investigation

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Scaffolds a structured investigation in scratch/ for empirical research and documentation. Use when the user says "start an investigation" or wants to: trace code paths or data flow ("trace from X to Y", "what touches X", "follow the wiring"), document system architecture comprehensively ("document how the system works", "archeology"), investigate bugs ("figure out why X happens"), explore technical feasibility ("can we do X?"), or explore design options ("explore the API", "gather context", "design alternatives"). Creates dated folder with README. NOT for simple code questions or single-file searches.

Install

mkdir -p .claude/skills/investigation && curl -L -o skill.zip "https://mcp.directory/api/skills/download/6410" && unzip -o skill.zip -d .claude/skills/investigation && rm skill.zip

Installs to .claude/skills/investigation

About this skill

Set up an investigation

Instructions

  1. Create a folder in {REPO_ROOT}/scratch/ with the format {YYYY-MM-DD}-{descriptive-name}:
    mkdir scratch/$(uv run python -c "import datetime; print(datetime.date.today().isoformat())")-{descriptive-name}
    
  2. Create a README.md in this folder with: task description, background context, task checklist. Update with findings as you progress.
  3. Create scripts and data files as needed for empirical work.
  4. For complex investigations, split into sub-documents as patterns emerge.

Investigation Patterns

These are common patterns, not rigid categories. Most investigations blend multiple patterns.

Tracing - "trace from X to Y", "what touches X", "follow the wiring"

  • Follow call stack or data flow from a focal component to its connections
  • Can trace forward (X → where does it go?) or backward (what leads to X?)
  • Useful for: assessing impact of changes, understanding coupling

System Architecture Archeology - "document how the system works", "archeology"

  • Comprehensive documentation of an entire system or flow for reusable reference
  • Start from entry points, trace through all layers, document relationships exhaustively
  • For complex systems, consider numbered sub-documents (01-cli.md, 02-data.md, etc.)

Bug Investigation - "figure out why X happens", "this is broken"

  • Reproduce → trace root cause → propose fix
  • For cross-repo bugs, consider per-repo task breakdowns

Technical Exploration - "can we do X?", "is this possible?", "figure out how to"

  • Feasibility testing with proof-of-concept scripts
  • Document what works AND what doesn't

Design Research - "explore the API", "gather context", "design alternatives"

  • Understand systems and constraints before building
  • Compare alternatives, document trade-offs
  • Include visual artifacts (mockups, screenshots) when relevant
  • For iterative decisions, use numbered "Design Questions" (DQ1, DQ2...) to structure review

Best Practices

  • Use uv with inline dependencies for standalone scripts; for scripts importing local project code, use python directly (or uv run python if env not activated)
  • Use subagents for parallel exploration to save context
  • Write small scripts to explore APIs interactively
  • Generate figures/diagrams and reference inline in markdown
  • For web servers: npx serve -p 8080 --cors --no-clipboard &
  • For screenshots: use Playwright MCP for web, Qt's grab() for GUI
  • For external package API review: clone to scratch/repos/ for direct source access

Important: Scratch is Gitignored

The scratch/ directory is in .gitignore and will NOT be committed.

  • NEVER delete anything from scratch - it doesn't need cleanup
  • When distilling findings into PRs, include all relevant info inline
  • Copy key findings, code, and data directly into PR descriptions
  • PRs must be self-contained; don't reference scratch files

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