generate-agents-md
Generate or update AGENTS.md for the current project. Use when user asks to create project guidelines, initialize AGENTS.md, or standardize project conventions.
Best use case
generate-agents-md is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Generate or update AGENTS.md for the current project. Use when user asks to create project guidelines, initialize AGENTS.md, or standardize project conventions.
Teams using generate-agents-md should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/generate-agents-md/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How generate-agents-md Compares
| Feature / Agent | generate-agents-md | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate or update AGENTS.md for the current project. Use when user asks to create project guidelines, initialize AGENTS.md, or standardize project conventions.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Generate AGENTS.md — 项目开发规范生成器 > **AGENTS.md** 是 AI 编码 Agent 的行业标准项目指引文件（[agents.md](https://agents.md/)）， > 被 Cursor、Codex、Copilot、Jules、Windsurf、Aider、opencode 等 20+ 工具支持。 > 一份文件，所有 AI 工具通用。 ## When to Use - 用户说"生成 AGENTS.md"、"初始化项目规范"、"创建项目指引" - 用户开始用 OpenAkita 开发一个新项目，还没有 AGENTS.md - 用户说"帮我规范这个项目"、"让 AI 更好地理解这个项目" ## Workflow ### Step 1: 扫描项目结构 使用 `list_directory` 和 `read_file` 收集以下信息： 1. **项目根文件**：检查 `package.json`、`pyproject.toml`、`Cargo.toml`、`go.mod`、`pom.xml`、`Gemfile`、`composer.json` 等，识别语言和框架 2. **README.md**：读取项目描述和现有文档 3. **配置文件**：`.eslintrc*`、`ruff.toml`、`pyproject.toml [tool.ruff]`、`.prettierrc`、`tsconfig.json` 等代码风格配置 4. **CI/CD**：`.github/workflows/`、`.gitlab-ci.yml`、`Jenkinsfile` 等 5. **测试**：`tests/`、`__tests__/`、`spec/`、`test/` 目录；`jest.config.*`、`vitest.config.*`、`pytest.ini`、`conftest.py` 等 6. **目录结构**：顶层目录布局，识别 monorepo（`apps/`、`packages/`、`workspaces`） 7. **现有 AGENTS.md**：如果已存在，读取后在其基础上更新 ### Step 2: 生成 AGENTS.md 按以下模板结构生成，**只写与项目相关的段落**，省略不适用的部分： ```markdown # [Project Name] [一句话描述项目做什么] ## Tech Stack - Language: [语言及版本] - Framework: [框架] - Package Manager: [包管理器] ## Dev Environment Setup [环境准备步骤，如 Python 版本、Node 版本、依赖安装命令] ## Build & Run [构建、启动、热重载等命令] ## Testing [测试框架、运行命令、覆盖率要求] ## Code Style [lint 工具、格式化工具、关键规则] ## Project Structure [关键目录说明，不要列出每个文件] ## Architecture Notes [核心架构设计、数据流、重要模块关系] ## PR & Commit Conventions [提交信息格式、分支策略] ## Known Gotchas [新手容易踩的坑、特殊约定] ``` ### Step 3: 写入文件 使用 `write_file` 写入到项目根目录的 `AGENTS.md`。 ### Step 4: Monorepo 检查 如果检测到 monorepo 结构（`apps/`、`packages/`、`services/` 等子项目），**询问用户**是否需要为子项目也生成嵌套的 AGENTS.md。子项目的 AGENTS.md 只写该子项目特有的内容，不重复根级内容。 ## Important Rules - **控制长度**：AGENTS.md 建议 150 行以内，不要写成完整文档 - **只写有用的**：不要填充模板中每个段落，省略不适用的 - **面向 AI Agent**：内容是给 AI 看的，不需要"入门教程"级别的解释 - **可执行的命令**：构建、测试、lint 等必须是可以直接复制执行的命令 - **不要暴露敏感信息**：不要写 API key、密码、内部 URL 等 - **中英文皆可**：跟随项目的主要语言（README 是中文就用中文） ## Examples 用户说："帮我生成 AGENTS.md" → 执行 Step 1-4，扫描项目后生成文件。 用户说："更新一下 AGENTS.md" → 先读取现有 AGENTS.md，结合项目当前状态更新过时的内容。
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