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init-project

Inspect a project and create or update CLAUDE.md files that give an AI agent project context. Summarize architecture and shared rules at the root, document individual modules, and report diagrams, navigation links, and scanning gaps.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Initialize project AI context, generate/update root-level and module-level CLAUDE.md indexes

查看安装方法

适用场景

  • Prepare project context for an AI agent
  • Document module interfaces and dependencies
  • Visualize project structure with Mermaid
  • Update documentation after project changes

包含的文件(1)

  • SKILL.md2.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Usage

/init-project <PROJECT_SUMMARY_OR_NAME>

Objective

Initialize project AI context using a mixed strategy of "concise at root + detailed at module level":

  • Generate/update CLAUDE.md at repository root (high-level vision, architecture overview, module index, global standards).
  • Generate/update local CLAUDE.md in identified module directories (interfaces, dependencies, entry points, tests, key files, etc.).
  • ✨ For improved readability, automatically generate Mermaid structure diagrams in the root CLAUDE.md and add navigation breadcrumbs to each module CLAUDE.md.

Orchestration Instructions

Step 1: Call the get-current-datetime sub-agent to obtain the current timestamp.

Step 2: Call the init-architect sub-agent once, with input:

  • project_summary: $ARGUMENTS
  • current_timestamp: (timestamp from step 1)

Execution Strategy (Agent adapts automatically, no user parameters needed)

  • Stage A: Repository Census (Lightweight) Quickly count files and directories, identify module roots (package.json, pyproject.toml, go.mod, apps/, packages/, services/*, etc.).
  • Stage B: Module Priority Scanning (Medium) For each module, perform targeted reading and sampling of "entry/interfaces/dependencies/tests/data models/quality tools".
  • Stage C: Deep Supplementation (As Needed) If repository is small or module scale is small, expand reading scope; if large, perform batch supplemental scanning on high-risk/high-value paths.
  • Coverage Measurement and Resumability Output "scanned files / estimated total files, covered module ratio, ignored/skipped reasons" and list "recommended next-step deep-dive sub-paths". When running /init-project repeatedly, perform incremental updates and breakpoint resumable scanning based on previous index.

Security and Boundaries

  • Only read/write documentation and indexes, do not modify source code.
  • Ignore common generated artifacts and binary large files by default.
  • Print "summary" in main dialog, write full content to repository.

Output Requirements

  • Print "Initialization Result Summary" in main dialog, including:
    • Whether root-level CLAUDE.md was created/updated, major section overview.
    • Number of identified modules and their path list.
    • Generation/update status of each module's CLAUDE.md.
    • ✨ Explicitly mention "Generated Mermaid structure diagram" and "Added navigation breadcrumbs for N modules".
    • Coverage and major gaps.
    • If not fully read: explain "why stopped here" and list recommended next steps (e.g., "suggest priority supplemental scanning: packages/auth/src/controllers").

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