Agent skill

Codebase Documenter

by ailabs-393 in ailabs-393/ai-labs-claude-skills

This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation.

MITAuto-check passedDevelopment

Install Codebase Documenter

skills CLI
$ npx skills add ailabs-393/ai-labs-claude-skills --skill codebase-documenter -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ailabs-393/ai-labs-claude-skills codebase-documenter --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills/codebase-documenter .claude/skills/codebase-documenter && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
codebase-documenter
GitHub stars
454
Used in
1 other repo
Token cost
~2.9k tokens
SKILL.md length
932 words
Files
9 (incl. references, assets)
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation.

  • Works in 8 steps: README Documentation → Architecture Documentation → Code Comments → …
  • Users request help documenting their code
  • SKILL.md covers Overview, Core Principles for…, Documentation Types and When… and Documentation Workflow, plus 5 more sections
  • Runs JavaScript scripts from its folder

What it does

Codebase Documenter is an agent skill from ailabs-393/ai-labs-claude-skills. This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation. Use this skill when users request help documenting their code, creating getting-started guides, explaining project structure, or making codebases more accessible to new developers. The skill provides templates, best practices, and structured approaches for creating clear, beginner-friendly documentation.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files and assets (for example `assets/templates/API.template.md`, `assets/templates/ARCHITECTURE.template.md` and `assets/templates/CODE_COMMENTS.template.md`).

It sits in Development, covering Technical documentation. The repository describes itself as: This package is use to remove the hustle of finding claudeskills and shift them into any of the user project. This project become a bridge between user's usage and claude skills. The licence is MIT.

When your agent uses it

  • Users request help documenting their code
  • Creating getting-started guides
  • Explaining project structure
  • Making codebases more accessible to new developers

Example prompts

  • “/codebase-documenter”

Requirements

  • Python 3
  • Node.js

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. README Documentation
  2. Architecture Documentation
  3. Code Comments
  4. API Documentation
  5. Analyze the Codebase
  6. Choose Documentation Type
  7. Generate Documentation
  8. Review for Clarity

What it can do on your machine

Read from SKILL.md and the folder at commit 1a12bc7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (JavaScript), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Codebase Documenter loads about 2.9k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 121 tokens; SKILL.md has 932 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~121
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~13k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ailabs-393/ai-labs-claude-skills at commit 1a12bc7, republished under its MIT licence (© ailabs-393). 932 words, ~2,934 tokens.

Download SKILL.mdSave it as .claude/skills/codebase-documenter/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
codebase-documenter
description
This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation. Use this skill when users request help documenting their code, creating getting-started guides, explaining project structure, or making codebases more accessible to new developers. The skill provides templates, best practices, and structured approaches for creating clear, beginner-friendly documentation.

Codebase Documenter

Overview

This skill enables creating comprehensive, beginner-friendly documentation for codebases. It provides structured templates and best practices for writing READMEs, architecture guides, code comments, and API documentation that help new users quickly understand and contribute to projects.

Core Principles for Beginner-Friendly Documentation

When documenting code for new users, follow these fundamental principles:

  1. Start with the "Why" - Explain the purpose before diving into implementation details
  2. Use Progressive Disclosure - Present information in layers from simple to complex
  3. Provide Context - Explain not just what the code does, but why it exists
  4. Include Examples - Show concrete usage examples for every concept
  5. Assume No Prior Knowledge - Define terms and avoid jargon when possible
  6. Visual Aids - Use diagrams, flowcharts, and file tree structures
  7. Quick Wins - Help users get something running within 5 minutes

Documentation Types and When to Use Them

1. README Documentation

When to create: For project root directories, major feature modules, or standalone components.

Structure to follow:

markdown
# Project Name

## What This Does
[1-2 sentence plain-English explanation]

## Quick Start
[Get users running the project in < 5 minutes]

## Project Structure
[Visual file tree with explanations]

## Key Concepts
[Core concepts users need to understand]

## Common Tasks
[Step-by-step guides for frequent operations]

## Troubleshooting
[Common issues and solutions]

Best practices:

  • Lead with the project's value proposition
  • Include setup instructions that actually work (test them!)
  • Provide a visual overview of the project structure
  • Link to deeper documentation for advanced topics
  • Keep the root README focused on getting started
2. Architecture Documentation

When to create: For projects with multiple modules, complex data flows, or non-obvious design decisions.

Structure to follow:

markdown
# Architecture Overview

## System Design
[High-level diagram and explanation]

## Directory Structure
[Detailed breakdown with purpose of each directory]

## Data Flow
[How data moves through the system]

## Key Design Decisions
[Why certain architectural choices were made]

## Module Dependencies
[How different parts interact]

## Extension Points
[Where and how to add new features]

Best practices:

  • Use diagrams to show system components and relationships
  • Explain the "why" behind architectural decisions
  • Document both the happy path and error handling
  • Identify boundaries between modules
  • Include visual file tree structures with annotations
3. Code Comments

When to create: For complex logic, non-obvious algorithms, or code that requires context.

Annotation patterns:

Function/Method Documentation:

javascript
/**
 * Calculates the prorated subscription cost for a partial billing period.
 *
 * Why this exists: Users can subscribe mid-month, so we need to charge
 * them only for the days remaining in the current billing cycle.
 *
 * @param {number} fullPrice - The normal monthly subscription price
 * @param {Date} startDate - When the user's subscription begins
 * @param {Date} periodEnd - End of the current billing period
 * @returns {number} The prorated amount to charge
 *
 * @example
 * // User subscribes on Jan 15, period ends Jan 31
 * calculateProratedCost(30, new Date('2024-01-15'), new Date('2024-01-31'))
 * // Returns: 16.13 (17 days out of 31 days)
 */

Complex Logic Documentation:

python
# Why this check exists: The API returns null for deleted users,
# but empty string for users who never set a name. We need to
# distinguish between these cases for the audit log.
if user_name is None:
    # User was deleted - log this as a security event
    log_deletion_event(user_id)
elif user_name == "":
    # User never completed onboarding - safe to skip
    continue

Best practices:

  • Explain "why" not "what" - the code shows what it does
  • Document edge cases and business logic
  • Add examples for complex functions
  • Explain parameters that aren't self-explanatory
  • Note any gotchas or counterintuitive behavior
4. API Documentation

When to create: For any HTTP endpoints, SDK methods, or public interfaces.

Structure to follow:

markdown
## Endpoint Name

### What It Does
[Plain-English explanation of the endpoint's purpose]

### Endpoint
`POST /api/v1/resource`

### Authentication
[What auth is required and how to provide it]

### Request Format
[JSON schema or example request]

### Response Format
[JSON schema or example response]

### Example Usage
[Concrete example with curl/code]

### Common Errors
[Error codes and what they mean]

### Related Endpoints
[Links to related operations]

Best practices:

  • Provide working curl examples
  • Show both success and error responses
  • Explain authentication clearly
  • Document rate limits and constraints
  • Include troubleshooting for common issues

Documentation Workflow

Step 1: Analyze the Codebase

Before writing documentation:

  1. Identify entry points - Main files, index files, app initialization
  2. Map dependencies - How modules relate to each other
  3. Find core concepts - Key abstractions users need to understand
  4. Locate configuration - Environment setup, config files
  5. Review existing docs - Build on what's there, don't duplicate
Step 2: Choose Documentation Type

Based on user request and codebase analysis:

  • New project or missing README → Start with README documentation
  • Complex architecture or multiple modules → Create architecture documentation
  • Confusing code sections → Add inline code comments
  • HTTP/API endpoints → Write API documentation
  • Multiple types needed → Address in order: README → Architecture → API → Comments
Step 3: Generate Documentation

Use the templates from assets/templates/ as starting points:

  • assets/templates/README.template.md - For project READMEs
  • assets/templates/ARCHITECTURE.template.md - For architecture docs
  • assets/templates/API.template.md - For API documentation

Customize templates based on the specific codebase:

  1. Fill in project-specific information - Replace placeholders with actual content
  2. Add concrete examples - Use real code from the project
  3. Include visual aids - Create file trees, diagrams, flowcharts
  4. Test instructions - Verify setup steps actually work
  5. Link related docs - Connect documentation pieces together
Show full SKILL.md (392 more words)Show less
Step 4: Review for Clarity

Before finalizing documentation:

  1. Read as a beginner - Does it make sense without project context?
  2. Check completeness - Are there gaps in the explanation?
  3. Verify examples - Do code examples actually work?
  4. Test instructions - Can someone follow the setup steps?
  5. Improve structure - Is information easy to find?

Documentation Templates

This skill includes several templates in assets/templates/ that provide starting structures:

Available Templates
  • README.template.md - Comprehensive README structure with sections for quick start, project structure, and common tasks
  • ARCHITECTURE.template.md - Architecture documentation template with system design, data flow, and design decisions
  • API.template.md - API endpoint documentation with request/response formats and examples
  • CODE_COMMENTS.template.md - Examples and patterns for effective inline documentation
Using Templates
  1. Read the appropriate template from assets/templates/
  2. Customize for the specific project - Replace placeholders with actual information
  3. Add project-specific sections - Extend the template as needed
  4. Include real examples - Use actual code from the codebase
  5. Remove irrelevant sections - Delete parts that don't apply

Best Practices Reference

For detailed documentation best practices, style guidelines, and advanced patterns, refer to:

  • references/documentation_guidelines.md - Comprehensive style guide and best practices
  • references/visual_aids_guide.md - How to create effective diagrams and file trees

Load these references when:

  • Creating documentation for complex enterprise codebases
  • Dealing with multiple stakeholder requirements
  • Needing advanced documentation patterns
  • Standardizing documentation across a large project

Common Patterns

Creating File Tree Structures

File trees help new users understand project organization:

project-root/
├── src/                    # Source code
│   ├── components/        # Reusable UI components
│   ├── pages/             # Page-level components (routing)
│   ├── services/          # Business logic and API calls
│   ├── utils/             # Helper functions
│   └── types/             # TypeScript type definitions
├── public/                # Static assets (images, fonts)
├── tests/                 # Test files mirroring src structure
└── package.json           # Dependencies and scripts
Explaining Complex Data Flows

Use numbered steps with diagrams:

User Request Flow:
1. User submits form → 2. Validation → 3. API call → 4. Database → 5. Response

[1] components/UserForm.tsx
    ↓ validates input
[2] services/validation.ts
    ↓ sends to API
[3] services/api.ts
    ↓ queries database
[4] Database (PostgreSQL)
    ↓ returns data
[5] components/UserForm.tsx (updates UI)
Documenting Design Decisions

Capture the "why" behind architectural choices:

markdown
## Why We Use Redux

**Decision:** State management with Redux instead of Context API

**Context:** Our app has 50+ components that need access to user
authentication state, shopping cart, and UI preferences.

**Reasoning:**
- Context API causes unnecessary re-renders with this many components
- Redux DevTools helps debug complex state changes
- Team has existing Redux expertise

**Trade-offs:**
- More boilerplate code
- Steeper learning curve for new developers
- Worth it for: performance, debugging, team familiarity

Output Guidelines

When generating documentation:

  1. Write for the target audience - Adjust complexity based on whether documentation is for beginners, intermediate, or advanced users
  2. Use consistent formatting - Follow markdown conventions, consistent heading hierarchy
  3. Provide working examples - Test all code snippets and commands
  4. Link between documents - Create a documentation navigation structure
  5. Keep it maintainable - Documentation should be easy to update as code changes
  6. Add dates and versions - Note when documentation was last updated

Quick Reference

Command to generate README: "Create a README file for this project that helps new developers get started"

Command to document architecture: "Document the architecture of this codebase, explaining how the different modules interact"

Command to add code comments: "Add explanatory comments to this file that help new developers understand the logic"

Command to document API: "Create API documentation for all the endpoints in this file"

© ailabs-393, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references, assets) in packages/skills/codebase-documenter of ailabs-393/ai-labs-claude-skills.

  • SKILL.md
  • assets/templates/API.template.md
  • assets/templates/ARCHITECTURE.template.md
  • assets/templates/CODE_COMMENTS.template.md
  • assets/templates/README.template.md
  • index.js
  • package.json
  • references/documentation_guidelines.md
  • references/visual_aids_guide.md

Open the folder on GitHubat commit 1a12bc7

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in ailabs-393/ai-labs-claude-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Codebase Documenter next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Codebase Documenter compared with similar skills
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Codebase Documenter this skillailabs-393/ai-labs-claude-skills4541 repos~2.9kAutomated safety check: PassMIT
Diagram Designcathrynlavery/diagram-design45k1 repos~7.5kAutomated safety check: PassMIT
Simple Englishmoeru-ai/airi50k2 repos~4.6kAutomated safety check: PassMIT
Get API Docs with chubandrewyng/context-hub14k2 repos~775Automated safety check: PassMIT
Doc SyncJetBrains/ideavim10k2 repos~2.6kAutomated safety check: PassMIT
Mailspring App ScreenshotsFoundry376/Mailspring18k—~1.5kAutomated safety check: PassGPL-3.0

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Categories

Questions about Codebase Documenter

What does Codebase Documenter do?

This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation. Codebase Documenter is an agent skill from ailabs-393/ai-labs-claude-skills. This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation.

When should I use Codebase Documenter?

Codebase Documenter fits situations like: users request help documenting their code; creating getting-started guides; explaining project structure; making codebases more accessible to new developers.

How do I install Codebase Documenter in Claude Code?

Run `npx skills add ailabs-393/ai-labs-claude-skills --skill codebase-documenter -a claude-code`. Or copy the skill folder (packages/skills/codebase-documenter in ailabs-393/ai-labs-claude-skills) into .claude/skills/codebase-documenter in your project. Claude Code loads it when a task matches its description.

How do I install Codebase Documenter in Codex?

Run `npx skills add ailabs-393/ai-labs-claude-skills --skill codebase-documenter -a codex`. Or copy the skill folder (packages/skills/codebase-documenter in ailabs-393/ai-labs-claude-skills) into .agents/skills/codebase-documenter in your project. Codex loads it when a task matches its description.

Can I use Codebase Documenter in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ailabs-393/ai-labs-claude-skills --skill codebase-documenter -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/codebase-documenter, .gemini/skills/codebase-documenter, .github/skills/codebase-documenter and .opencode/skills/codebase-documenter in your project.

What does Codebase Documenter need to run?

Going by SKILL.md and its folder, Codebase Documenter needs JavaScript for the scripts in its folder. Our summary lists: Python 3; Node.js.

Does Codebase Documenter access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Codebase Documenter safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Codebase Documenter use?

Codebase Documenter is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Codebase Documenter use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.8k tokens, read only when the agent opens those files.

What are the alternatives to Codebase Documenter?

Skills that share tags, products or a category with Codebase Documenter: Diagram Design (cathrynlavery/diagram-design, 45k stars), Simple English (moeru-ai/airi, 50k stars), Get API Docs with chub (andrewyng/context-hub, 14k stars) and Doc Sync (JetBrains/ideavim, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Codebase Documenter?

ailabs-393 (a GitHub user) maintains it in ailabs-393/ai-labs-claude-skills, which has 454 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on November 11, 2025.

Source: ailabs-393/ai-labs-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.