deepinit

Generate hierarchical AGENTS.md files with parent-path references and validation.

Updated Apr 17, 2026
One-click install
npx skills add https://github.com/dropsyoon/oh-my-claudecode --skill deepinit-dropsyoon
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deepinit
Source: https://github.com/dropsyoon/oh-my-claudecode/tree/main/skills/deepinit
Command: npx skills add https://github.com/dropsyoon/oh-my-claudecode --skill deepinit-dropsyoon

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

deepinit eliminates the time-consuming effort of manually documenting a codebase so that AI agents can reliably understand directories, relationships, and how to operate safely in each area.

Core Features & Use Cases

  • Hierarchical documentation generation: Creates comprehensive AGENTS.md files across the repository using parent-path references for navigable structure.
  • Update-and-preserve workflow: When AGENTS.md already exists, it regenerates auto sections while preserving manual sections marked for retention.
  • Validation of doc integrity: Verifies that parent references resolve, no AGENTS.md files become orphaned, coverage is complete, and timestamps are current.

Quick Start

Use the deepinit skill on your repository to generate a full set of hierarchical AGENTS.md files that reflect the current directory structure.

Frequently Asked Questions about deepinit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate hierarchical AGENTS.md documentation for my codebase?

Generate hierarchical AGENTS.md files by mapping a repository's directory structure and inter-relationships for agent navigation. It produces level-ordered documents using parent-path references to ensure navigable structure across the codebase.

Why does my AI agent fail to understand my repository's directory relationships?

AI agents fail without AI-readable documentation mapping directory relationships. Generating hierarchical AGENTS.md files provides agents with correct parent references and section semantics so they can navigate and operate safely within each area.

Can I regenerate AGENTS.md files without losing my manual annotations?

Yes, when AGENTS.md already exists, the regeneration workflow updates auto sections while preserving manual sections marked for retention. This update-and-preserve approach maintains custom annotations alongside refreshed structural mapping.

What's the best way to onboard an AI agent to a complex codebase structure?

Onboard AI agents by generating hierarchical AGENTS.md documentation that maps the repository's directory structure. This provides agents with navigable parent-path references and section semantics for correct operation across the codebase.

How does AGENTS.md validation verify parent link resolution and documentation completeness?

Validation of AGENTS.md integrity verifies that parent references resolve correctly, no AGENTS.md files become orphaned, directory coverage is complete, and timestamps remain current before the documentation generation process finishes.

When do I need to regenerate codebase documentation for agent workflows?

Regenerate codebase documentation during codebase bootstrapping, after structural changes, or for onboarding. This ensures AGENTS.md files reflect the current directory structure and maintain valid parent references for agent navigation.