code-documenter
jeffallan/claude-skills
Generate and validate technical documentation—docstrings, API specs, JSDoc, and developer guides.
What is code-documenter?
Generates, formats, and validates technical documentation across multiple formats including docstrings, OpenAPI/Swagger specs, JSDoc annotations, documentation sites, and user guides. Use when adding inline documentation to code, creating API specifications, building documentation portals, or writing tutorials and getting-started guides.
- Generate Google/NumPy/Sphinx-style Python docstrings with parameter types, return values, and exception documentation
- Create and validate OpenAPI 3.0/3.1 and AsyncAPI specifications for REST and async APIs
- Write and format JSDoc annotations for TypeScript/JavaScript with type hints and examples
- Build documentation sites using Docusaurus, MkDocs, or VitePress with structured content
- Validate code examples in documentation by running doctests, TypeScript compilation, and spec linting
- Generate documentation coverage reports showing documented vs. undocumented functions
How to install code-documenter
npx skills add https://github.com/jeffallan/claude-skills --skill code-documenter- Python 3.7+ for doctest validation
- Node.js 14+ for TypeScript/JavaScript validation and OpenAPI linting
- npx @redocly/cli for OpenAPI spec validation
- pytest for Python module-wide doctest checks
How to use code-documenter
- 1.Ask the skill for your preferred documentation format (Google/NumPy/JSDoc/OpenAPI) and any exclusions
- 2.The skill detects your code language and framework to apply the correct documentation strategy
- 3.Identify undocumented public functions, classes, and API endpoints in your codebase
- 4.Apply consistent documentation format with parameter types, descriptions, return values, and exceptions
- 5.Validate all code examples by running doctests, TypeScript compilation, or OpenAPI linting
- 6.Review the generated documentation coverage report and iterate on any failed validations
Use cases
- Add comprehensive docstrings to a Python codebase with consistent Google-style formatting and validated examples
- Create an OpenAPI specification for a FastAPI or Express API and generate an interactive Swagger UI portal
- Document a TypeScript library with JSDoc annotations including parameter types, return types, and usage examples
- Build a getting-started guide and tutorial site for a new framework or library with MkDocs or Docusaurus
- Validate that all code examples in API documentation compile and run correctly before publishing
- Backend developers documenting Python, Node.js, or TypeScript APIs
- API maintainers creating OpenAPI specifications and interactive documentation portals
- Technical writers building user guides, tutorials, and documentation sites
- DevOps and platform teams documenting infrastructure code and runbooks
- Open-source maintainers ensuring consistent, tested documentation across projects
code-documenter FAQ
Google-style, NumPy-style, and Sphinx-style for Python; JSDoc for TypeScript/JavaScript; and OpenAPI 3.0/3.1 for API specifications.
Python uses doctest and pytest --doctest-modules; TypeScript uses tsc --noEmit; OpenAPI uses npx @redocly/cli lint. All examples must compile/run before the report is generated.
Yes, it creates OpenAPI specs that integrate with Swagger UI, Redoc, or Stoplight for interactive API portals.
Docusaurus, MkDocs, VitePress, and other static site generators with structured markdown content and build instructions.
No—the skill avoids verbose documentation of obvious getters/setters to keep documentation maintainable and focused on complex logic.
Full instructions (SKILL.md)
Source of truth, from jeffallan/claude-skills.
name: code-documenter description: Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides. Use when adding docstrings to functions or classes, creating API documentation, building documentation sites, or writing tutorials and user guides. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, getting started guides. license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: quality triggers: documentation, docstrings, OpenAPI, Swagger, JSDoc, comments, API docs, tutorials, user guides, doc site role: specialist scope: implementation output-format: code related-skills: spec-miner, fullstack-guardian, code-reviewer
Code Documenter
Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.
When to Use This Skill
Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.
Core Workflow
- Discover - Ask for format preference and exclusions
- Detect - Identify language and framework
- Analyze - Find undocumented code
- Document - Apply consistent format
- Validate - Test all code examples compile/run:
- Python:
python -m doctest file.pyfor doctest blocks;pytest --doctest-modulesfor module-wide checks - TypeScript/JavaScript:
tsc --noEmitto confirm typed examples compile - OpenAPI: validate spec with
npx @redocly/cli lint openapi.yaml - If validation fails: fix examples and re-validate before proceeding to the Report step
- Python:
- Report - Generate coverage summary
Quick-Reference Examples
Google-style Docstring (Python)
def fetch_user(user_id: int, active_only: bool = True) -> dict:
"""Fetch a single user record by ID.
Args:
user_id: Unique identifier for the user.
active_only: When True, raise an error for inactive users.
Returns:
A dict containing user fields (id, name, email, created_at).
Raises:
ValueError: If user_id is not a positive integer.
UserNotFoundError: If no matching user exists.
"""
NumPy-style Docstring (Python)
def compute_similarity(vec_a: np.ndarray, vec_b: np.ndarray) -> float:
"""Compute cosine similarity between two vectors.
Parameters
----------
vec_a : np.ndarray
First input vector, shape (n,).
vec_b : np.ndarray
Second input vector, shape (n,).
Returns
-------
float
Cosine similarity in the range [-1, 1].
Raises
------
ValueError
If vectors have different lengths.
"""
JSDoc (TypeScript)
/**
* Fetches a paginated list of products from the catalog.
*
* @param {string} categoryId - The category to filter by.
* @param {number} [page=1] - Page number (1-indexed).
* @param {number} [limit=20] - Maximum items per page.
* @returns {Promise<ProductPage>} Resolves to a page of product records.
* @throws {NotFoundError} If the category does not exist.
*
* @example
* const page = await fetchProducts('electronics', 2, 10);
* console.log(page.items);
*/
async function fetchProducts(
categoryId: string,
page = 1,
limit = 20
): Promise<ProductPage> { ... }
Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|---|---|---|
| Python Docstrings | references/python-docstrings.md | Google, NumPy, Sphinx styles |
| TypeScript JSDoc | references/typescript-jsdoc.md | JSDoc patterns, TypeScript |
| FastAPI/Django API | references/api-docs-fastapi-django.md | Python API documentation |
| NestJS/Express API | references/api-docs-nestjs-express.md | Node.js API documentation |
| Coverage Reports | references/coverage-reports.md | Generating documentation reports |
| Documentation Systems | references/documentation-systems.md | Doc sites, static generators, search, testing |
| Interactive API Docs | references/interactive-api-docs.md | OpenAPI 3.1, portals, GraphQL, WebSocket, gRPC, SDKs |
| User Guides & Tutorials | references/user-guides-tutorials.md | Getting started, tutorials, troubleshooting, FAQs |
Constraints
MUST DO
- Ask for format preference before starting
- Detect framework for correct API doc strategy
- Document all public functions/classes
- Include parameter types and descriptions
- Document exceptions/errors
- Test code examples in documentation
- Generate coverage report
MUST NOT DO
- Assume docstring format without asking
- Apply wrong API doc strategy for framework
- Write inaccurate or untested documentation
- Skip error documentation
- Document obvious getters/setters verbosely
- Create documentation that's hard to maintain
Output Formats
Depending on the task, provide:
- Code Documentation: Documented files + coverage report
- API Docs: OpenAPI specs + portal configuration
- Doc Sites: Site configuration + content structure + build instructions
- Guides/Tutorials: Structured markdown with examples + diagrams
Knowledge Reference
Google/NumPy/Sphinx docstrings, JSDoc, OpenAPI 3.0/3.1, AsyncAPI, gRPC/protobuf, FastAPI, Django, NestJS, Express, GraphQL, Docusaurus, MkDocs, VitePress, Swagger UI, Redoc, Stoplight
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