IN

investigation

Creates a dated scratch directory with a template README to document code tracing, architecture analysis, and feasibility studies.

Install

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

Installs to .claude/skills/investigation

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

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.
609 chars · catalog description✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Beginner

Key capabilities

  • Scaffold dated investigation folders in scratch/
  • Initialize standard README templates with task checklists
  • Document call stack tracing for complex code paths
  • Facilitate empirical research for system architecture archeology
  • Break down multi-repo bug investigations into actionable task lists

How it works

It generates a filesystem structure and boilerplate documentation based on a dated folder template to force methodical tracking of findings.

Inputs & outputs

You give it
Request to trace a complex flow, document architecture, or solve a multi-layered bug
You get back
Organized directory with a scaffolded README tracker

When to use investigation

  • Tracing complex code paths
  • Documenting system architecture
  • Investigating bug root causes

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

When not to use it

  • Simple coding questions that require a quick fix
  • Single-file modifications or basic debugging

Prerequisites

pythonuv

Limitations

  • Requires manual effort to keep the README updated
  • Not intended for tasks that do not require multi-step documentation

How it compares

It forces an empirical, documentation-first approach for complex tasks instead of diving directly into code changes.

Compared to similar skills

investigation side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
investigation (this skill)37moReviewBeginner
react-expert86moReviewAdvanced
rust-learner86moReviewBeginner
cartographer36moReviewIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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