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Documentation

CommunityPopular
mcollina
documentation

Creates, structures, and reviews technical documentation following the Diátaxis framework (tutorials, how-to guides, reference, and explanation pages). Use when a user needs to write or reorganize docs, structure a tutorial vs. a how-to guide, build reference docs or API documentation, create explanation pages, choose between Diátaxis documentation types, or improve existing documentation structure. Trigger terms include: documentation structure, Diátaxis, tutorials vs how-to guides, organize docs, user guide, reference docs, technical writing.

Overview

Publishermcollina
Repositoryskills
Skill namedocumentation
Stars
1.9K
Forks
149
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Documentation 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/mcollina/skills/tree/main/skills/documentation
  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/mcollina/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/documentation .claude/skills/documentation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Documentation 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 Documentation 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 Documentation 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.

When to use

Use this skill when you need to create, review, or improve technical documentation following the Diátaxis framework. Examples include:

  • Creating user guides
  • API documentation
  • Tutorial content
  • Restructuring existing documentation to better serve different user needs and contexts

Instructions

Organize documentation into four distinct types — tutorials, how-to guides, reference material, and explanations — each serving different user needs and contexts.

Always ask clarifying questions about the user's context, audience, and goals before creating documentation.


Step 1 — Identify the documentation type

Use the following decision checklist based on user signals:

User signalDocumentation type
"I'm new to X and want to learn it" / "walk me through"Tutorial
"How do I…?" / "I need to accomplish X"How-to guide
"What are the parameters/options/syntax for X?"Reference
"Why does X work this way?" / "Help me understand X"Explanation

Quick decision tree:

  • Is the user learning by doing for the first time? → Tutorial
  • Do they need to solve a specific problem they already understand? → How-to guide
  • Do they need technical facts to look up? → Reference
  • Do they want conceptual background? → Explanation

Step 2 — Apply type-specific patterns

Tutorials (learning-oriented)
  • Title pattern: Start with a verb — "Build your first X", "Create a Y from scratch"
  • Structure: Goal → Prerequisites → Numbered steps → Immediate verifiable result at each step → Final outcome
  • Minimise explanation; maximise doing
  • Every step must produce a visible, testable result
  • Validation: A beginner must be able to complete the tutorial without external help

Example intro:

"In this tutorial, you will build a simple REST API using Express. By the end, you will have a running server that responds to GET requests. No prior Express experience is needed."


How-to guides (problem-oriented)
  • Title pattern: Frame as a task — "How to configure X", "How to deploy Y to Z"
  • Structure: Goal statement → Assumptions/prerequisites → Numbered steps → Expected result
  • Assume baseline knowledge; skip conceptual explanations
  • Allow for variation; note alternatives where they exist
  • Validation: An experienced user can complete the task without confusion or backtracking

Example intro:

"This guide shows how to add JWT authentication to an existing Express app. It assumes you have a working Express server and basic familiarity with middleware."


Reference (information-oriented)
  • Title pattern: Name the thing — "Configuration options", "API endpoints", "CLI flags"
  • Structure: Consistent repeatable format per entry (name → type → default → description → example)
  • State facts; avoid instruction beyond minimal usage examples
  • Keep current; version-stamp if needed
  • Validation: A user can look up a specific fact in under 30 seconds without reading surrounding content

Example entry:

timeout (integer, default: 5000) Maximum time in milliseconds to wait for a response before the request fails. Example: { timeout: 3000 }


Explanations (understanding-oriented)
  • Title pattern: Frame as a concept — "How X works", "Understanding Y", "Why Z is designed this way"
  • Structure: Context → Core concept → Alternatives/trade-offs → Higher-level perspective
  • Avoid step-by-step instruction or technical specification
  • Validation: After reading, the user can explain the concept in their own words and understands the rationale behind design decisions

Example intro:

"Authentication and authorisation are often confused. This page explains the distinction, why both matter, and how common patterns (sessions, tokens, OAuth) approach each concern differently."


Step 3 — Maintain separation and integration

  • Keep each document a single type — don't mix tutorial steps with reference tables or conceptual digressions
  • Cross-link between types: a tutorial can link to the relevant reference page; a how-to guide can link to an explanation for background
  • Use consistent headings and terminology across all types so users can navigate the full documentation system

Step 4 — Validate before delivering

TypeValidation check
TutorialCan a beginner complete it end-to-end without external help?
How-to guideDoes it solve the stated problem for an experienced user?
ReferenceCan the user find a specific fact in under 30 seconds?
ExplanationDoes the user understand the why, not just the what?

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 Documentation AI skill do?

Creates, structures, and reviews technical documentation following the Diátaxis framework (tutorials, how-to guides, reference, and explanation pages). Use when a user needs to write or reorganize docs, structure a tutorial vs. a how-to guide, build reference docs or API documentation, create explanation pages, choose between Diátaxis documentation types, or improve existing documentation structure. Trigger terms include: documentation structure, Diátaxis, tutorials vs how-to guides, organize docs, user guide, reference docs, technical writing.

Why use Documentation on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mcollina/skills/tree/main/skills/documentation. 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 Documentation?

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 Documentation?

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

Is the Documentation AI skill free?

Yes. It is published on GitHub by mcollina 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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