agents-md-creator
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refactor
TDD-based code refactoring preserving behavior through tests. Use Red-Green-Refactor cycles to apply refactoring patterns one test-verified change at a time. **TRIGGERS**: 'clean up code', 'make code simpler', 'reduce complexity', 'refactor this', 'apply DRY', 'extract method', 'remove duplication'. **DISTINCT FROM**: Adding features (use /tdd) or fixing bugs. **PROACTIVE**: Auto-invoke when test-covered code has complexity (functions >50 lines, high cyclomatic complexity, duplication).
16git-commit
Generate concise, descriptive git commit messages following best practices. Use when creating git commits from staged changes, crafting commit messages, or reviewing commit message quality. Use when the user says /commit or asks to create a git commit. **PROACTIVE ACTIVATION**: Auto-invoke when staged changes detected or user asks to commit/save work. **DETECTION**: Run git status - if staged changes exist, offer to commit. User says \"commit\", \"save\", \"done with feature\". **USE CASES**: Staged changes detected, work completed, user wants to save progress.
12create-pr
Creates GitHub pull requests with properly formatted titles, a body matching the project's PR template, and appropriate type/scope labels. Automatically creates labels if they don't exist. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request. **PROACTIVE ACTIVATION**: Auto-invoke when a branch has commits ahead of main and the user signals the work is ready. **DETECTION**: Run git log origin/main..HEAD - if commits exist and user signals readiness, offer to open a PR. User says \"open a PR\", \"ready for review\", \"this is done\", \"let's merge\", \"submit this\". **USE CASES**: Feature or fix complete, user finished a series of commits and mentions review or merging.
11prompt-engineering
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.
10copilot-sdk
Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications or integrating Copilot SDK. **DETECTION**: Check for @github/copilot-sdk imports, copilot dependencies in package.json/pyproject.toml/go.mod. **USE CASES**: Embedding agents in apps, creating custom tools, implementing streaming, managing sessions, connecting to MCP servers.
9phoenix-observability
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, monitoring production AI systems, or setting up observability infrastructure for agentic systems. **PROACTIVE ACTIVATION**: Auto-invoke when implementing observability/tracing for LLM agents, setting up evaluation pipelines, or configuring OpenTelemetry instrumentation. **DETECTION**: Check for arize-phoenix imports, OpenTelemetry setup, or observability-related code. **USE CASES**: Debugging LLM apps, running evaluations, monitoring production systems, setting up tracing infrastructure, instrumenting agent frameworks, tracing custom agents with decorators (@tracer.agent, @tracer.chain, @tracer.tool).
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