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code-documenter

Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides

Install / Use

npx skills add Jeffallan/claude-skills --skill code-documenter

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

91/100

Supported Platforms

Universal

Our assessment of code-documenter

code-documenter scores 91/100 on our quality scale, 160th of 670 Content & Media skills we index (top 24%).

Its SKILL.md is 5.4 KB long, well organised into 13 sections with 3 code examples: a solid amount of guidance for an agent.

With 11,621 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
15/15
Adoption
17/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so code-documenter is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

code-documenter compared with similar skills

All 4 of these similar skills score higher than code-documenter; compare them before choosing.

SkillScoreStarsUpdatedFormat
code-documenter (this skill)by Jeffallan9111.6k51d agoSKILL.md
Agent-Reachby Panniantong10085.8k12d agoCLAUDE.md
headroomby headroomlabs-ai10074.0k1d agoCLAUDE.md
crawl4aiby unclecode10084.4k2d agoMCP Server
Scraplingby D4Vinci10084.1ktodayMCP Server

Frequently asked questions

How do I install code-documenter?
Run npx skills add Jeffallan/claude-skills --skill code-documenter. The install tabs above show the steps for each supported agent.
Which AI agents does code-documenter work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is code-documenter safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is code-documenter still maintained?
The repository was last updated about 2 months ago, so code-documenter is actively maintained.

name: code-documenter description: 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. license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: quality triggers: documentation, docstrings, OpenAPI, Swagger, JSDoc, comments, API docs, tutorials, user guides, doc site role: specialist scope: implementation output-format: code related-skills: spec-miner, fullstack-guardian, code-reviewer

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

Documentation

Related Skills

View on GitHub
GitHub Stars11.6k
CategoryContent
Updated1mo ago
Forks1.1k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions