Codebase Documenter
- 530 installs
- 656 repo stars
- Updated July 25, 2026
- mhattingpete/claude-skills-marketplace
codebase-documenter is a Claude Code skill that generates structured architecture, component, and data-flow documentation for an entire codebase so developers and agents can understand it quickly.
About
codebase-documenter is a skill from mhattingpete/claude-skills-marketplace that scans a repository and writes comprehensive documentation covering architecture, key components, data flow, and development guidelines. It triggers on prompts like explain this codebase, document the architecture, or create onboarding docs. Developers reach for it when joining an unfamiliar repo, preparing handoff material, or giving agents a readable system map before refactors. The output is structured prose aimed at humans and coding agents alike. It fits early onboarding and ongoing maintenance when docs drift from implementation.
- Automatically reads and analyzes entire codebases
- Produces clear, hierarchical documentation with summaries and cross-references
- Outputs ready-to-use Markdown files for READMEs, architecture overviews, and module docs
- Reduces manual documentation time from hours to minutes
- Compatible with Claude Code, Cursor, and other agent workflows
Codebase Documenter by the numbers
- 530 all-time installs (skills.sh)
- +5 installs in the week ending Aug 4, 2026 (Skillselion tracking)
- Ranked #375 of 1,879 Documentation skills by installs in the Skillselion catalog
- Data as of Aug 4, 2026 (Skillselion catalog sync)
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| Installs | 530 |
|---|---|
| repo stars | ★ 656 |
| Last updated | July 25, 2026 |
| Repository | mhattingpete/claude-skills-marketplace ↗ |
How do you document an unfamiliar codebase architecture?
Automatically generate accurate, structured documentation for an entire codebase so agents and humans can understand it instantly.
Who is it for?
Developers onboarding to a large repo or preparing agent-readable system documentation before refactors.
Skip if: Teams that only need a single function explained or already maintain up-to-date auto-generated API reference docs.
When should I use this skill?
User says explain this codebase, document architecture, create onboarding docs, or how does this system work
What you get
Architecture write-ups, component inventories, data-flow explanations, and developer onboarding documentation
- Architecture documentation
- Onboarding guides
- Component and data-flow write-ups
Files
Codebase Documenter
Generates comprehensive documentation for codebases - architecture, components, data flow, development guidelines.
When to Use
- "explain this codebase"
- "document the architecture"
- "how does this code work"
- "create developer documentation"
- "generate codebase overview"
- "create onboarding docs"
What It Documents
1. Project Overview
- Purpose & vision
- Target users
- Key features
- Technology stack
- Project status
2. Architecture
- High-level structure
- Design patterns
- Data flow
- Control flow
- Diagrams (Mermaid)
- Architectural decisions
3. Directory Structure
- Organization purpose
- Naming conventions
- Entry points
- Core modules
- Configuration locations
4. Key Components
- Major modules
- Classes & functions
- Responsibilities
- Interactions
- Extension points
- Code examples
5. External Integrations
- APIs consumed
- Databases & schemas
- Authentication
- Caching
- Message queues
- File storage
6. Data Models
- Database schema
- Data structures
- Validation
- Migrations
- Data transformations
7. Development Setup
- Prerequisites
- Installation steps
- Configuration
- Running the app
- Testing
- Debugging
- Troubleshooting
8. Development Guidelines
- Coding conventions
- Testing approach
- Error handling
- Logging
- Security practices
- Performance patterns
9. Deployment
- Build process
- Deployment steps
- Environments
- Monitoring
- Rollback procedures
10. Contributing
- Development workflow
- Code review guidelines
- Testing requirements
- Documentation updates
Approach
1. Explore using Explore agent (thorough) 2. Map structure with Glob 3. Read critical files (README, entry points, core modules) 4. Identify patterns with Grep (imports, exports) 5. Trace execution paths 6. Extract knowledge from docs, comments, tests 7. Synthesize into cohesive documentation
Output
Creates markdown documentation:
docs/
├── README.md # Overview and quick start
├── ARCHITECTURE.md # System architecture
├── DEVELOPMENT.md # Development guide
├── API.md # API documentation
├── DEPLOYMENT.md # Deployment guide
└── CONTRIBUTING.md # Contribution guidelinesOr single comprehensive doc if preferred.
Depth Levels
- Quick: High-level overview (15-30 min)
- Standard: Comprehensive coverage (30-60 min)
- Deep: Exhaustive with examples (60+ min)
Visual Elements
- Mermaid diagrams (architecture, flow charts, sequence)
- Code examples from codebase
- Specific file:line references
- Tables for structured info
- Lists for guidelines
Tools Used
- Task (Explore agent): Codebase exploration
- Glob: Map directory structure
- Grep: Find patterns, imports, exports
- Read: Analyze key files
- Write: Create documentation
- Bash: Extract metadata (git log, versions)
Success Criteria
- Complete coverage of all areas
- Clear explanations with examples
- Visual diagrams for complex concepts
- Specific file:line references
- Actionable setup/development instructions
- New developer can onboard using only docs
- Organized, navigable structure
- Accurate and current information
Integration
- code-auditor: Includes quality/security context
- project-bootstrapper: Documents bootstrap decisions
- visual-html-creator: Create visual diagrams
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What does codebase-documenter produce?
codebase-documenter writes structured documentation for a repository, including architecture summaries, key components, data-flow explanations, and development guidelines aimed at onboarding developers and coding agents.
When should I use codebase-documenter?
Use codebase-documenter when prompts ask to explain an unfamiliar codebase, document architecture, or create onboarding docs. The skill is meant for whole-repo understanding rather than single-file comments.