codedocs

Generating AI-friendly codebase documentation involves orchestrating discovery and module mapping to output a searchable, multi-layered docs suite. This creates an index, overview, and module documents from repository sources for AI agents.

Yes, you can automatically map modules across a polyglot monorepo. The documentation pipeline detects tech-stack boundaries and generates targeted module documentation to help AI agents understand structure and dependencies without reading raw code.

You can incrementally update codebase documentation using diff-based re-generation. When source changes occur, the tool performs targeted module refresh to keep the documentation suite and JSON manifest current without regenerating everything.

A .codedocs.json manifest is a structured file generated alongside an INDEX.md to provide AI agents with a searchable map of a codebase. It helps agents quickly understand structure, dependencies, and cross-cutting patterns without parsing raw code.

Yes, automated codebase documentation can work without external dependencies. The tool independently orchestrates repository discovery, module boundary detection, and pattern documentation to generate the full documentation surface from source files.