS 26 Liquid Glass UI in SwiftUI, UIKit, or WidgetKit.
media-use heygen-com/hyperframes · score 59/100 (grade D)
Get or make any media for a HyperFrames video - music, sound effects, images, icons, logos, voiceover, avatar and generated video, transcripts, cutouts, colour grades and looks - with HeyGen or free local tools, and mix placed audio. Also for footage that looks dark, flat or dull, or should be stylized or hidden.
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.
teaser anthropics/financial-services · score 59/100 (grade D)
Draft anonymous one-page company teasers for sell-side M&A processes. Creates a compelling summary without revealing the company's identity, designed to gauge buyer interest before NDA execution. Triggers on "teaser", "blind teaser", "anonymous profile", "one-pager for process", or "draft teaser for sell-side".
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.
customer-journey Illyism/seo-skills · score 58/100 (grade D)
Map how customers discover, evaluate, and choose a product across Google, AI chatbots (ChatGPT, Claude, Perplexity), and social platforms, using the 5-stage awareness journey. Use when the user asks about search intent, AI SEO prompts, discoverability, buyer journeys, awareness stages, or what content to create for a brand, website, or keyword list.
frost-sequence-camera-orbit heygen-com/hyperframes · score 58/100 (grade D)
An orbiting camera follows an ice logo as it breaks apart, reforms into two text moments, and fades. HyperFrames block, 1920×1080, 22.5s, 216 variables.
swift-actor-persistence affaan-m/ECC · score 58/100 (grade D)
Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design. Use when persisting data in Swift and a data race or thread-safety problem needs designing out.
swift-actor-persistence affaan-m/everything-claude-code · score 58/100 (grade D)
Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design. Use when persisting data in Swift and a data race or thread-safety problem needs designing out.
bio-clinical-biostatistics-bayesian-trials GPTomics/bioSkills · score 57/100 (grade D)
Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.
llm-cost-optimizer alirezarezvani/claude-skills · score 57/100 (grade D)
Use proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize token usage', 'which model should I use', 'LLM spend is out of control', 'implement prompt caching', 'we're about to launch an AI feature', 'build me an AI endpoint'. Don't wait for an explicit cost complaint -- if someone is building an AI feature, designing an LLM endpoint, or choosing between models, cost architecture belongs in the conversation. Apply immediately when any of these are true: a system prompt appears that exceeds a few hundred tokens, all requests are hitting the same model, max_tokens is not set, or no per-feature cost logging exists. NOT for RAG pipeline design (use rag-architect). NOT for improving prompt quality or effectiveness (use senior-prompt-engineer).
openclaw-persona-forge affaan-m/ECC · score 57/100 (grade D)
为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡，输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。如当前环境提供已审核的生图 skill，可自动生成统一风格头像图片。当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。不适用于：微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。触发词：龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。 Use when creating, designing, or customizing an OpenClaw lobster persona — identity, SOUL.md, name, or avatar prompt.
openclaw-persona-forge affaan-m/everything-claude-code · score 57/100 (grade D)
为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡，输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。如当前环境提供已审核的生图 skill，可自动生成统一风格头像图片。当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。不适用于：微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。触发词：龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。 Use when creating, designing, or customizing an OpenClaw lobster persona — identity, SOUL.md, name, or avatar prompt.
threejs-postprocessing cloudai-x/threejs-skills · score 57/100 (grade D)
Three.js post-processing: composer pass chains, built-in renderer effects, and the WebGPU/TSL node pipeline — bloom, depth of field, ambient occlusion, custom screen effects. Use when adding visual effects, color grading, blur, glow, or screen-space shaders, on WebGL or with WebGPU and TSL.
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.
bio-structural-biology-structure-modification GPTomics/bioSkills · score 55/100 (grade D)
Modifies protein structures in place with Biopython Bio.PDB - transforms coordinates, strips waters/heteroatoms, overloads the B-factor column, renumbers, and builds entities. Use when applying a rotation matrix and needing to know whether it is row-convention (Entity.transform, Superimposer) or column-convention (REMARK 350 / _pdbx_struct_oper_list assembly operators) so geometry is not silently mirrored; when overloading B-factors with pLDDT/conservation for coloring and needing to preserve the destroyed originals; when stripping solvent by HETFLAG (r.id[0]) rather than residue name so catalytic metals and cofactors survive; and when building or copying entities through StructureBuilder/Select without breaking SMCRA parent-child links or the (hetflag, resseq, icode) id tuple. Keywords transform, rotation matrix, occupancy, assembly operators.
chaos-experiment alirezarezvani/claude-skills · score 55/100 (grade D)
Interactive wizard to design and validate a chaos engineering experiment
color-font-skill MiniMax-AI/skills · score 55/100 (grade D)
Choose presentation-ready color palettes and font pairings for PPT/design tasks. Use when users ask for visual theme choices, brand-safe palettes, or font recommendations. Triggers include: 配色, 色板, 字体, color palette, font, PPT配色, 字体搭配.
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.
slo-design alirezarezvani/claude-skills · score 55/100 (grade D)
Interactive wizard to design an SLO with SLI, target, error budget, and burn-rate alerts
Content Strategist alirezarezvani/claude-skills · score 54/100 (grade D)
Builds content engines that rank, convert, and compound. Thinks in systems — topic clusters, not individual posts. Every piece earns its place or gets killed. Use when content needs to behave like a system rather than a stream of posts — e.g., designing a topic-cluster plan to grow organic traffic from zero, or auditing an editorial calendar and killing pieces that don't convert after 90 days. (For single-asset, on-brand copy production, see cs-content-creator.)
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.
design-style-skill MiniMax-AI/skills · score 54/100 (grade D)
Select a consistent visual design system for PPT slides using radius/spacing style recipes. Use when users ask for overall style direction or component styling consistency. Includes Sharp/Soft/Rounded/Pill recipes, component mappings, typography/spacing rules, and mixing guidance. Triggers: 风格, style, radius, spacing, 圆角, 间距, PPT风格, 视觉风格, design style, component style.
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".
oversized-cursor heygen-com/hyperframes · score 54/100 (grade D)
House-style oversized macOS cursor technique for HyperFrames launch videos. Load whenever a scene involves cursors or a pointer-led action, when kicking off a UI scene, when igniting a morph/transition/typing run with a click, or when a scene reads as static, dead, or stale and needs a cheap high-yield source of motion to carry the viewer's eye and segment them out of the stale state. Covers cursor size/look (incl. brand-motif cursors), the off-screen entry law, tip-targeting and the click tap, click-ignites-the-next-beat, and exit / cross-scene handoff.
taste affaan-m/ECC · score 54/100 (grade D)
Creative-direction layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop family — a named-genre aesthetic vocabulary, mood + color + light system, beat-synced editing grammar, and a pipeline chaining ECC's video skills from b-roll generation to distribution. Use when a video must feel intentional rather than merely functional — music videos, fancams, moodboard-driven reels, or giving AI-generated b-roll a coherent visual direction.
taste affaan-m/everything-claude-code · score 54/100 (grade D)
Creative-direction layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop family — a named-genre aesthetic vocabulary, mood + color + light system, beat-synced editing grammar, and a pipeline chaining ECC's video skills from b-roll generation to distribution. Use when a video must feel intentional rather than merely functional — music videos, fancams, moodboard-driven reels, or giving AI-generated b-roll a coherent visual direction.
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.
designs davidondrej/skills · score 47/100 (grade F)
Show 4 better, new design options as separate real image renders. Use for "designs" or when the user asks for new design ideas.
grill-me mattpocock/skills · score 42/100 (grade F)
A relentless interview to sharpen a plan or design.
grill-with-docs mattpocock/skills · score 42/100 (grade F)
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.