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Found 2,663 Skills
TDD-based code simplification that preserves behavior through tests. Use Red-Green-Refactor cycles to simplify code one test-verified change at a time. **DISTINCT FROM**: General code review or AI rewriting—this skill requires existing tests and only proceeds when tests confirm behavior is preserved. **PROACTIVE**: Auto-invoke when test-covered code has complexity (functions >50 lines, high cyclomatic complexity, duplication) and user wants to simplify it safely. Trigger phrases: 'clean up code', 'make code simpler', 'reduce complexity', 'refactoring help'. **NOT FOR**: Adding features or fixing bugs—use /tdd skill instead.
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.
Guide Test-Driven Development workflow (Red-Green-Refactor) for new features, bug fixes, and refactoring. Identifies test improvement opportunities and applies pytest best practices. Use when writing tests, implementing features, or following TDD methodology. **PROACTIVE ACTIVATION**: Auto-invoke when implementing features or fixing bugs in projects with test infrastructure (pytest files, tests/ directory). **DETECTION**: Check for tests/ directory, pytest.ini, pyproject.toml with pytest config, or test files. **USE CASES**: Writing production code, fixing bugs, adding features, legacy code characterization.
Creates system prompts, writes tool descriptions, and structures agent instructions for agentic systems. Use when the user asks to create, generate, or design prompts for AI agents, especially for tool-using agents, planning agents, or autonomous systems. **PROACTIVE ACTIVATION**: Auto-invoke when designing prompts for agents, tools, or agentic workflows in AI projects. **DETECTION**: Check for agent/tool-related code, prompt files, or user mentions of "prompt", "agent", "LLM". **USE CASES**: Designing system prompts, tool descriptions, agent instructions, prompt optimization, reducing hallucinations.
Google Optimization Tools. An open-source software suite for optimization, specialized in vehicle routing, flows, integer and linear programming, and constraint programming. Features the world-class CP-SAT solver. Use for vehicle routing problems (VRP), scheduling, bin packing, knapsack problems, linear programming (LP), integer programming (MIP), network flows, constraint programming, combinatorial optimization, resource allocation, shift scheduling, job-shop scheduling, and discrete optimization problems.
Creative problem-solving and ideation using SCAMPER, First Principles, Random Word, and AI-optimized techniques. Use when generating ideas, breaking creative blocks, brainstorming alternatives, or innovating.
REST API for optimized token swapping (including executable transaction generation), swap quoting, and pricing using the SushiSwap Aggregator. Use this skill when the user wants to: - Get a swap quote between two tokens on 40+ evm networks - Generate executable swap transaction data - Fetch token prices for a specific network or token - Retrieve token metadata - Discover supported AMM liquidity sources - Integrate SushiSwap swapping or pricing logic via HTTP/REST (and not the SushiSwap Javascript API)
Direct technical advisor mode for counting/estimation and architecture/design
Systematic competitive analysis for product positioning, sales enablement, and strategic planning. Use when the user wants to analyze competitors, build battlecards, create comparison pages, understand market positioning, or research competitive landscape. Also triggers on: 'competitor analysis,' 'competitive landscape,' 'battlecard,' 'win/loss analysis,' 'market positioning,' 'how do we compare to,' or 'what is [company] doing.'
Analyze and explain a pull request to help review it effectively
Reset the working directory for the next task by ensuring no uncommitted changes exist, then switching to the main branch and pulling latest.
Jujutsu (`jj`) is a Git-compatible version control system with a simpler mental model - no staging area, working copy is always a commit, and conflicts don't block operations. Use this skill for version control operations in `jj` repositories (which may be co-located with `git`) or when `jj` is called out specifically.