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Rinzler78
Rinzler78COMMUNITY
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bmad-document-project

Classify repository structure and generate markdown documentation for brownfield projects.

1|Updated Dec 22, 2022
Search Tags:#architecture#documentation#codebase analysis#ai context#brownfield#project scanning#resumable workflow
One-click install
npx skills add https://github.com/Rinzler78/osmosis-launcher --skill bmad-document-project-rinzler78
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bmad-document-project
Source: https://github.com/Rinzler78/osmosis-launcher/tree/main/.agents/skills/bmad-document-project
Command: npx skills add https://github.com/Rinzler78/osmosis-launcher --skill bmad-document-project-rinzler78

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill turns an existing codebase into clear, AI-ready project documentation so agents can understand architecture, structure, setup, and implementation details without manual digging.

Core Features & Use Cases

  • Project classification: Detects whether a repository is a monolith, monorepo, or multi-part system and identifies the relevant tech stack.
  • Documentation generation: Produces structured artifacts such as project overviews, source tree analysis, architecture docs, development guides, and optional API or data model docs.
  • Resumable analysis: Tracks progress in a state file so long scans can be resumed safely and consistently.
  • Use case: A developer asks an AI to document a brownfield project before adding a new feature, and this Skill gathers the needed context into a navigable documentation set.

Quick Start

Use this skill to document the current project and generate AI-friendly architecture and setup docs.

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 architecture documentation for an existing brownfield codebase?▼

This Skill scans an existing repository to classify the project structure, analyze the technology stack, and generate navigable markdown architecture and setup documentation for onboarding or planning.

What is the best way to create AI-ready project context for a monorepo?▼

Generating AI-ready context for a monorepo involves classifying the multi-part system structure and producing structured markdown outputs like source tree analysis and architecture docs so agents can understand implementation details without manual digging.

Can I resume a project scanning workflow if my codebase analysis is interrupted?▼

Yes, you can resume an interrupted codebase analysis because this Skill tracks scanning progress in a state file, allowing long repository scans to be safely resumed and consistently executed without restarting.

Does this project documentation tool work with multi-part systems and monoliths?▼

Yes, this project documentation tool works with multi-part systems, monorepos, and single monolith codebases by detecting the repository type and producing tailored development guides, source tree analysis, and integration context.

What limitations should I expect when scanning a large repository for codebase analysis?▼

When scanning large repositories, you should expect that analyzing complex source trees and generating comprehensive architecture docs requires conditional scanning and resumable state tracking to safely manage the workflow without losing progress.

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