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Found 32 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.
Initialize Navigator documentation structure in a project. Auto-invokes when user says "Initialize Navigator", "Set up Navigator", "Create Navigator structure", or "Bootstrap Navigator".
TDD enforcement during implementation. Reads `tdd:` setting from CLAUDE.md. Modes - strict (human approval for escape), soft (warnings), off (disabled). Auto-invoked by /implement.
JSON Hygiene Agent. Detects duplicate keys in JSON configuration files that might be silently ignored by standard parsers. Auto-invoked for JSON audits or manifest validation. V2 includes L5 Delegated Constraint Verification.
ADR management skill. Auto-invoked for generating architecture decisions, documenting design rationale, and maintaining the decision record log. Uses native read/write tools to scaffold and update ADR markdown files.