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Documentation Best Practices

Community
Omar-Obando
documentation-best-practices

Use when creating and maintaining project documentation, writing README files, documenting APIs, establishing documentation standards, and building knowledge bases. Includes Markdown, ADRs, API docs, and documentation automation. Based on software documentation certification standards and technical writing best practices.

Overview

PublisherOmar-Obando
Repositoryqwen-orchestrator
Skill namedocumentation-best-practices
Stars
53
Forks
13
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Omar-Obando on GitHub. Read the source before you install it.

Installation

Install the Documentation Best Practices 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/Omar-Obando/qwen-orchestrator/tree/main/skills/documentation-best-practices
  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/Omar-Obando/qwen-orchestrator.git /tmp/qwen-orchestrator
mkdir -p .claude/skills
cp -r /tmp/qwen-orchestrator/skills/documentation-best-practices .claude/skills/documentation-best-practices
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Documentation Best Practices 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 Best Practices 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 Best Practices 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.

Documentation Best Practices Skill — Comprehensive Documentation Standards

Overview

This skill provides comprehensive guidance for creating and maintaining project documentation, writing README files, documenting APIs, establishing documentation standards, and building knowledge bases. It includes Markdown, ADRs, API docs, and documentation automation. Based on software documentation certification standards and technical writing best practices.

When to Use

Use this skill when:

  • Creating project documentation for new projects
  • Writing README files for repositories
  • Documenting APIs (REST, GraphQL, gRPC)
  • Establishing documentation standards across teams
  • Building knowledge bases for organizations
  • Creating Architecture Decision Records (ADRs)
  • Writing API documentation with OpenAPI/Swagger
  • Setting up documentation automation
  • Creating documentation templates and styles
  • Building documentation websites (Docusaurus, MkDocs)
  • Implementing documentation versioning
  • Creating documentation for different audiences
  • Setting up documentation review processes
  • Implementing documentation quality gates
  • Creating documentation metrics and KPIs
  • Building documentation migration strategies
  • Setting up documentation monitoring
  • Creating documentation training materials
  • Implementing documentation security
  • Creating documentation compliance documentation

Do NOT use this skill when:

  • Writing code implementation (use developer skill)
  • Designing system architecture (use architecture-patterns skill)
  • Writing tests (use testing-strategy skill)
  • Implementing features (use implementer agent)

Documentation Types

1. README Files

Every project, module, and package needs a README.

markdown
# Project Name

**Version:** 1.0.0  
**Status:** Active  
**License:** MIT

## Overview

Brief description of what this project does and why it exists.

## Features

- Feature 1
- Feature 2
- Feature 3

## Quick Start

```bash
# Install dependencies
npm install

# Run development server
npm run dev

# Run tests
npm test
```

Project Structure

project/
├── src/           # Source code
├── tests/         # Test files
├── docs/          # Documentation
└── scripts/       # Automation scripts

Configuration

OptionTypeDefaultDescription
debugbooleanfalseEnable debug mode
portnumber3000Server port
logLevelstringinfoLogging level

API Reference

See API Documentation for complete API reference.

Contributing

See Contributing Guide for details.

License

MIT


### 2. API Documentation

Document all public APIs.

```markdown
# API Documentation

## Base URL

https://api.example.com/v1


## Authentication

All endpoints require authentication via Bearer token.

Authorization: Bearer


## Endpoints

### GET /api/v1/users

Retrieve a list of users.

**Query Parameters:**
- `page` (optional): Page number (default: 1)
- `limit` (optional): Items per page (default: 20)
- `sort` (optional): Sort field (default: name)
- `order` (optional): Sort order (asc/desc, default: asc)

**Response:**
```json
{
  "data": [
    {
      "id": "uuid",
      "name": "string",
      "email": "string"
    }
  ],
  "meta": {
    "page": 1,
    "limit": 20,
    "total": 100,
    "totalPages": 5
  }
}

POST /api/v1/users

Create a new user.

Request Body:

json
{
  "name": "string (required)",
  "email": "string (required)",
  "password": "string (required)",
  "role": "string (optional, default: user)"
}

Response:

json
{
  "id": "uuid",
  "name": "string",
  "email": "string",
  "role": "string",
  "createdAt": "ISO8601"
}

Error Responses

StatusCodeDescription
400INVALID_INPUTRequest validation failed
401UNAUTHORIZEDAuthentication required
403FORBIDDENInsufficient permissions
404NOT_FOUNDResource not found
422VALIDATION_ERRORBusiness rule violation
500SERVER_ERRORInternal server error

### 3. Architecture Decision Records (ADRs)

Document architecture decisions.

```markdown
# ADR-001: Database Technology Selection

**Date:** 2024-01-15
**Status:** Accepted

## Context

We need to choose a database for our ERP system. The system requires:
- ACID compliance
- Complex queries
- High availability
- Scalability

## Options Considered

### PostgreSQL

**Pros:**
- ACID compliant
- Rich query capabilities
- Strong community
- Good performance

**Cons:**
- Scaling requires more effort
- Learning curve for complex features

### MongoDB

**Pros:**
- Easy scaling
- Flexible schema
- Good for document-based data

**Cons:**
- No ACID compliance (until 4.0)
- Complex queries are harder
- Memory usage

### MySQL

**Pros:**
- Well-understood
- Good performance
- Strong community

**Cons:**
- Limited JSON support
- Scaling challenges

## Decision

**We chose PostgreSQL.**

### Rationale

- ACID compliance is critical for ERP
- Complex queries are common in ERP
- Performance is acceptable
- Community support is strong

### Implementation

- Use PostgreSQL 15
- Enable logical replication
- Set up read replicas
- Implement connection pooling

## Consequences

### Positive

- Data integrity guaranteed
- Complex queries supported
- Good performance for our use case

### Negative

- Scaling requires more effort
- Learning curve for team
- More complex setup

## Next Steps

- Set up production database
- Migrate existing data
- Document database schema
- Train team on PostgreSQL

## References

- [PostgreSQL Documentation](https://www.postgresql.org/docs/)
- [Database Selection Study](https://example.com/study)

4. Module Documentation

Document each business module.

markdown
# Module Name

**Version:** 1.0.0  
**Domain:** business-domain  
**Bounded Context:** context-name

## Overview

Brief description of the module's purpose and business value.

## Domain Model

### Entities

- `EntityName` - Description
- `EntityName` - Description

### Value Objects

- `ValueObjectName` - Description
- `ValueObjectName` - Description

## API

### Endpoints

- `GET /module-name/` - Description
- `POST /module-name/` - Description

## Integration

### Dependencies

- `module-a` - Purpose
- `module-b` - Purpose

### Dependencies On

- None

## Testing

- Unit tests: `tests/unit/`
- Integration tests: `tests/integration/`

## Documentation

- `API.md` - API documentation
- `DECISIONS.md` - Architecture decisions
- `TESTING.md` - Testing strategy

Documentation Standards

Markdown Style

markdown
# Headers (PascalCase)

## Section Headers

### Subsections

- Bullet lists
- Numbered lists

`code blocks`

| Tables | Are    | Good |
| ------ | ------ | ---- |
| Use    | them   | for  |
| Data   | tables |      |

> Quotes for emphasis

File Naming

File TypeConventionExample
READMEREADME.mdREADME.md
API DocsAPI.mdAPI.md
ADRADR-001.mdADR-001.md
TestingTESTING.mdTESTING.md
ContributingCONTRIBUTING.mdCONTRIBUTING.md

Documentation Locations

docs/
├── README.md                    # Main README
├── architecture/
│   ├── decisions/              # ADRs
│   │   ├── ADR-001.md
│   │   └── ADR-002.md
│   └── patterns/               # Architecture patterns
│       ├── layered-architecture.md
│       └── ddd.md
├── api/                        # API documentation
│   ├── v1/
│   │   ├── endpoints/
│   │   └── guides/
│   └── README.md
├── modules/                    # Module documentation
│   ├── inventory/
│   │   ├── README.md
│   │   ├── API.md
│   │   └── DECISIONS.md
│   └── sales/
│       └── ...
├── contributing.md             # Contributing guide
├── code-of-conduct.md          # Code of conduct
└── deployment.md               # Deployment guide

Documentation Maintenance

When to Update

  • After any architectural decision
  • When adding new APIs
  • When changing behavior
  • When fixing bugs that change behavior
  • When onboarding new team members

Documentation Review

  • Review PRs include documentation changes
  • Documentation is checked in code review
  • Outdated documentation is flagged

Documentation Tools

Static Site Generators

ToolPurpose
DocusaurusReact-based docs site
MkDocsPython-based docs site
SphinxPython API docs
JSDocJavaScript API docs

API Documentation

ToolPurpose
Swagger/OpenAPIREST API docs
PostmanAPI testing & docs
GraphQL SchemaGraphQL docs

Documentation Automation

ToolPurpose
TypeDocTypeScript API docs
Swagger UIInteractive API docs
Read the DocsHosted documentation

Common Anti-Patterns

❌ Bad: Outdated Documentation

markdown
# ❌ BAD: Outdated example

```typescript
// This example is outdated
const result = oldFunction();
```

✅ GOOD: Updated example

typescript
// Current example
const result = newFunction();

### ❌ Bad: No Examples

```markdown
# ❌ BAD: No examples
The function processes data.

# ✅ GOOD: With examples
The function processes data:

```typescript
const result = processor.process(data);

### ❌ Bad: Too Much Detail

```markdown
# ❌ BAD: Too much detail
1. Open the file
2. Read the content
3. Parse the JSON
4. Validate the schema
5. ...

# ✅ GOOD: Appropriate detail
The function reads and parses a JSON file.

❌ Bad: Missing Status

markdown
# ❌ BAD: No status

# Project Name

Some description...

# ✅ GOOD: With status

# Project Name

**Version:** 1.0.0  
**Status:** Active  
**License:** MIT

Some description...

Documentation Quality Checklist

markdown
## Documentation Quality Checklist

### README Files

- [ ] Clear project description
- [ ] Quick start instructions
- [ ] Project structure overview
- [ ] Configuration options
- [ ] API reference link
- [ ] Contributing link
- [ ] License information

### API Documentation

- [ ] Base URL specified
- [ ] Authentication explained
- [ ] All endpoints documented
- [ ] Request/response examples
- [ ] Error responses documented
- [ ] Rate limiting information

### ADRs

- [ ] Clear context
- [ ] Options considered
- [ ] Decision documented
- [ ] Rationale explained
- [ ] Consequences listed
- [ ] Next steps defined

### Module Documentation

- [ ] Module purpose clear
- [ ] Domain model documented
- [ ] API endpoints listed
- [ ] Integration points defined
- [ ] Testing strategy explained

Real-World Impact

Before this skill:

  • No documentation
  • Outdated docs
  • Hard to onboard
  • Unknown APIs

After this skill:

  • Comprehensive documentation
  • Up-to-date docs
  • Easy onboarding
  • Clear APIs

Cross-References

  • api-design - For API documentation standards
  • designing-architecture - For architecture documentation
  • product-owner - For user story documentation

References

Frequently asked questions

What does the Documentation Best Practices AI skill do?

Use when creating and maintaining project documentation, writing README files, documenting APIs, establishing documentation standards, and building knowledge bases. Includes Markdown, ADRs, API docs, and documentation automation. Based on software documentation certification standards and technical writing best practices.

Why use Documentation Best Practices on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Omar-Obando/qwen-orchestrator/tree/main/skills/documentation-best-practices. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Documentation Best Practices?

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 Best Practices?

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

Is the Documentation Best Practices AI skill free?

Yes. It is published on GitHub by Omar-Obando 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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