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ajianaz
ajianazCOMMUNITY
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docs-generator

Generate AGENTS.md and agent.d documentation for AI coding agents.

4|Updated Dec 4, 2025
Search Tags:#developer tools#documentation#AI agent#monorepo#codebase analysis#agent.d#AGENTS.md
One-click install
npx skills add https://github.com/ajianaz/skills-collection --skill docs-generator-ajianaz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: docs-generator
Source: https://github.com/ajianaz/skills-collection/tree/main/skills/docs-generator
Command: npx skills add https://github.com/ajianaz/skills-collection --skill docs-generator-ajianaz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill generates hierarchical documentation structures (like AGENTS.md, agent.d, or custom formats) for codebases, specifically optimized for AI coding agents. It solves the problem of providing AI with relevant, token-efficient context, reducing the need for extensive manual codebase exploration and improving AI's coding accuracy.

Core Features & Use Cases

  • AI-Optimized Documentation: Create lightweight root documentation with JIT indexing and detailed sub-folder documentation for specific modules.
  • Multiple Formats: Supports AGENTS.md, agent.d, and custom Markdown formats tailored for AI consumption.
  • Codebase Analysis: Automatically analyze repository type, tech stack, and key directories to inform documentation structure.
  • Use Case: "I have a large monorepo and need to generate documentation that helps an AI agent understand its structure, conventions, and key files without overwhelming its context window. This skill will create AGENTS.md files at the root and within each package."

Quick Start

Use the docs-generator skill to generate AGENTS.md documentation for my monorepo, including root and sub-folder files.

Frequently Asked Questions about docs-generator

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

FAQPage Schema
How do I generate documentation for AI agents to understand my codebase?▼

Generate hierarchical documentation structures like AGENTS.md or agent.d files that provide AI agents with token-efficient, contextual information about your codebase. This reduces context window overhead and improves AI coding accuracy by surfacing key conventions, directory structure, and module guidance without manual exploration.

Can I create AI-optimized documentation for a monorepo with multiple packages?▼

Yes. Generate root-level AGENTS.md files alongside per-package documentation across monorepos and multi-package projects. The skill analyzes repository structure and tech stack to create hierarchical docs that help AI agents navigate complex layouts efficiently.

What documentation formats does codebase analysis support for AI agents?▼

Codebase analysis supports AGENTS.md, agent.d, and custom Markdown formats tailored for AI consumption. Each format is optimized for lightweight root docs with JIT indexing and detailed sub-folder guidance to balance coverage and token efficiency.

How does documentation help AI agents work with large codebases?▼

AI-optimized documentation provides contextual, token-efficient guidance that helps agents understand repository conventions, identify key files, and navigate structure without overwhelming their context window. This accelerates code comprehension and reduces errors in multi-package or monorepo environments.

Do I need to manually configure documentation structure for different project layouts?▼

No. The skill automatically analyzes repository type, tech stack, and key directories to inform documentation structure. It adapts to single-repo, multi-package, and monorepo setups, generating appropriate AGENTS.md and agent.d files with minimal configuration.

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