codebase-analysis

To generate a knowledge graph from your codebase, this Skill traverses your project directories to map code structures into a JSON file of nodes and edges. It systematically identifies files, directories, and their relationships.

Code structure mapping works by scanning directories to identify repositories, applications, libraries, and files, then translating them into graph nodes. It defines relationships like 'contains', 'uses', and 'dependsOn' as edges between these nodes.

Yes, the code analysis process includes entrypoint detection. It automatically identifies key application entry points such as APIs, pages, and CLIs to provide a clearer architectural overview within the generated knowledge graph.

The best way to map microservice dependencies is to generate a structured knowledge graph JSON. This approach details inter-service relationships and structural properties, helping you identify potential structural issues before deployment.

Yes, the generated knowledge graph is validated against a predefined schema. This ensures the output JSON correctly details nodes, edges, and properties representing your codebase architecture without structural errors.

A limitation of mapping code structure to a knowledge graph is that the output is a static JSON representation of nodes and edges. It requires external tools to visualize the architecture and does not dynamically update without re-running the directory traversal.