codebase-docs-search

Codebase documentation search locates relevant docs in common project locations like docs/, READMEs, and guides to accelerate onboarding. It extracts concise, actionable summaries of patterns and learnings so engineers can quickly understand project architecture and decisions.

Surfacing architectural patterns and learnings is done by retrieving previous decisions from project documentation using frontmatter metadata. This informs current implementation work, reduces duplicate effort, and guides architectural planning by referencing established project guidance.

Searching project READMEs and guides to inform debugging and implementation decisions is supported. The search targets common documentation locations, extracts relevant patterns and learnings, and surfaces project-wide frontmatter metadata to guide future work and reduce duplication.

Project-wide frontmatter metadata helps locate relevant codebase docs by tagging documentation with structured attributes. This metadata is parsed to surface patterns, learnings, and architectural decisions, enabling targeted retrieval of guidance that matches the current engineering task.

Reducing duplicate engineering work across teams is a core use case for codebase documentation search. By surfacing existing learnings, patterns, and decisions from project docs, it prevents redundant implementation efforts and ensures teams reference established architectural guidance.

Limitations of searching codebase docs include reliance on documentation existing in common locations like docs/ and READMEs. If project documentation is sparse, outdated, or lacks structured frontmatter metadata, the search cannot surface meaningful patterns or learnings to guide onboarding and planning.