Generating Documentation

Documentation Generation

Generate comprehensive technical documentation across multiple layers: API documentation, code documentation, documentation sites, architecture decisions, and system diagrams.

When to Use This Skill

Use this skill when:

• Documenting REST or GraphQL APIs with OpenAPI specifications
• Creating code documentation for libraries (TypeScript, Python, Go, Rust)
• Building documentation sites for projects or products
• Recording architectural decisions (ADRs) for system design choices
• Generating diagrams to visualize system architecture or data flows
• Setting up automated documentation pipelines in CI/CD

Documentation Layers Overview

Technical documentation operates at five distinct layers:

Layer 1: API Documentation - OpenAPI specs for REST/GraphQL APIs (Swagger UI, Redoc, Scalar) Layer 2: Code Documentation - Generated from code comments (TypeDoc, Sphinx, godoc, rustdoc) Layer 3: Documentation Sites - Comprehensive guides and tutorials (Docusaurus, MkDocs) Layer 4: Architecture Decisions - ADRs using MADR template format Layer 5: Diagrams - Visual architecture (Mermaid, PlantUML, D2)

See references/api-documentation.md, references/code-documentation.md, and references/documentation-sites.md for detailed guides.

Quick Decision Framework

Which Documentation Layer?

Copy code
API for external consumers?
  → Layer 1: API Documentation (OpenAPI + Swagger UI/Redoc)

Code for maintainers?
  → Layer 2: Code Documentation (TypeDoc/Sphinx/godoc/rustdoc)

Comprehensive guides?
  → Layer 3: Documentation Site (Docusaurus/MkDocs)

Architectural decision?
  → Layer 4: ADR (MADR template)

Visual system design?
  → Layer 5: Diagrams (Mermaid/PlantUML/D2)

Tool Selection Matrix

API Documentation Quick Start

Create OpenAPI specification:

yamlCopy code
openapi: 3.1.0
info:
  title: User API
  version: 1.0.0

servers:
  - url: https://api.example.com/v1

paths:
  /users/{userId}:
    get:
      summary: Get a user
      parameters:
        - name: userId
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/User'

components:
  schemas:
    User:
      type: object
      required: [id, email, name]
      properties:
        id:
          type: string
        email:
          type: string
          format: email
        name:
          type: string

  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT

security:
  - bearerAuth: []

Render with Swagger UI, Redoc, or Scalar. See references/api-documentation.md for complete examples and templates/openapi-template.yaml for starter template.

Code Documentation Quick Start

TypeScript

typescriptCopy code
/**
 * Calculate the sum of two numbers.
 *
 * @param a - The first number
 * @param b - The second number
 * @returns The sum of a and b
 *
 * @example
 * ```typescript
 * const result = add(2, 3);
 * console.log(result); // 5
 * ```
 */
export function add(a: number, b: number): number {
  return a + b;
}

Generate docs:

bashCopy code
npm install -D typedoc
npx typedoc --entryPoints src/index.ts --out docs

Python

pythonCopy code
def calculate_total(items: list[dict], tax_rate: float = 0.0) -> float:
    """Calculate the total price including tax.

    Args:
        items: List of items with 'price' and 'quantity' keys.
        tax_rate: Tax rate as decimal (e.g., 0.1 for 10%).

    Returns:
        Total price including tax.

    Example:
        >>> items = [{'price': 10, 'quantity': 2}]
        >>> calculate_total(items, tax_rate=0.1)
        22.0
    """
    subtotal = sum(item['price'] * item['quantity'] for item in items)
    return subtotal * (1 + tax_rate)

Generate docs:

bashCopy code
pip install sphinx sphinx-rtd-theme
sphinx-quickstart docs
cd docs && make html

See references/code-documentation.md for Go and Rust examples.

Documentation Site Quick Start

Docusaurus

bashCopy code
npx create-docusaurus@latest my-website classic
cd my-website
npm start

Basic config:

javascriptCopy code
// docusaurus.config.js
module.exports = {
  title: 'My Project',
  url: 'https://docs.example.com',
  themeConfig: {
    navbar: {
      items: [
        {type: 'doc', docId: 'intro', label: 'Docs'},
      ],
    },
  },
  presets: [
    ['@docusaurus/preset-classic', {
      docs: {
        sidebarPath: require.resolve('./sidebars.js'),
      },
    }],
  ],
};

MkDocs

bashCopy code
pip install mkdocs mkdocs-material
mkdocs new my-project
mkdocs serve

Basic config:

yamlCopy code
# mkdocs.yml
site_name: My Project
theme:
  name: material
  features:
    - navigation.tabs
    - search.suggest

plugins:
  - search

nav:
  - Home: index.md
  - Getting Started: getting-started.md

See references/documentation-sites.md for versioning and deployment.

Architecture Decision Records

Use MADR template for recording decisions:

markdownCopy code
# Use PostgreSQL for Primary Database

* Status: accepted
* Deciders: Engineering Team, CTO
* Date: 2025-01-15

## Context and Problem Statement

Application requires relational database with complex queries,
ACID transactions, JSON support, and full-text search.

## Decision Drivers

* Data integrity (ACID compliance)
* Performance (10K+ queries/second)
* Cost (open-source preferred)
* Features (JSONB, full-text search)

## Considered Options

* PostgreSQL
* MySQL
* Amazon Aurora

## Decision Outcome

Chosen "PostgreSQL" for best balance of features and cost.

### Positive Consequences

* Open-source with no licensing costs
* Advanced features (JSONB, full-text search)
* Strong ACID compliance

### Negative Consequences

* Self-hosting requires DevOps investment
* Horizontal scaling requires changes

Copy full template from templates/adr-template.md. See references/adr-guide.md for workflow and examples/adr/0001-database-selection.md for complete example.

Diagrams Quick Start

Create diagrams with Mermaid:

markdownCopy code
```mermaid
sequenceDiagram
    User->>Frontend: Click "Login"
    Frontend->>API: POST /auth/login
    API->>Database: Verify credentials
    Database-->>API: User found
    API-->>Frontend: JWT token
    Frontend->>User: Redirect to dashboard
```

Mermaid renders in GitHub, Docusaurus, and MkDocs. See references/diagram-generation.md for PlantUML and D2 examples.

Common Patterns

Design-First vs Code-First APIs

Design-First:

1. Write OpenAPI spec
2. Review with stakeholders
3. Generate server stubs
4. Implement handlers

Pros: Contract before implementation, parallel development Cons: Spec authoring can be verbose

Code-First:

1. Implement API with decorators
2. Generate OpenAPI from code
3. Publish documentation

Pros: Faster development, spec matches code Cons: Documentation lags behind

Recommendation: Design-first for new APIs, code-first for existing.

Embedding API Docs in Sites

Docusaurus integration:

javascriptCopy code
// docusaurus.config.js
plugins: [
  ['docusaurus-plugin-openapi-docs', {
    config: {
      api: {
        specPath: 'openapi/api.yaml',
        outputDir: 'docs/api',
      },
    },
  }],
],
themes: ['docusaurus-theme-openapi-docs'],

See references/api-documentation.md for MkDocs integration.

CI/CD Automation

yamlCopy code
# .github/workflows/docs.yml
name: Documentation

on:
  push:
    branches: [main]

jobs:
  build-deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4

      - name: Generate API docs
        run: npm run docs:api

      - name: Generate code docs
        run: npm run docs:code

      - name: Build site
        run: npm run docs:build

      - name: Deploy to GitHub Pages
        uses: peaceiris/actions-gh-pages@v3
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          publish_dir: ./build

See references/ci-cd-integration.md for validation and versioning.

When to Write an ADR

Write ADRs for:

✅ Technology selection (database, framework, cloud) ✅ Architecture patterns (microservices, event-driven) ✅ Decisions with trade-offs (pros/cons) ✅ Team alignment needed

Don't write ADRs for:

❌ Trivial decisions (naming, formatting) ❌ Easily reversible (config tweaks) ❌ Implementation details (document in code)

See references/adr-guide.md for workflow and examples.

Reference Documentation

For detailed guides:

• references/api-documentation.md - OpenAPI, Swagger UI, Redoc, Scalar, design-first vs code-first
• references/code-documentation.md - TypeDoc, Sphinx, godoc, rustdoc with examples
• references/documentation-sites.md - Docusaurus and MkDocs setup, versioning, deployment
• references/adr-guide.md - MADR template, workflow, when to write ADRs
• references/diagram-generation.md - Mermaid, PlantUML, D2 syntax and integration
• references/ci-cd-integration.md - Automation, validation, deployment strategies

Templates

• templates/adr-template.md - MADR template for Architecture Decision Records
• templates/openapi-template.yaml - OpenAPI 3.1 specification starter

Examples

• examples/openapi/ - Complete OpenAPI specifications
• examples/typescript/ - TypeDoc configuration and TSDoc examples
• examples/python/ - Sphinx configuration and docstring examples
• examples/adr/ - Real-world Architecture Decision Records
• examples/diagrams/ - Mermaid, PlantUML, D2 examples

Tool Recommendations

Based on research (December 2025):

Documentation Sites:

• Docusaurus - React-based, feature-rich (versioning, i18n, search)
• MkDocs Material - Python-based, simple, beautiful

API Documentation:

• Swagger UI - Interactive testing
• Redoc - Beautiful read-only
• Scalar - Modern 2025 design

Code Documentation:

• TypeScript: TypeDoc
• Python: Sphinx
• Go: godoc (built-in)
• Rust: rustdoc (built-in)

Diagrams:

• Mermaid - Most popular, GitHub-integrated
• PlantUML - UML standard
• D2 - Modern, declarative

Integration with Other Skills

• api-patterns - API implementation and documentation
• building-ci-pipelines - Automate documentation generation
• testing-strategies - Document test patterns
• sdk-design - Generate SDK documentation

Best Practices

1. Docs-as-Code - Keep docs in version control
2. Single Source of Truth - Generate from code/specs
3. Automation - Generate in CI/CD pipelines
4. Examples - Include working code examples
5. Validation - Lint Markdown, validate specs
6. Versioning - Version docs with releases
7. Consistency - Use consistent terminology
8. Maintenance - Update when code changes

Common Pitfalls

Documentation Drift - Docs become outdated → Automate generation, validate in CI/CD

Over-Documentation - Documenting obvious behavior → Focus on "why" not "what"

Fragmented Docs - Information scattered → Single site with clear navigation

No Examples - Theory without practice → Include runnable examples