---
name: code-documenter-c317493f9b94
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
  company: https://synergetic.solutions
  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

- Adding docstrings to functions, classes, and modules
- Writing OpenAPI/Swagger specs or JSDoc annotations
- Creating API documentation for REST or GraphQL endpoints
- Building documentation sites or developer portals
- Writing getting-started guides, tutorials, and user guides

## Core Workflow

1. **Discover** - Ask for format preference and exclusions
2. **Detect** - Identify language and framework
3. **Analyze** - Find undocumented code
4. **Document** - Apply consistent format
5. **Validate** - Test all code examples compile/run:
   - Python: `python -m doctest file.py` for doctest blocks; `pytest --doctest-modules` for module-wide checks
   - TypeScript/JavaScript: `tsc --noEmit` to 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
6. **Report** - Generate coverage summary

## Quick-Reference Examples

### Google-style Docstring (Python)
```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)
```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)
```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:
1. **Code Documentation:** Documented files + coverage report
2. **API Docs:** OpenAPI specs + portal configuration
3. **Doc Sites:** Site configuration + content structure + build instructions
4. **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

Maintained by [@jeffallan](https://github.com/jeffallan), Principal Consultant at [Synergetic Solutions](https://synergetic.solutions)

[Documentation](https://jeffallan.github.io/claude-skills/skills/quality/code-documenter/)


---
Source attribution: Jeffallan
Original project: https://github.com/Jeffallan/claude-skills
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: Jeffallan
Original project: https://github.com/Jeffallan/claude-skills
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Content & Media, Development & Engineering, Product Management
Roles: Backend Developer, Frontend Developer, Product Manager, QA / Test Engineer, Technical Writer
Specialties: API, Backend, Cross Platform, Testing
Tools: Jsdoc, Openapi, Swagger
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: e0b55598527cdd98b734512b2fce38eb8b60ac4bd2ca7424a8ea27ac104e0ed3