Agent skill · AI & Agents

acquire-codebase-knowledge

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

GitHub68,948★ · +463/wk · 2 repos on radarProfile →
copilotships scriptsMIT
Install
npx skills add github/awesome-copilot --skill acquire-codebase-knowledge --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

Facts
Files in the skill folder: 11
SKILL.md size: 9 KB
Bundled scripts: yes
Version: 1.3
Requires: Cross-platform. Requires Python 3.8+ and git. Run scripts/scan.py from the target project root.
Path: skills/acquire-codebase-knowledge/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 37,432 · +281 this week
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Acquire Codebase Knowledge Produces seven populated documents in `docs/codebase/` covering everything needed to work effectively on the project. Only document what is verifiable from files or terminal output — never infer or assume. ## Output Contract (Required) Before finishing, all of the following must be true: 1. Exactly these files exist in `docs/codebase/`: `STACK.md`, `STRUCTURE.md`, `ARCHITECTURE.md`, `CONVENTIONS.md`, `INTEGRATIONS.md`, `TESTING.md`, `CONCERNS.md`. 2. Every claim is traceable to source files, config, or terminal output. 3. Unknowns are marked as `[TODO]`; intent-dependent decisions are marked `[ASK USER]`. 4. Every document includes a short "evidence" list with concrete file paths. 5. Final response includes numbered `[ASK USER]` questions and intent-vs-reality divergences. ## Workflow Copy and track this checklist: ``` - [ ] Phase 1: Run scan, read intent documents - [ ] Phase 2: Investigate each documentation area - [ ] Phase 3: Populate all seven docs in docs/codebase/ - [ ] Phase 4: Validate docs, present findings, resolve all [ASK USER] items ``` ## Focus Area Mode If the user supplies a focus area (for example: "architecture only" or "testing and c

What's inside
Steps it walks through
  1. Output Contract (Required)
  2. Workflow
  3. Focus Area Mode
  4. Phase 1: Scan and Read Intent
  5. Phase 2: Investigate
  6. Phase 3: Populate Templates
  7. Phase 4: Validate, Repair, Verify
  8. Gotchas
  9. Anti-Patterns
  10. Enhanced Scan Output Sections
  11. Bundled Assets
Ships with 10 files
  • assets/templates/ARCHITECTURE.md
  • assets/templates/CONCERNS.md
  • assets/templates/CONVENTIONS.md
  • assets/templates/INTEGRATIONS.md
  • assets/templates/STACK.md
  • assets/templates/STRUCTURE.md
  • assets/templates/TESTING.md
  • references/inquiry-checkpoints.md
  • references/stack-detection.md
  • scripts/scan.py
Commands it runs
python3 "$SKILL_ROOT/scripts/scan.py" --output docs/codebase/.codebase-scan.txt
python3 /absolute/path/to/skills/acquire-codebase-knowledge/scripts/scan.py --output docs/codebase/.codebase-scan.txt
More from awesome-copilot
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About this skill
What does the acquire-codebase-knowledge skill do?

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

How do I install it?

Run `npx skills add github/awesome-copilot --skill acquire-codebase-knowledge --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going