Code Documenter

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

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)

pythonCopy code
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)

pythonCopy code
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)

typescriptCopy code
/**
 * 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

Documentation