deepinit

Generates hierarchical AGENTS.md documentation for AI agent codebase navigation.

Updated May 20, 2026
One-click install
npx skills add https://github.com/xdkp/oh-my-claudecode --skill deepinit-xdkp
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deepinit
Source: https://github.com/xdkp/oh-my-claudecode/tree/main/skills/deepinit
Command: npx skills add https://github.com/xdkp/oh-my-claudecode --skill deepinit-xdkp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the problem of making large, unfamiliar codebases understandable to AI agents by generating consistent, AI-readable AGENTS.md documentation across directories.

Core Features & Use Cases

  • Hierarchical documentation: Creates AGENTS.md files with correct parent references so navigation and context inheritance are reliable.
  • Comprehensive directory mapping: Scans the directory tree, analyzes each directory’s purpose, and documents key files, subdirectories, working instructions, and dependency notes.
  • Safe regeneration: Detects existing AGENTS.md, updates auto-generated sections, and preserves manual annotations for maintainable long-term use.
  • Use Case: When onboarding a team to a monorepo, run this Skill to produce a complete AGENTS.md hierarchy so agents can quickly locate how to work, test, and modify each part of the repository.

Quick Start

Ask your AI to run the Deepinit Skill to scan the repository and generate or update AGENTS.md files with correct parent references.

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 documentation by running the Skill to recursively map your directory tree, analyze each directory's purpose, and create files with correct parent references for AI agent navigation.

What is the best way to onboard AI agents to a large monorepo?

Onboarding AI agents to a large monorepo requires hierarchical AGENTS.md files that document key files, subdirectories, working instructions, and dependency notes so agents understand modification rules across the repository.

Can I regenerate repository onboarding documentation without losing manual annotations?

Regenerating repository onboarding documentation is safe because the Skill detects existing AGENTS.md files, updates auto-generated sections, and preserves manual annotations for maintainable long-term use.

Does generating AGENTS.md files require specific dependencies or components?

Generating AGENTS.md files requires no external dependencies or components, operating entirely through recursive directory mapping, parent-tag path validation, and prompt instructions within your codebase.

When do I need to regenerate hierarchical AGENTS.md files?

Regenerate hierarchical AGENTS.md files when your codebase structure changes, ensuring AI agents receive updated directory relationships and modification rules during ongoing repository onboarding and agent workflow initialization.