bmad-document-project

Documenting a brownfield project for AI context requires generating index, architecture, and data-model templates from the codebase. This skill produces consistent project docs with YAML frontmatter, enabling fast onboarding and contextual AI guidance for monoliths, monorepos, and multi-part repositories.

Yes, you can document multi-part architectures like monorepos for AI consumption. The skill supports monoliths, monorepos, and multi-part systems by generating per-part inventories and workflow bindings for consistent project documentation.

The output templates generated for brownfield PRD workflows include index, architecture, data models, and API contracts. These comprehensive documentation artifacts support planning and execution for existing codebases.

Yes, YAML frontmatter is mandatory for project documentation discovery. The skill uses a mandatory SKILL.md entry with YAML frontmatter to identify, load, and activate the documentation workflow for AI consumption.

The best way to onboard AI onto an existing codebase is generating consistent project docs with YAML frontmatter-based discovery. This provides AI-contextual documentation including architecture and data models, enabling richer AI reasoning about the system.