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bmad-document-project

Generate architecture diagrams, source tree analysis, and API contracts for brownfield projects.

Updated Mar 16, 2026
Search Tags:#code analysis#documentation#software architecture#AI context#project documentation#brownfield projects
One-click install
npx skills add https://github.com/geekdesign27/travailleursisoles --skill bmad-document-project-geekdesign27
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bmad-document-project
Source: https://github.com/geekdesign27/travailleursisoles/tree/main/_bmad/bmm/workflows/bmad-document-project
Command: npx skills add https://github.com/geekdesign27/travailleursisoles --skill bmad-document-project-geekdesign27

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the comprehensive documentation of brownfield software projects, transforming complex codebases into easily understandable guides for AI and human developers.

Core Features & Use Cases

  • Automated Project Analysis: Scans codebases to identify project structure, technology stack, and architecture.
  • Comprehensive Documentation Generation: Creates detailed documents including architecture, source tree analysis, API contracts, and development guides.
  • AI Context Preparation: Formats documentation to be readily usable by AI agents for tasks like feature planning, migration, and code understanding.
  • Use Case: When faced with a legacy system, use this Skill to generate up-to-date documentation that allows an AI to quickly grasp the system's architecture and suggest improvements or new features.

Quick Start

Use the bmad-document-project skill to document the current project.

Frequently Asked Questions about bmad-document-project

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

FAQPage Schema
How do I document brownfield projects for AI context?▼

To document brownfield projects for AI context, you need to scan the codebase structure, technology stack, and architectural patterns. This process generates detailed output artifacts like architecture diagrams and API contracts to automate AI-driven understanding.

What is the best way to generate project documentation for a legacy codebase?▼

Generating project documentation for a legacy codebase is best achieved by automating the analysis of the source tree and software architecture. This creates comprehensive guides that help both AI agents and human developers grasp the system quickly.

Can I use automated code analysis to create API contracts for existing software?▼

Automated code analysis can be used to create API contracts for existing software by scanning the codebase. It identifies architectural patterns and structural components, formatting the extracted API documentation for AI-driven development planning.

Does this automated documentation approach work with any technology stack?▼

This automated documentation approach works by scanning your codebase to identify the specific project structure and technology stack. It adapts to the existing architectural patterns to generate accurate, comprehensive documentation for your software.

How do I prepare a legacy codebase for AI-driven feature planning?▼

Preparing a legacy codebase for AI-driven feature planning involves generating detailed documentation from code analysis. This creates AI context artifacts like source tree analysis and architecture diagrams, allowing AI to suggest improvements and new features.

When do I need to generate architecture diagrams for brownfield software?▼

You need to generate architecture diagrams for brownfield software when you want to transform complex codebases into understandable guides. This is essential for enabling AI agents to quickly grasp system architecture and support migration tasks.

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