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Acquire Codebase Knowledge

GitHubOfficialFirst committed by SriSatyaLokeshDistributed by GitHub

  • Skill
  • Workflow
  • Software development
  • MIT
  • Low risk
  • Has scripts

From the author

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.
— the description by SriSatyaLokesh

From the skill’s files

Taken from the skill’s own files (its description, section headings and stated usage). Not an AutoGineer summary, and not written by the author as one.

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. 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.

What it does

  • Output Contract (Required)
  • Workflow
  • Focus Area Mode
  • Gotchas
  • Anti-Patterns
  • Enhanced Scan Output Sections

When to use 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".

Advantages

The skill’s files do not state this.

Usage examples

The skill’s files do not state this.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/github/acquire-codebase-knowledge/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip acquire-codebase-knowledge.zip -d .agents/skills

Documentation by SriSatyaLokesh

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 concerns"):

  1. Always run Phase 1 in full.

  2. Fully complete focus-area documents first.

  3. For non-focus documents not yet analyzed, keep required sections present and mark unknowns as [TODO].

  4. Still run the Phase 4 validation loop on all seven documents before final output.

Phase 1: Scan and Read Intent
  1. Run the scan script from the target project root:

    python3 "$SKILL_ROOT/scripts/scan.py" --output docs/codebase/.codebase-scan.txt

    Where $SKILL_ROOT is the absolute path to the skill folder. Works on Windows, macOS, and Linux.

    Quick start: If you have the path inline:

    python3 /absolute/path/to/skills/acquire-codebase-knowledge/scripts/scan.py --output docs/codebase/.codebase-scan.txt
  2. Search for PRD, TRD, README, ROADMAP, SPEC, DESIGN files and read them.

  3. 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:

  1. STACK.md — language, runtime, frameworks, all dependencies

  2. STRUCTURE.md — directory layout, entry points, key files

  3. ARCHITECTURE.md — layers, patterns, data flow

  4. CONVENTIONS.md — naming, formatting, error handling, imports

  5. INTEGRATIONS.md — external APIs, databases, auth, monitoring

  6. TESTING.md — frameworks, file organization, mocking strategy

  7. CONCERNS.md — tech debt, bugs, security risks, perf bottlenecks

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:

  1. Validate each doc against references/inquiry-checkpoints.md.

  2. For each non-trivial claim, confirm at least one evidence reference exists.

  3. If any required section is missing or unsupported:

  • Fix the document.

  • Re-run validation.

  1. 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.json paths 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 dbUrlCheck manifest for pg, mysql2, mongoose, prisma, etc.
Document dist/ or build/ naming patterns as conventionsSource 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)

  • CI/CD PIPELINES — Detected GitHub Actions, GitLab CI, Jenkins, CircleCI, etc.

  • CONTAINERS & ORCHESTRATION — Docker, Docker Compose, Kubernetes, Vagrant configs

  • SECURITY & COMPLIANCE — Snyk, Dependabot, SECURITY.md, SBOM, security policies

  • PERFORMANCE & TESTING — Benchmark configs, profiling markers, load testing tools

Use these sections during Phase 2 to inform investigation questions and identify tool-specific patterns.


Bundled Assets

AssetWhen to load
scripts/scan.pyPhase 1 — run first, before reading any code (Python 3.8+ required)
references/inquiry-checkpoints.mdPhase 2 — load for per-template investigation questions
references/stack-detection.mdPhase 2 — only if stack is ambiguous
assets/templates/STACK.mdPhase 3 step 1
assets/templates/STRUCTURE.mdPhase 3 step 2
assets/templates/ARCHITECTURE.mdPhase 3 step 3
assets/templates/CONVENTIONS.mdPhase 3 step 4
assets/templates/INTEGRATIONS.mdPhase 3 step 5
assets/templates/TESTING.mdPhase 3 step 6
assets/templates/CONCERNS.mdPhase 3 step 7

Template usage mode:

  • Default mode: complete only the "Core Sections (Required)" in each template.

  • Extended mode: add optional sections only when the repo complexity justifies them.

Files

references/stack-detection.md

Stack Detection Reference

Load this file when the tech stack is ambiguous — e.g., multiple manifest files present, unfamiliar file extensions, or no obvious package.json / go.mod.


Manifest File → Ecosystem

FileEcosystemKey fields to read
package.jsonNode.js / JavaScript / TypeScriptdependencies, devDependencies, scripts, main, type, engines
go.modGoModule path, Go version, require block
requirements.txtPython (pip)Package list with pinned versions
PipfilePython (pipenv)[packages], [dev-packages], [requires] python version
pyproject.tomlPython (poetry / uv / hatch)[tool.poetry.dependencies], [project], [build-system]
setup.py / setup.cfgPython (setuptools, legacy)install_requires, python_requires
Cargo.tomlRust[dependencies], [[bin]], [lib]
pom.xmlJava / Kotlin (Maven)<dependencies>, <artifactId>, <groupId>, <java.version>
build.gradle / build.gradle.ktsJava / Kotlin (Gradle)dependencies {}, sourceCompatibility
composer.jsonPHPrequire, require-dev
GemfileRubygem declarations, ruby version constraint
mix.exsElixirdeps/0, elixir: "~> X.Y"
pubspec.yamlDart / Flutterdependencies, dev_dependencies, environment.sdk
*.csproj.NET / C#<PackageReference>, <TargetFramework>
*.sln.NET solutionReferences multiple .csproj projects
deno.json / deno.jsoncDeno (TypeScript runtime)imports, tasks
bun.lockbBun (JavaScript runtime)Binary lockfile — check package.json for deps

Language Runtime Version Detection

LanguageWhere to find the version
Node.js.nvmrc, .node-version, engines.node in package.json, Docker FROM node:X
Python.python-version, pyproject.toml [requires-python], Docker FROM python:X
GoFirst line of go.mod (go 1.21)
Java<java.version> in pom.xml, sourceCompatibility in build.gradle, Docker FROM eclipse-temurin:X
Ruby.ruby-version, Gemfile ruby 'X.Y.Z'
Rustrust-toolchain.toml, rust-toolchain file
.NET<TargetFramework> in .csproj (e.g., net8.0)

Framework Detection (Node.js / TypeScript)

Dependency in package.jsonFramework
expressExpress.js (minimal HTTP server)
fastifyFastify (high-performance HTTP server)
nextNext.js (SSR/SSG React — check for pages/ or app/ directory)
nuxtNuxt.js (SSR/SSG Vue)
@nestjs/coreNestJS (opinionated Node.js framework with DI)
koaKoa (middleware-focused, no built-in router)
@hapi/hapiHapi
@trpc/servertRPC (type-safe API without REST/GraphQL schemas)
routing-controllersrouting-controllers (decorator-based Express wrapper)
typeormTypeORM (SQL ORM with decorators)
prismaPrisma (type-safe ORM, check prisma/schema.prisma)
mongooseMongoose (MongoDB ODM)
sequelizeSequelize (SQL ORM)
drizzle-ormDrizzle (lightweight SQL ORM)
react without nextVanilla React SPA (check for react-router-dom)
vue without nuxtVanilla Vue SPA

Framework Detection (Python)

PackageFramework
fastapiFastAPI (async REST, auto OpenAPI docs)
flaskFlask (minimal WSGI web framework)
djangoDjango (batteries-included, check settings.py)
starletteStarlette (ASGI, often used as FastAPI base)
aiohttpaiohttp (async HTTP client and server)
sqlalchemySQLAlchemy (SQL ORM; check for alembic migrations)
alembicAlembic (SQLAlchemy migration tool)
pydanticPydantic (data validation; core to FastAPI)
celeryCelery (distributed task queue)

Monorepo Detection

Check these signals in order:

  1. pnpm-workspace.yaml — pnpm workspaces

  2. lerna.json — Lerna monorepo

  3. nx.json — Nx monorepo (also check workspace.json)

  4. turbo.json — Turborepo

  5. rush.json — Rush (Microsoft monorepo manager)

  6. moon.yml — Moon

  7. package.json with "workspaces": [...] — npm/yarn workspaces

  8. Presence of packages/, apps/, libs/, or services/ directories with their own package.json

If monorepo is detected: each workspace may have independent dependencies and conventions. Map each sub-package separately in STACK.md and note the monorepo structure in STRUCTURE.md.


TypeScript Path Alias Detection

If tsconfig.json has a paths key, imports with non-relative prefixes are aliases. Map them before documenting structure.

// tsconfig.json example
"paths": {
  "@/*": ["./src/*"],
  "@components/*": ["./src/components/*"],
  "@utils/*": ["./src/utils/*"]
}

Imports like import { foo } from '@/utils/bar' resolve to src/utils/bar. Document as src/utils/bar, not @/utils/bar.


Docker Base Image → Runtime

If no manifest file is present but a Dockerfile exists, the FROM line reveals the runtime:

FROM line patternRuntime
FROM node:XNode.js X
FROM python:XPython X
FROM golang:XGo X
FROM eclipse-temurin:XJava X (Eclipse Temurin JDK)
FROM mcr.microsoft.com/dotnet/aspnet:X.NET X
FROM ruby:XRuby X
FROM rust:XRust X
FROM alpine (alone)Check what's installed via RUN apk add

Requirements and compatibility

Written for: GitHub Copilot, Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter, Needs Python

The author says: Cross-platform. Requires Python 3.8+ and git. Run scripts/scan.py from the target project root.

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

First committed by
GitHub avatar of SriSatyaLokeshSriSatyaLokesh
Publisher
GitHub (Official)
Distributed by
GitHub
Source
github/awesome-copilot · skills/acquire-codebase-knowledge · commit 797337f
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Contributors
SriSatyaLokesh, aaronpowell

AutoGineer is not affiliated with or endorsed by SriSatyaLokesh or GitHub.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download acquire-codebase-knowledge.zip