code-documenter

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

1. 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:

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, Principal Consultant at Synergetic Solutions

Documentation