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bmad-document-project

Generate structured architecture and source-tree documentation for brownfield repositories as Markdown and JSON files.

Updated May 23, 2026
Search Tags:#architecture#documentation#project analysis#brownfield#resumable workflow#source tree
One-click install
npx skills add https://github.com/diegosanchespereira1/lavarapido --skill bmad-document-project-diegosanchespereira1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bmad-document-project
Source: https://github.com/diegosanchespereira1/lavarapido/tree/main/lava-rapido/.agents/skills/bmad-document-project
Command: npx skills add https://github.com/diegosanchespereira1/lavarapido --skill bmad-document-project-diegosanchespereira1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns existing software repositories into structured, AI-ready documentation so agents can understand a codebase quickly without manual reverse-engineering.

Core Features & Use Cases

  • Project Classification: Detects whether a repository is a monolith, monorepo, or multi-part system and maps the relevant documentation workflow.
  • Architecture and Source Analysis: Produces an indexed view of source tree structure, architecture, development setup, deployment details, and optional API or data-model documentation.
  • Resumable Documentation Runs: Tracks progress with a state file so long scans can be resumed safely after interruption.
  • Use Case: Use this Skill when you need to document a brownfield app before planning new features, onboarding an AI agent, or creating a migration-ready knowledge base.

Quick Start

Run the bmad-document-project skill against the repository root to generate AI-ready project documentation and an indexed set of architecture and development guides.

Frequently Asked Questions about bmad-document-project

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

FAQPage Schema
How do I generate AI-ready documentation for an existing codebase?▼

You can document a brownfield repository by running a scan that detects the project type, analyzes conditional files, and outputs structured markdown and JSON artifacts for AI retrieval.

Can I automatically document monorepos and multi-part software systems?▼

Yes, you can automatically document monorepos and multi-part systems through project classification detection that maps the relevant workflow and indexes the architecture and source tree structure.

What is the best way to structure architecture documentation for AI agents?▼

The best way to structure architecture documentation for AI agents is generating indexed markdown files that cover source tree structure, development setup, and deployment details for quick retrieval.

Does this project analysis workflow support resumable scans for large repositories?▼

Yes, the project analysis workflow supports resumable scans for large repositories by tracking progress with a state file, allowing safely interrupted documentation runs to resume.

When do I need to document a brownfield app before planning new features?▼

You need to document a brownfield app before planning new features, onboarding an AI agent, or creating a migration-ready knowledge base to eliminate manual reverse-engineering.

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