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code-documenter

Create and maintain code comments, API specifications, documentation sites, and user guides. Apply consistent formats, document parameters and errors, validate code examples, and report which parts of the code have been documented.

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Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides. Use when adding docstrings to functions or classes, creating API documentation, building documentation sites, or writing tutorials and user guides. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, getting started guides.

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适用场景

  • Add explanations to public functions and classes
  • Create API specifications and reference pages
  • Build a documentation site
  • Write getting-started guides and tutorials
  • Check code examples and documentation coverage

包含的文件(9)

  • SKILL.md5.7 KB
  • references/api-docs-fastapi-django.md4.1 KB
  • references/api-docs-nestjs-express.md4.8 KB
  • references/coverage-reports.md3.0 KB
  • references/documentation-systems.md6.0 KB
  • references/interactive-api-docs.md10.0 KB
  • references/python-docstrings.md2.9 KB
  • references/typescript-jsdoc.md3.0 KB
  • references/user-guides-tutorials.md10.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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,).

    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:

TopicReferenceLoad When
Python Docstringsreferences/python-docstrings.mdGoogle, NumPy, Sphinx styles
TypeScript JSDocreferences/typescript-jsdoc.mdJSDoc patterns, TypeScript
FastAPI/Django APIreferences/api-docs-fastapi-django.mdPython API documentation
NestJS/Express APIreferences/api-docs-nestjs-express.mdNode.js API documentation
Coverage Reportsreferences/coverage-reports.mdGenerating documentation reports
Documentation Systemsreferences/documentation-systems.mdDoc sites, static generators, search, testing
Interactive API Docsreferences/interactive-api-docs.mdOpenAPI 3.1, portals, GraphQL, WebSocket, gRPC, SDKs
User Guides & Tutorialsreferences/user-guides-tutorials.mdGetting 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

Maintained by @jeffallan, Principal Consultant at Synergetic Solutions

Documentation

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