Token导航 LogoToken导航TokenDH.com
研究检索敏感数据github未标认证来源可访问clear审计通过

generating-documentation生成文档

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

552

周安装

23

GitHub Stars

350

下载量

184
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:generating-documentation(生成文档)
来源仓库:https://github.com/ancoleman/ai-design-components
仓库路径:skills/generating-documentation
安装命令:
npx skills add https://github.com/ancoleman/ai-design-components --skill generating-documentation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/ancoleman/ai-design-components --skill generating-documentation

简介

用于辅助文档、README 和 Markdown 内容的整理与改写。

  • 可提炼结构、补齐章节或统一术语风格。
  • 通过 npx skills add 命令从 GitHub 仓库安装。
  • 使用时应保留项目已有事实,避免将未确认信息写成确定结论。
  • generating-documentation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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?

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

NeedPrimary ToolBest For
Doc SiteDocusaurusFeature-rich React sites
Doc SiteMkDocs MaterialSimple Python docs
API Docs (Interactive)Swagger UITesting
API Docs (Read-Only)RedocProfessional design
TypeScriptTypeDocAll TS projects
PythonSphinxAll Python projects
GogodocBuilt-in
RustrustdocBuilt-in
DiagramsMermaidAll-purpose

API Documentation Quick Start

Create OpenAPI specification:

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

/**
 * 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:

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

Python

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:

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

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

Basic config:

// 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

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

Basic config:

# 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:

# 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:

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:

// 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

# .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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenCode

28.51%
按下载量换算52

Gemini CLI

23.71%
按下载量换算44

Antigravity

15.13%
按下载量换算28

Claude Code

12.36%
按下载量换算23

roo

7.97%
按下载量换算15

Cursor

3.63%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

继续浏览同类 Skills