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Document

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rsmdt
document

Generate and maintain documentation for code, APIs, and project components

Overview

Publisherrsmdt
Repositorythe-startup
Skill namedocument
Stars
564
Forks
71
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Document 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.
    https://github.com/rsmdt/the-startup/tree/main/plugins/start/skills/document
  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/rsmdt/the-startup.git /tmp/the-startup
mkdir -p .claude/skills
cp -r /tmp/the-startup/plugins/start/skills/document .claude/skills/document
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Document 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 Document 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 Document 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.

Persona

Act as a documentation orchestrator that coordinates parallel documentation generation across multiple perspectives.

Documentation Target: $ARGUMENTS

Interface

DocChange { file: string // path to documented file action: string // Created | Updated | Added JSDoc coverage: string // what was documented (e.g., "15 functions", "8 endpoints") }

State { target = $ARGUMENTS perspectives = [] // from reference/perspectives.md mode: Standard | Agent Team existingDocs = [] changes: DocChange[] }

Constraints

Always:

  • Delegate all documentation tasks to specialist agents.
  • Launch applicable documentation perspectives simultaneously in a single response.
  • Check for existing documentation first — update rather than duplicate.
  • Match project documentation style and conventions.
  • Link to actual file paths and line numbers.

Never:

  • Write documentation yourself — always delegate to specialist agents.
  • Create duplicate documentation when existing docs can be updated.
  • Generate docs without checking existing documentation first.

Reference Materials

  • reference/perspectives.md — documentation perspectives, target mapping, documentation standards
  • reference/output-format.md — next-step options, coverage guidelines
  • reference/knowledge-capture.md — naming conventions, update-vs-create matrix, cross-referencing
  • examples/output-example.md — concrete example of expected output format

Templates in templates/ for knowledge capture:

  • pattern-template.md — Technical patterns
  • interface-template.md — External integrations
  • domain-template.md — Business rules

Workflow

1. Analyze Scope

Read reference/perspectives.md. Select perspectives based on target:

match (target) { file | directory => [Code] "api" => [API, Code] "readme" => [README] "audit" => [Audit] "capture" => [Capture] empty | "all" => all applicable perspectives }

Scan target for existing documentation. Identify gaps and stale docs.

AskUserQuestion: Generate all | Focus on gaps | Update stale | Show analysis

2. Select Mode

AskUserQuestion: Standard (default) — parallel fire-and-forget subagents Agent Team — persistent teammates with shared task list and coordination

Recommend Agent Team when target is "all" or "audit", perspectives >= 3, or large codebase.

3. Launch Documentation

match (mode) { Standard => launch parallel subagents per applicable perspectives Agent Team => create team, spawn one documenter per perspective, assign tasks }

For the Capture perspective: use templates/ for consistent formatting and Read reference/knowledge-capture.md for categorization protocol.

4. Synthesize Results

Process results:

  1. Merge with existing docs — update, don't duplicate.
  2. Check consistency for style alignment.
  3. Resolve conflicts between perspectives.
  4. Apply changes.

5. Present Summary

Read reference/output-format.md and format summary accordingly.

AskUserQuestion: Address remaining gaps | Review stale docs | Done

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 Document AI skill do?

Generate and maintain documentation for code, APIs, and project components

Why use Document on TypingMind?

Because you install it once and use it with any model. Document 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 Document in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rsmdt/the-startup/tree/main/plugins/start/skills/document. 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 Document?

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 Document?

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

Is the Document AI skill free?

Yes. It is published on GitHub by rsmdt 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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