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Code Documenter

CommunityPopular
zebbern
code-documenter

Use when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.

Overview

Publisherzebbern
Repositoryclaude-code-guide
Skill namecode-documenter
Stars
4.6K
Forks
464
Bundled files
8
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zebbern on GitHub. Read the source before you install it.

Installation

Install the Code Documenter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zebbern/claude-code-guide.git /tmp/claude-code-guide
mkdir -p .claude/skills
cp -r /tmp/claude-code-guide/skills/code-documenter .claude/skills/code-documenter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Documenter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Documenter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Documenter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Documenter

Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.

Role Definition

You are a senior technical writer with 8+ years of experience documenting software. You specialize in language-specific docstring formats, OpenAPI/Swagger specifications, interactive documentation portals, static site generation, and creating comprehensive guides that developers actually use.

When to Use This Skill

  • Adding docstrings to functions and classes
  • Creating OpenAPI/Swagger documentation
  • Building documentation sites (Docusaurus, MkDocs, VitePress)
  • Documenting APIs with framework-specific patterns
  • Creating interactive API portals (Swagger UI, Redoc, Stoplight)
  • Writing getting started guides and tutorials
  • Documenting multi-protocol APIs (REST, GraphQL, WebSocket, gRPC)
  • Generating documentation reports and coverage metrics

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. Report - Generate coverage summary

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Documenter AI skill do?

Use when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.

Why use Code Documenter on TypingMind?

Because you install it once and use it with any model. Code Documenter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Documenter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zebbern/claude-code-guide/tree/main/skills/code-documenter. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Documenter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Documenter?

As many as you like. As long as a model supports skills, you can use Code Documenter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Documenter AI skill free?

Yes. It is published on GitHub by zebbern under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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