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)

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,).