bmad-document-project

To generate AI-ready documentation for a brownfield project, this skill discovers your project structure and produces comprehensive docs including index, architecture, data models, API contracts, and deployment notes for existing codebases.

Documenting a monorepo with multi-part architectures requires mapping integration points across project parts. This skill detects your project type and generates multi-part architecture and integration documentation for complex codebases.

Automatic project type detection for codebase documentation works by analyzing the repository structure to identify frameworks and patterns, enabling the generation of tailored machine-readable metadata like index and deep-dive docs.

Yes, you can produce API contracts and data models for an undocumented codebase. The skill applies a documentation workflow that extracts these details to provide actionable AI context for brownfield PRD workflows.

The brownfield PRD documentation workflow generates a complete set of AI-ready outputs, specifically an index, architecture overviews, data models, API documentation, and deployment notes for the repository.

No, you do not need to manually structure index files. The skill automatically generates machine-readable metadata including index and project-parts documents to map multi-part integration points.