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Agent skills

Skills you can use with AI coding agents, indexed from public GitHub repositories.

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workspace-calibration Analyze Linear workspace health and usage patterns before jumping into backlog work. Like a pre-flight check for a new PM joining a team or organization.
breethomas/bette-think 13
agent-workflow Expert system for designing and architecting AI agent workflows based on proven Meta methodologies. Use when users need to build AI agents, create agent workflows, solve problems using agentic systems, integrate multiple tools into agent architectures, or need guidance on agent design patterns. Helps translate business problems into structured agent solutions with clear scope, tool integration, and multi-layer architecture planning.
breethomas/bette-think 13
ai-cost-check Calculate AI feature costs and challenge if you actually need it. Invokes ai-cost-analyzer agent for detailed economics modeling.
breethomas/bette-think 13
context-engineering [ARCHIVED] Full 4D Context Canvas reference. For new AI features, use /spec --ai. For debugging, use /ai-debug. For quality checks, use /context-check.
breethomas/bette-think 13
generate-test-data Create diverse synthetic test inputs using dimension-based tuple generation. Use when bootstrapping an eval dataset, when real user data is sparse, or when stress-testing specific failure hypotheses. Do NOT use when you already have 100+ representative real traces (use stratified sampling instead).
breethomas/bette-think 13
build-judge Build an LLM-as-Judge evaluator for one specific failure mode. Binary pass/fail only. Use when a failure mode requires interpretation (tone, faithfulness, relevance, completeness) and cannot be checked with code. Do NOT use when the failure can be checked with regex, schema validation, or execution tests. Do NOT use before completing error analysis (/upgrade-evals).
breethomas/bette-think 13
upgrade-evals Systematic error analysis on real AI traces. Read traces, judge pass/fail, let failure categories emerge from data, compute failure rates, decide what to fix. Use when you have 50+ test cases or are seeing production failures. Do NOT use when you have fewer than 20 test cases (use /start-evals first).
breethomas/bette-think 13
eval-rag Evaluate RAG pipeline retrieval and generation quality separately. Measure Recall@k, Precision@k, MRR, NDCG@k for retrieval. Assess faithfulness and relevance for generation. Use when the AI feature uses retrieval (search, knowledge base, document QA). Do NOT use for non-RAG AI features.
breethomas/bette-think 13
council Run multi-LLM council for adversarial debate and cross-validation. Use it for implementation, architecture, review, security, research, and planning tasks with the canonical llm-council subagents and modes.
sherifkozman/the-llm-council 35
jbct-review Thorough parallel JBCT code review. Launches 10 focused reviewers plus aggregator for comprehensive compliance checking.
siy/coding-technology 13
JBCT Java Backend Coding Technology skill for designing, implementing, and reviewing functional Java backend code. Use when working with Result, Option, Promise types, value objects, use cases, or when asked about JBCT patterns, monadic composition, parse-don't-validate, structural patterns (Leaf, Sequencer, Fork-Join), or functional Java backend architecture.
siy/coding-technology 13
fix-all Fix ALL issues found in the preceding review. Thorough, relentless, complete.
siy/coding-technology 13
orchestrate-deployment Orchestrate deployment pipelines and infrastructure. Use when user says "deploy to staging", "set up CI/CD for this project", "configure deployment pipeline", "deploy to production with canary", or "rollback the last deployment".
Uniswap/ai-toolkit 30
setup-repository Interactive setup wizard for configuring any repository with Claude Code best practices. Use when user says "setup claude", "init claude", "configure claude code", "setup repository", "boris setup", "best practices setup", or wants to configure their repo for optimal AI-assisted development.
Uniswap/ai-toolkit 30
update-claude-docs Update CLAUDE.md documentation files after code changes. Use when user says "update the CLAUDE.md", "sync the docs with my changes", "document what I changed", "update documentation for this package", or after making significant code modifications that should be reflected in project documentation.
Uniswap/ai-toolkit 30
generate-document Generate professional documents in multiple formats (PDF, DOCX, HTML, ODT, EPUB, RTF). Use when the user says "make a PDF", "generate a report", "create a document", "export to Word", "make a Word doc", "convert to PDF", "export findings", "create documentation", or wants to save analysis results as a formatted document.
Uniswap/ai-toolkit 30
research-topic Research external documentation and best practices. Use when user says "look up the docs for this library", "research best practices for implementing caching", "how do other projects handle authentication", "check the official documentation for this API", "compare our implementation with industry standards", or "what's the recommended way to structure this".
Uniswap/ai-toolkit 30
generate-tests Generate comprehensive tests for code. Use when user says "write tests for this function", "add unit tests to this file", "generate integration tests for the API", "I need test coverage for this module", or "create e2e tests for the checkout flow".
Uniswap/ai-toolkit 30
optimize-prompt Optimize prompts for better AI performance. Use when user says "improve this prompt for better results", "optimize this prompt to reduce tokens", "apply prompt engineering best practices to this", "make this prompt more effective", "help me refine this system prompt", or "tune this prompt for the AI model I'm using".
Uniswap/ai-toolkit 30
analyze-code Comprehensive code explanation and analysis. Use when user says "explain this file to me", "what does this code do", "analyze the security of this module", "review the performance of this function", or "help me understand this architecture".
Uniswap/ai-toolkit 30
explore-codebase Explore and understand how the codebase works. Use when user asks "how does the authentication work", "where is the API endpoint defined", "show me how data flows through the system", "explain this module's architecture", "trace the request from controller to database", or "I need to understand this feature before making changes".
Uniswap/ai-toolkit 30
diagram-excalidraw Generate Excalidraw architecture diagrams from codebase analysis. Use when user says "create an architecture diagram", "visualize the system design", "generate an excalidraw diagram", "draw the component structure", "create a visual representation of the codebase", or "diagram the data flow".
Uniswap/ai-toolkit 30
analyze-tech-debt Analyze and prioritize technical debt with remediation plans. Use when user says "analyze the technical debt in this codebase", "what's the code quality like in this module", "identify what's slowing down our development", "assess the maintenance burden of this legacy code", "create a plan to pay down our tech debt", or "where should we focus our cleanup efforts".
Uniswap/ai-toolkit 30
refactor-code Refactor code with safety checks and pattern application. Use when user says "refactor this code", "clean up this function", "simplify this logic", "extract this into a separate function", "apply the strategy pattern here", "reduce the complexity of this module", or "reorganize this file structure".
Uniswap/ai-toolkit 30