What is an AGENTS.md file?

An AGENTS.md file is a specialized documentation file that provides AI coding agents with specific context, coding patterns, and search commands tailored to a specific directory or project.

How does the hierarchical structure improve AI performance?

It uses a 'nearest-wins' logic, ensuring the AI reads the most granular and relevant instructions for the file it's currently editing, which prevents context pollution and saves tokens.

Can this skill handle monorepos?

Yes, the skill is designed to analyze monorepos and automatically identify major directories like apps, services, and packages that require individual AGENTS.md files.

What is JIT indexing in the context of this skill?

JIT (Just-In-Time) indexing provides the AI with specific search commands (like ripgrep) instead of full file content, allowing the agent to find necessary information dynamically while keeping the documentation lightweight.

AGENTS.md Generator

Name: AGENTS.md Generator
Author: julianromli

byjulianromli

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123

学習とドキュメンテーション

Generates hierarchical, token-efficient documentation structures optimized for AI coding assistants to navigate and understand complex codebases.

概要

The agents-md-generator skill automates the creation of a tiered documentation system designed specifically for AI agents like Claude Code and Droid. By implementing a 'nearest-wins' hierarchy with a lightweight root file and detailed sub-folder AGENTS.md files, it provides AI assistants with actionable project context, coding patterns, and Just-In-Time (JIT) indexing commands without exhausting token limits. This skill is essential for developers looking to optimize their repository for AI-assisted development, ensuring agents follow specific project conventions, security protocols, and testing standards.

主な機能

Hierarchical documentation architecture (Root + Sub-folders)
123 GitHub stars
JIT indexing via pre-configured search commands (ripgrep, find)
Specialized templates for UI, Databases, APIs, and Testing
Automated repository tech stack and pattern analysis
Token-efficient 'Nearest-wins' context strategy

ユースケース

Onboarding AI agents to a complex monorepo with multiple frameworks
Standardizing coding patterns and 'Definition of Done' for AI-assisted PRs
Optimizing large codebases for better AI context understanding with minimal token usage

概要

主な機能

Hierarchical documentation architecture (Root + Sub-folders)
123 GitHub stars
JIT indexing via pre-configured search commands (ripgrep, find)
Specialized templates for UI, Databases, APIs, and Testing
Automated repository tech stack and pattern analysis
Token-efficient 'Nearest-wins' context strategy

ユースケース

Onboarding AI agents to a complex monorepo with multiple frameworks
Standardizing coding patterns and 'Definition of Done' for AI-assisted PRs
Optimizing large codebases for better AI context understanding with minimal token usage