codebase-recon-skill
April 26, 2026 ยท View on GitHub
A coding agent skill that analyzes git history to understand a codebase before reading any code. Reveals project health, risk areas, team structure, and development momentum.
Inspired by "The Git Commands I Run Before Reading Any Code" by Ally Piechowski.
Installation
Via skills.sh (works with 20+ coding agents)
npx skills add yujiachen-y/codebase-recon-skill
Works with Claude Code, Cline, Cursor, GitHub Copilot, Gemini CLI, and any agent supporting the Agent Skills Specification.
Via Claude Code plugin system
/plugin marketplace add yujiachen-y/codebase-recon-skill
Then install the plugin from the marketplace browser via /plugin.
Via Codex plugin system
codex plugin marketplace add yujiachen-y/codebase-recon-skill
Then run /plugins in Codex, choose the Codebase Recon marketplace, and install codebase-recon.
Usage
In your coding agent, invoke:
/codebase-recon
The skill will:
- Probe the repo to determine its scale (small / medium / large)
- Analyze 7 dimensions in parallel: code hotspots, bus factor, bug magnets, team momentum, firefighting frequency, recently added files, and active contributors
- Cross-reference hotspots with bug magnets to identify high-risk files
- Report findings with actionable recommendations
What You'll Learn
| Dimension | Question Answered |
|---|---|
| Code Hotspots | Which files change the most? |
| Bug Magnets | Which files attract the most bug fixes? |
| High-Risk Files | Which files are both hot AND buggy? |
| Bus Factor | Who knows what? Is knowledge concentrated? |
| Team Momentum | Is development accelerating, stable, or declining? |
| Firefighting | How often are there emergency fixes and reverts? |
| Recently Added | Where is active development happening? |
Requirements
git(any version)- A git repository with commit history
Attribution
This skill is inspired by "The Git Commands I Run Before Reading Any Code" by Ally Piechowski. The original article describes 5 git commands for codebase reconnaissance. This skill extends the concept with auto-scaling, cross-referencing, and actionable recommendations.