analyze-codebase

To analyze codebase architecture, apply automatic community detection and cross-file relationship tracing to generate a production-ready map. This process identifies module boundaries and visualizes tightly coupled groups of files to accelerate onboarding and debugging.

Automatic community detection in a codebase is a technique that identifies tightly coupled groups of files and visualizes their coupling. It maps module boundaries by applying algorithms to language-agnostic graphs, revealing the high-level structure and relationships within the repository.

You can trace cross-file relationships in a repository by using tools that list graph stats and architecture overviews. This method follows dependencies across language-agnostic graphs to deliver actionable insights into how different files and modules interact.

Yes, you can generate a wiki and embedding-ready search for your codebase. Analyzing the repository structure produces documentation pages and vector search capabilities, providing quick context and accelerating the onboarding process for new developers.

Codebase architecture mapping works across different programming languages by utilizing language-agnostic graphs. This approach requires access to the repository structure to automatically detect communities and trace relationships regardless of the specific tech stack.

The best way to visualize code coupling and module boundaries is to apply automatic community detection to the codebase. This generates an architecture overview that highlights tightly coupled groups of files, making it easier to understand high-level structure and navigate complex repositories.