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 rep
Install
Use withClaudeCursorCodex
The file stays in the publisher's repository. PlugMCP does not host or rewrite it.
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.
name: acquire-codebase-knowledge
description: '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.'
license: MIT
compatibility: 'Cross-platform. Requires Python 3.8+ and git. Run scripts/scan.py from the target project root.'
metadata:
version: "1.3"
enhancements:
- Multi-language manifest detection (25+ languages supported)
- CI/CD pipeline detection (10+ platforms)
- Container & orchestration detection
- Code metrics by language
- Security & compliance config detection
- Performance testing markers
argument-hint: 'Optional: specific area to focus on, e.g. "architecture only", "testing and concerns"'
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:
Exactly these files exist in docs/codebase/: STACK.md, STRUCTURE.md, ARCHITECTURE.md, CONVENTIONS.md, INTEGRATIONS.md, , .
TESTING.md
CONCERNS.md
Every claim is traceable to source files, config, or terminal output.
Unknowns are marked as [TODO]; intent-dependent decisions are marked [ASK USER].
Every document includes a short "evidence" list with concrete file paths.
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 concerns"):
Always run Phase 1 in full.
Fully complete focus-area documents first.
For non-focus documents not yet analyzed, keep required sections present and mark unknowns as [TODO].
Still run the Phase 4 validation loop on all seven documents before final output.
Search for PRD, TRD, README, ROADMAP, SPEC, DESIGN files and read them.
Summarise the stated project intent before reading any source code.
Phase 2: Investigate
Use the scan output to answer questions for each of the seven templates. Load references/inquiry-checkpoints.md for the full per-template question list.
If the stack is ambiguous (multiple manifest files, unfamiliar file types, no package.json), load references/stack-detection.md.
Phase 3: Populate Templates
Copy each template from assets/templates/ into docs/codebase/. Fill in this order:
STACK.md — language, runtime, frameworks, all dependencies
Use [TODO] for anything that cannot be determined from code. Use [ASK USER] where the right answer requires team intent.
Phase 4: Validate, Repair, Verify
Run this mandatory validation loop before finalizing:
Validate each doc against references/inquiry-checkpoints.md.
For each non-trivial claim, confirm at least one evidence reference exists.
If any required section is missing or unsupported:
Fix the document.
Re-run validation.
Repeat until all seven docs pass.
Then present a summary of all seven documents, list every [ASK USER] item as a numbered question, and highlight any Intent vs. Reality divergences from Phase 1.
Validation pass criteria:
No unsupported claims.
No empty required sections.
Unknowns use [TODO] rather than assumptions.
Team-intent gaps are explicitly marked [ASK USER].
Gotchas
Monorepos: Root package.json may have no source — check for workspaces, packages/, or apps/ directories. Each workspace may have independent dependencies and conventions. Map each sub-package separately.
Outdated README: README often describes intended architecture, not the current one. Cross-reference with actual file structure before treating any README claim as fact.
TypeScript path aliases:tsconfig.jsonpaths config means imports like @/foo don't map directly to the filesystem. Map aliases to real paths before documenting structure.
Generated/compiled output: Never document patterns from dist/, build/, generated/, .next/, out/, or __pycache__/. These are artefacts — document source conventions only.
.env.example reveals required config: Secrets are never committed. Read .env.example, .env.template, or .env.sample to discover required environment variables.
devDependencies ≠ production stack: Only dependencies (or equivalent, e.g. [tool.poetry.dependencies]) runs in production. Document linters, formatters, and test frameworks separately as dev tooling.
Test TODOs ≠ production debt: TODOs inside test/, tests/, __tests__/, or spec/ are coverage gaps, not production technical debt. Separate them in CONCERNS.md.
High-churn files = fragile areas: Files appearing most in recent git history have the highest modification rate and likely hidden complexity. Always note them in CONCERNS.md.
Anti-Patterns
❌ Don't
✅ Do instead
"Uses Clean Architecture with Domain/Data layers." (when no such directories exist)
State only what directory structure actually shows.
"This is a Next.js project." (without checking package.json)
Check dependencies first. State what's actually there.
Guess the database from a variable name like dbUrl
Check manifest for pg, mysql2, mongoose, prisma, etc.
Document dist/ or build/ naming patterns as conventions
Source files only.
Enhanced Scan Output Sections
The scan.py script now produce the following sections in addition to the original output:
CODE METRICS — Total files, lines of code by language, largest files (complexity signals)
Default mode: complete only the "Core Sections (Required)" in each template.
Extended mode: add optional sections only when the repo complexity justifies them.
How do I install acquire-codebase-knowledge?
Download skills/acquire-codebase-knowledge/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does acquire-codebase-knowledge live?
The publisher keeps it at https://github.com/github/awesome-copilot.
Which agents can use acquire-codebase-knowledge?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.