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)

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)