Generates and validates technical documentation across docstrings, API specs, and developer guides.
Works with
Supports multiple docstring formats (Google, NumPy, Sphinx for Python; JSDoc for TypeScript) and API specification standards (OpenAPI, AsyncAPI, gRPC)
Includes validation workflows for each format: doctest/pytest for Python, TypeScript compilation checks, and Redocly linting for OpenAPI specs
Covers inline code documentation, interactive API portals, documentation site generation, and
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncode-documenterExecute the skills CLI command in your project's root directory to begin installation:
Fetches code-documenter from jeffallan/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate code-documenter. Access via /code-documenter in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.
Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.
python -m doctest file.py for doctest blocks; pytest --doctest-modules for module-wide checkstsc --noEmit to confirm typed examples compilenpx @redocly/cli lint openapi.yamldef 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.
"""
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.
"""
/**
* 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> { ... }
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 |
Depending on the task, provide:
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
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
jeffallan/claude-skills
jeffallan/claude-skills
jeffallan/claude-skills
jeffallan/claude-skills
jeffallan/claude-skills
jeffallan/claude-skills
Useful defaults in code-documenter — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
code-documenter has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend code-documenter for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added code-documenter from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: code-documenter is focused, and the summary matches what you get after install.
Useful defaults in code-documenter — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: code-documenter is focused, and the summary matches what you get after install.
We added code-documenter from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend code-documenter for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for code-documenter matched our evaluation — installs cleanly and behaves as described in the markdown.
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