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init-project

Organize project architecture, conventions, and module details into root and module-level CLAUDE.md files. Add a structure diagram and navigation links, track scanning coverage, and update existing documentation incrementally when the skill runs again.

OriginalShow the original description

初始化项目 AI 上下文,生成/更新根级与模块级 CLAUDE.md 索引

See how to install

Good for

  • Preparing project context for an AI agent
  • Documenting a repository with multiple modules
  • Updating existing CLAUDE.md files
  • Finding areas that need further scanning

Files included (1)

  • SKILL.md2.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

用法

/init-project <项目摘要或名称>

目标

以"根级简明 + 模块级详尽"的混合策略初始化项目 AI 上下文:

  • 在仓库根生成/更新 CLAUDE.md(高层愿景、架构总览、模块索引、全局规范)。
  • 在识别的各模块目录生成/更新本地 CLAUDE.md(接口、依赖、入口、测试、关键文件等)。
  • ✨ 为了提升可读性,会在根 CLAUDE.md 中自动生成 Mermaid 结构图,并为每个模块 CLAUDE.md 添加导航面包屑。

编排说明

步骤 1:调用 get-current-datetime 子智能体获取当前时间戳。

步骤 2:调用一次 init-architect 子智能体,输入:

  • project_summary: $ARGUMENTS
  • current_timestamp: (来自步骤1的时间戳)

执行策略(由 Agent 自适应决定,不需要用户传参)

  • 阶段 A:全仓清点(轻量) 快速统计文件与目录,识别模块根(package.json、pyproject.toml、go.mod、apps/、packages/、services/* 等)。
  • 阶段 B:模块优先扫描(中等) 对每个模块做"入口/接口/依赖/测试/数据模型/质量工具"的定点读取与样本抽取。
  • 阶段 C:深度补捞(按需) 若仓库较小或模块规模较小,则扩大读取面;若较大,则对高风险/高价值路径分批追加扫描。
  • 覆盖率度量与可续跑 输出"已扫描文件数 / 估算总文件数、已覆盖模块占比、被忽略/跳过原因",并列出"建议下一步深挖的子路径"。重复运行 /init-project 时按上次索引做增量更新与断点续扫。

安全与边界

  • 只读/写文档与索引,不改源代码。
  • 默认忽略常见生成物与二进制大文件。
  • 结果在主对话打印"摘要",全文写入仓库。

输出要求

  • 在主对话中打印"初始化结果摘要",包含:
    • 根级 CLAUDE.md 是否创建/更新、主要栏目概览。
    • 识别的模块数量及其路径列表。
    • 每个模块 CLAUDE.md 的生成/更新情况。
    • ✨ 明确提及"已生成 Mermaid 结构图"和"已为 N 个模块添加导航面包屑"。
    • 覆盖率与主要缺口。
    • 若未读全:说明"为何到此为止",并列出推荐的下一步(例如"建议优先补扫:packages/auth/src/controllers")。

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