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Agent Skill · 研究检索

agents-md-generator(特工 MD 生成器)

agents-md-generator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

agents-md-generator 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 47,767。

总安装 720周安装 30GitHub Stars 56下载 240核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:agents-md-generator(特工 MD 生成器)
来源仓库:https://github.com/thienanblog/awesome-ai-agent-skills
仓库路径:skills/agents-md-generator
安装命令:
npx skills add https://github.com/thienanblog/awesome-ai-agent-skills --skill agents-md-generator
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/thienanblog/awesome-ai-agent-skills --skill agents-md-generator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

agents-md-generator 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。通过 npx 命令从指定 GitHub 仓库安装并使用。安装前需确认权限范围、维护状态及是否触发联网或文件操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/agents-md-generator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/thienanblog/awesome-ai-agent-skills --skill ag…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agents-md-generator 怎么安装?

在终端执行 npx skills add https://github.com/thienanblog/awesome-ai-agent-skills --skill agents-md-ge…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agents-md-generator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agents-md-generator 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

agents-md-generator 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

agents-md-generator 用的人多吗?

公开数据是累计安装 720 次,近一周安装 30 次,下载 240 次,GitHub 56 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agents-md-generator 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agents-md-generator

特工 MD 生成器 · 本页

72056调用外部服务MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

AGENTS.md / CLAUDE.md Generator

Overview

This skill helps you generate comprehensive instruction files (CLAUDE.md or AGENTS.md) that teach AI coding agents how to work effectively in your project. It combines automatic project scanning with interactive questions to create tailored guidelines.

When to use this skill:

  • Setting up a new project for AI-assisted development
  • Updating existing instruction files after project changes
  • Standardizing AI agent behavior across team members
  • Migrating from one AI tool to another

Key Principle

Do not duplicate specialized skills. If a request falls into a specialized domain (e.g., Design System), delegate to the specialized skill when available.

Quick Start

To generate a new CLAUDE.md file:

  1. Navigate to your project root
  2. Tell the AI agent: "Use the agents-md-generator skill to create a CLAUDE.md file"
  3. Answer the interactive questions about your project
  4. Review and customize the generated file

Answering Questions (Convenient Formats)

When this skill asks numbered questions with lettered options, users can answer in any style:

  • Short form (fast): 1a 2b 3c
  • Mixed form: 1a 2b 3c 4b (also scan packages/*) 5d
  • Full sentences: “Use medium scan depth and Docker Compose; service name is app.”

Short form is never required; it is only provided for convenience.

Generation Modes

Interactive Mode (Default):

  • Guides you through each phase with questions
  • Best for first-time setup or complex projects
  • Maximum customization

Quick Mode:

  • Tell the AI: "Generate CLAUDE.md in quick mode"
  • Skips all questions, uses auto-detection only
  • Best for experienced users or simple projects
  • Uses Medium scan depth by default
  • Generates all standard sections based on detection

Interactive Workflow

Phase 1: Initialization & Discovery

Check for existing files:

  1. Look for CLAUDE.md or AGENTS.md in the project root
  2. If found, ask user: "I found an existing [filename]. Would you like to:"

1. Update it (merge new content while preserving customizations) 2. Replace it (generate fresh, backup existing) 3. Cancel - Reply examples (optional): 1 or update; 2 or replace; 3 or cancel

Determine primary file:

  • Default: CLAUDE.md as primary, AGENTS.md as symlink
  • For Windows or if user prefers: Both files with sync header

Phase 1b: Agent Tooling & System Prompt Alignment (Scripted)

Goal: Detect AI tool instruction files, global system prompts, and MCP configs using scripts (not AI scanning) to save tokens and avoid missing overrides.

Run the detection script (best effort):

  • bash/zsh: bash skills/agents-md-generator/scripts/detect-agent-context --root.
  • Windows cmd: skills\agents-md-generator\scripts\detect-agent-context.cmd --root.

The script should report:

  • Project instruction files for AI tools (Copilot, Cursor, Cline, Kilo Code, Roo Code, OpenCode, Codex, Claude Code)
  • Global instruction files (e.g., ~/.claude/CLAUDE.md, ~/.codex/config.toml, ~/.roo/rules/, ~/.kilocode/rules/)
  • MCP config files and server names (from .mcp.json, .roo/mcp.json, mcp_settings.json, plus any --mcp-path entries)

If script is unavailable:

  • Do a minimal manual check using the paths listed in references/tech-stack-detection.md under AI Agent Tooling Detection.

Warn the user about overrides:

  • If ~/.claude/CLAUDE.md or other global instruction files exist, explicitly warn that they can override project prompts.
  • Ask the user to review or adjust those system prompts to avoid conflicts with this repo.

Ask the user to confirm tool usage:

I detected these AI tool instruction sources:
- .github/copilot-instructions.md (GitHub Copilot)
- .cursorrules (Cursor)
- .clinerules or .clinerules/ (Cline)
- .kilocoderules / .kilo/ / .kilocodemodes (Kilo Code)
- .roo/rules/ / .roo/rules-* / .roorules* (Roo Code)
- opencode.jsonc (OpenCode)
- ~/.codex/config.toml (Codex)
- .claude/CLAUDE.md or ~/.claude/CLAUDE.md (Claude Code)

Which of these do you actively use for this project, and should we align or ignore any of them?

If MCP servers are detected:

  • Ask whether they should be used in this project.
  • Capture a short purpose/usage note for each server.

Phase 1c: Skill Library Duplicate Scan (Scripted)

If a skills/ folder exists, run the duplicate scan script to avoid copy-pasted skills:

  • bash/zsh: bash skills/agents-md-generator/scripts/scan-skill-duplicates --skills-dir skills
  • Windows cmd: skills\agents-md-generator\scripts\scan-skill-duplicates.cmd --skills-dir skills

If duplicates are detected:

  • Recommend consolidating with symlinks so there is one source of truth.
  • Example (macOS/Linux): ln -s./skills/skill-a./skills/skill-b
  • On Windows, recommend a copy with a clear header if symlinks are not supported.

Phase 2: Scan Depth Selection

Ask the user:

What scan depth should I use to analyze your project?

1. Quick (approximately 30 seconds)
   Scans: package.json, composer.json, docker-compose.yml, pyproject.toml,
          Gemfile, go.mod, Cargo.toml, and other root config files
   Best for: When you know your stack well and want fast generation

2. Medium (approximately 1-2 minutes) [RECOMMENDED]
   Scans: Root configs + src/, app/, lib/, config/, routes/, components/,
          pages/, views/, controllers/, models/, services/
   Best for: Most projects - good balance of accuracy and speed

3. Deep (approximately 3-5 minutes)
   Scans: Entire project tree including tests/, docs/, scripts/, all
          subdirectories, hidden configs, and build artifacts
   Best for: Complex projects, monorepos, or unfamiliar codebases

Reply examples:
- Short: `2` (or `1` / `3`)
- With extra notes: `2 (also scan packages/*)`

Scan actions per depth:

DepthFiles ScannedDirectories Explored
QuickRoot configs onlyNone (root level)
MediumConfigs + source headerssrc/, app/, lib/, config/, routes/
DeepAll filesFull tree traversal

Phase 3: Environment Detection

Ask the user:

What development environment does this project use?

1. Docker Compose
   - Commands run via: docker compose exec <service> <command>
   - Example: docker compose exec app php artisan migrate

2. Laravel Sail
   - Commands run via: ./vendor/bin/sail <command>
   - Example: ./vendor/bin/sail artisan migrate

3. Native/Host Machine
   - Commands run directly on your machine
   - Example: php artisan migrate

4. Dev Containers / Codespaces
   - Commands run inside the container environment

5. Other (please describe)
   - Specify your custom environment setup

Reply examples:
- Short: `1` (or `2` / `3` / `4` / `5`)
- Detailed: `1; main service is app; node runs in node service`

Follow-up questions based on selection:

  • Docker: "What is the main service name? (e.g., app, web, php)"
  • Docker: "Do you have separate services for different runtimes? (e.g., app for PHP, node for JS)"
  • Native: "Do you use any version managers? (nvm, rbenv, pyenv, etc.)"

Phase 4: Auto-Detection + Confirmation

Scan the project based on selected depth and detect:

  1. Backend Framework:

- Laravel (composer.json + artisan) - Express/Node (package.json + server files) - Django/Flask (requirements.txt + manage.py/app.py) - Rails (Gemfile + config/routes.rb) - Spring Boot (pom.xml/build.gradle + @SpringBootApplication)

  1. Frontend Framework:

- Vue.js (package.json +.vue files) - React (package.json +.jsx/.tsx files) - Angular (angular.json) - Svelte (svelte.config.js) - Next.js/Nuxt.js (next.config.js/nuxt.config.ts)

  1. Package Manager:

- npm/yarn/pnpm/bun (package-lock.json/yarn.lock/pnpm-lock.yaml/bun.lockb) - Composer (composer.lock) - pip/poetry (requirements.txt/poetry.lock)

  1. Testing Framework:

- PHPUnit (phpunit.xml) - Pest (pestphp/pest in composer.json) - Jest (jest.config.js) - Vitest (vitest.config.ts) - pytest (pytest.ini/conftest.py)

  1. Code Style/Linting:

- Laravel Pint (pint.json) - ESLint (.eslintrc.*) - Prettier (.prettierrc.*) - PHP CS Fixer (.php-cs-fixer.php)

  1. Database:

- MySQL/MariaDB (config references) - PostgreSQL (config references) - SQLite (database/*.sqlite) - MongoDB (mongoose in package.json)

  1. AI Agent Tooling (scripted detection):

- GitHub Copilot (.github/copilot-instructions.md) - Cursor (.cursorrules) - Cline (.clinerules or .clinerules/) - Kilo Code (.kilocoderules, .kilo/, .kilocodemodes, .kilocode/config.json) - Roo Code (.roo/rules/, .roo/rules-*, .roorules*, .roo/mcp.json, mcp_settings.json) - OpenCode (opencode.jsonc, OPENCODE_CONFIG) - Codex (~/.codex/config.toml) - Claude Code (.claude/CLAUDE.md, ~/.claude/CLAUDE.md, .mcp.json)

Present findings to user:

I detected the following tech stack:

Backend:
  - Laravel 11 (high confidence)
  - PHP 8.3 (from composer.json)

Frontend:
  - Vue.js 3 with Composition API (high confidence)
  - TailwindCSS v3 (from package.json)

Testing:
  - Pest PHP (from composer.json)
  - Vitest (from package.json)

Code Style:
  - Laravel Pint (pint.json found)
  - ESLint + Prettier (configs found)

Environment:
  - Docker Compose detected (docker-compose.yml)
  - Services: app, mysql, redis

Is this correct? Would you like to add or modify anything?

Phase 4b: Optional Sections (Interactive Mode Only)

Ask the user about optional sections:

Would you like to include any of these optional sections?

1. CI/CD Configuration
   - Detect: GitHub Actions, GitLab CI, CircleCI, Jenkins
   - Include: Pipeline commands, deployment notes

2. Git Workflow Guidelines
   - Include: Branch naming, commit message format, PR guidelines
   - Detect: .github/PULL_REQUEST_TEMPLATE.md, commitlint config

3. Security Guidelines
   - Include: Env file handling, secrets management, input validation
   - Best practices for the detected stack

4. API Documentation
   - Detect: OpenAPI/Swagger specs, Postman collections
   - Include: Documentation conventions and tooling

5. Mobile App Guidelines (if detected)
   - React Native / Flutter specific patterns
   - Platform-specific considerations

6. Monorepo Guidelines (if detected)
   - Nx / Turborepo / Lerna workspace patterns
   - Package management and dependencies

7. System Prompt Alignment (if detected)
   - Document global or editor-level prompts that can override project rules
   - Remind contributors to review and align prompts

8. MCP Servers & Tooling (if detected)
   - List MCP servers and when to use them
   - Include required environment variables or access notes

9. Project Progress Memory (PROGRESS.md)
   - Ask if the team wants `PROGRESS.md` for continuity across tasks
   - Require an `Original Prompt` section so future runs can compare intent vs current status

Select the sections you need (comma-separated numbers, or 'none' to skip):

Reply examples:
- Short: `none`
- Multiple: `1,3,4`
- With extra notes: `2,3,7 (also include branch naming rules)`

Note: In Quick Mode, these optional sections are skipped unless auto-detected with high confidence.

Phase 5: Section Generation

Generate the following sections based on detected stack and user input:

Section 1: Header & Role
# AI Agent Guidelines & Repository Manual

**Role:** You are an expert Senior [DETECTED_ROLE] and Technical Lead.
You are responsible for the entire lifecycle of a task: understanding,
planning, [STACK_SPECIFIC_RESPONSIBILITIES].

Role detection rules:

  • Laravel only → "Laravel Backend Engineer"
  • Vue/React only → "[Framework] Frontend Engineer"
  • Laravel + Vue/React → "Full-Stack Developer"
  • Node.js backend → "Node.js Backend Engineer"
  • Generic → "Software Engineer"
Section 2: Auto-Pilot Workflow

Generate the 6-step workflow cycle:

  1. Discovery & Context - What to read first, where to find docs
  2. Plan - How to break down tasks, constraints to check
  3. Documentation - When to update docs, what format to use
  4. Implementation - Coding standards, patterns to follow
  5. Verification & Refinement - Testing, linting, manual checks
  6. Self-Review - Checklist of common mistakes to avoid

Each step includes stack-specific instructions from templates.

Section 3: Documentation & Knowledge Base

List paths to important documentation:

## Documentation & Knowledge Base

You are expected to read and adhere to these single sources of truth:

* **[Doc Type]**: `[path/to/doc.md]` ([Brief description])

Auto-detect common paths:

  • docs/, documentation/
  • README.md, CONTRIBUTING.md
  • docs/api/, docs/architecture/
  • Important: Do not list CLAUDE.md or AGENTS.md in this section. These files are already loaded by AI tools, and self-references waste context.
  • For new docs, prefer YAML frontmatter + Markdown body (headings, tables, examples) so metadata and content stay consistent.
Section 4: Project Structure & Architecture

Map the folder structure with purposes:

## Project Structure & Architecture

* **`[folder/]`**: [Purpose description]

Common patterns to detect:

  • MVC structure (controllers, models, views)
  • Feature-based modules
  • Domain-driven design
  • Component-based frontend
Section 5: Development Environment

Based on Phase 3 selection:

## Development Environment

### Container Commands (if Docker)
* App container: `docker compose exec [service] <command>`

### Host Commands
* Git, file operations, IDE commands

### Key Commands
* Format: `[detected formatter command]`
* Test: `[detected test command]`
* Build: `[detected build command]`
Section 6: Coding Standards

Based on detected stack:

## Coding Standards (The "Gold Standard")

* **Language**: [Language] [Version]
* **Framework**: [Framework] [Version]
* **Code Style**: [Style guide/tool]
* **Strictness**: [Type hints, strict mode, etc.]

Include anti-patterns section if applicable:

### Critical Anti-Patterns
- [Stack-specific anti-patterns to avoid]
Section 7: Domain Specifics (Optional)

If the project has specific domain rules detected:

## Domain Specifics & Non-Negotiables

* **[Rule Category]**: [Rule description]

Common domain patterns:

  • Multi-tenant applications
  • Permission/role systems
  • Localization requirements
  • Real-time features
Section 8: CI/CD Configuration (Optional)

If user selected or auto-detected:

## CI/CD & Deployment

### Detected Pipelines
* **GitHub Actions**: `.github/workflows/`
* **GitLab CI**: `.gitlab-ci.yml`

### Pipeline Commands
* Run tests: `[detected command]`
* Build: `[detected command]`
* Deploy: `[detected command]`

### Deployment Notes
* [Environment-specific notes]
Section 9: Git Workflow (Optional)

If user selected:

## Git Workflow

### Branch Naming
* Feature: `feature/<ticket>-<description>`
* Bugfix: `fix/<ticket>-<description>`
* Hotfix: `hotfix/<description>`

### Commit Message Format

type(scope): description

[optional body]

Types: `feat`, `fix`, `docs`, `style`, `refactor`, `test`, `chore`

### Pull Request Guidelines
* Reference ticket/issue in description
* Ensure tests pass before requesting review
* Keep PRs focused and reasonably sized
Section 10: Security Guidelines (Optional)

If user selected:

## Security Guidelines

### Environment Variables
* Never commit `.env` files (only `.env.example`)
* Use secrets management for production
* Rotate credentials regularly

### Input Validation
* Validate all user input at boundaries
* Sanitize data before database queries
* Use parameterized queries (ORM handles this)

### Authentication & Authorization
* [Stack-specific auth patterns]
* Always verify permissions before actions
Section 11: API Documentation (Optional)

If detected or user selected:

## API Documentation

### Documentation Location
* OpenAPI Spec: `[path/to/openapi.yaml]`
* Postman Collection: `[path/to/collection.json]`

### Documentation Standards
* Keep API docs in sync with implementation
* Document all endpoints, request/response schemas
* Include example requests and responses
Section 12: Mobile Guidelines (Optional)

If React Native or Flutter detected:

## Mobile Development

### Platform Considerations
* Test on both iOS and Android
* Handle platform-specific UI patterns
* Consider offline functionality

### Build Commands
* iOS: `[build command]`
* Android: `[build command]`
Section 13: Monorepo Guidelines (Optional)

If monorepo detected:

## Monorepo Structure

### Workspace Management
* Package manager: [pnpm/yarn/npm workspaces]
* Build tool: [Nx/Turborepo/Lerna]

### Package Dependencies
* Use workspace protocol for internal packages
* Keep shared dependencies at root level

### Commands
* Build all: `[command]`
* Build affected: `[command]`
* Test affected: `[command]`
Section 14: System Prompt Alignment (Optional)

If global or editor-level prompts were detected or the user requests it:

## System Prompt Alignment

These prompts can override project instructions. Review and align them with this file:

* **Claude Code Global Prompt**: `~/.claude/CLAUDE.md` (review for conflicts)
* **GitHub Copilot**: `.github/copilot-instructions.md` (project scope)
* **Cursor Rules**: `.cursorrules`
* **Cline Rules**: `.clinerules` or `.clinerules/`
* **Kilo Code Rules**: `.kilocoderules` / `.kilo/` / `.kilocodemodes`
* **Roo Code Rules**: `.roo/rules/` / `.roo/rules-*` / `.roorules*`
* **OpenCode Config**: `opencode.jsonc`
* **Codex Config**: `~/.codex/config.toml`

If any of these conflict with this file, update the global/system prompts first.

### Local AI Tool Folders & Git Hygiene
Remind contributors to keep local AI tool data out of Git:

* Add local folders like `.codex/` and `.claude/` to `.gitignore` because they may contain sensitive prompts, logs, or secrets.
* Put shareable skill packs in `.agents/skills/` so teams can version and share them safely.
Section 15: MCP Servers & Tooling (Optional)

If MCP servers are detected and user opts in:

## MCP Servers & Tooling

Use these MCP servers when the task matches their capability:

* **[server-name]**: [Purpose, when to use it, required env vars]

If a server is not needed for this project, disable it in the MCP config.
Section 16: Project Progress Memory (PROGRESS.md) (Optional)

If the user wants project progress tracking:

## Project Progress Tracking

Use one lightweight progress file that all agents can continue from:

* **Progress**: `PROGRESS.md` (current focus + recent completions)
* **Required field**: `Original Prompt` (copy exact user request that started the task)

At the start of every task, read `PROGRESS.md` first, compare with the active request, and continue unfinished work before starting unrelated changes.

If a memory MCP server is used instead, keep `PROGRESS.md` minimal or omit it.

Phase 6: File Creation/Update

For new files:

  1. Write CLAUDE.md with generated content
  2. Create AGENTS.md as symlink: ln -s CLAUDE.md AGENTS.md
  3. If symlink fails (Windows), create copy with header: <!-- This file mirrors CLAUDE.md. Edit CLAUDE.md as the primary source. -->

For updates (merge mode):

  1. Parse existing file into sections (split by ## headers)
  2. Compare auto-detected findings against existing guidance; if they conflict, ask the user whether to keep existing content, replace it, or merge.
  3. For each section:

- If exists in both: Show diff and ask user preference - If only in existing: Preserve (user customization) - If only in new: Add with note

  1. Generate merged file
  2. Show summary of changes
  3. Ensure the generated content does not instruct the agent to read CLAUDE.md or AGENTS.md, since those files are already loaded by AI tools.

Design System Delegation (Skill Reuse Policy)

This skill is intentionally not a full Design System engine. When the user requests any of the following:

  • "design system", "UI consistency", "style guide"
  • "colors/typography/tokens"
  • "component library rules"
  • "generate DESIGN_SYSTEM.md"

Then this skill must:

If design-system-generator skill is available:

  1. Delegate generation of DESIGN_SYSTEM.md to design-system-generator
  2. Then update AGENTS.md/CLAUDE.md to reference DESIGN_SYSTEM.md with this block:
## Design System
All UI components and pages must follow `DESIGN_SYSTEM.md`:
- Use design tokens (no hardcoded colors/sizes).
- Implement component states (hover/focus/disabled/loading/error).
- Meet accessibility and performance requirements.

If design-system-generator is NOT available:

  1. Suggest installing design-system-generator from:

- https://github.com/thienanblog/awesome-ai-agent-skills (documentation-skills plugin)

  1. Produce only:

- AGENTS.md/CLAUDE.md patch referencing DESIGN_SYSTEM.md - Optional minimal scaffold DESIGN_SYSTEM.md (no deep recommendations)

Minimal Scaffold for DESIGN_SYSTEM.md (only if design-system-generator unavailable)

If the user still wants a file now, generate ONLY this scaffold:

# DESIGN_SYSTEM.md (Scaffold)

## Scope
Defines UI consistency rules for this project.

## Tokens (TBD)
- Colors: CSS variables
- Typography: scale + line-height
- Spacing: spacing scale
- Radius/Shadows: scales

## Components
Define component patterns and required states:
- hover, focus, disabled, loading, error

## Production assets
Use hashed filenames + a manifest mapping to avoid cache issues.
Minify CSS/JS and optimize images/fonts.

Do not pick Tailwind/MUI/shadcn/etc. in the scaffold unless the project already uses it.

Never implement the full Design System logic inside agents-md-generator.

Tech Stack Detection Reference

See references/tech-stack-detection.md for complete detection patterns.

Section Templates Reference

See references/section-templates.md for complete section templates per stack.

Update/Merge Strategy Reference

See references/merge-strategy.md for detailed merge logic.

Progress Tracking (Maintainers)

When discussing or implementing new ideas/features for this skill, use PROGRESS.md as the single continuity file.

Required PROGRESS.md sections:

  • Original Prompt (verbatim user request that initiated the task)
  • Current Status (what is done, in progress, blocked)
  • Next Steps (clear continuation checklist)

Maintainer workflow:

  1. Read PROGRESS.md before starting any task.
  2. Compare Original Prompt and Current Status against the new request.
  3. Continue unfinished work first when it matches the same objective.
  4. Update Current Status and Next Steps before ending the task.

Archiving rule: keep PROGRESS.md readable (about 200-300 lines max). Move old completed entries to docs/archives/PROGRESS-YYYY-MM.md when needed.

Output File Naming

Primary file: CLAUDE.md

  • This is the main instruction file that AI agents read
  • All edits should be made to this file

Secondary file: AGENTS.md

  • Symlink to CLAUDE.md (Unix/macOS/Linux)
  • Or copy with header note (Windows)
  • Provides compatibility with tools expecting AGENTS.md

Why this approach:

  • Single source of truth prevents drift
  • Works across all AI coding tools
  • Follows Claude Code conventions while supporting others

*This skill is part of the awesome-ai-agent-skills community library.*

平台分布

Claude Code

29.16%
按下载量换算70

Antigravity

21.52%
按下载量换算52

Codex

19.23%
按下载量换算46

windsurf

12.74%
按下载量换算31

trae

7.26%
按下载量换算17

OpenCode

3.74%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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