Skills Development Code Documentation Specialist

Code Documentation Specialist

v20260306
code-documenter
Generates, formats, and validates technical documentation, covering docstrings, OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, and guides. Use it when adding docstrings, creating API docs, building doc sites, or writing getting-started materials, and rely on the built-in validation reports.
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Overview

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)

/**
 * 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

Info
Category Development
Name code-documenter
Version v20260306
Size 21.07KB
Updated At 2026-03-10
Language