analyze

To generate an evidence-backed codebase explanation, analyze the repository across multiple modules and dependencies. The resulting synthesis ranks conclusions by confidence and provides concrete file references to support architectural findings.

Analyzing cross-file impacts requires evaluating behavior causality across modules. This approach produces a ranked synthesis that distinguishes between known facts and interpreted inferences, supported by explicit file-level references.

Yes, you can distinguish evidence from inference. The analysis enforces evidence-vs-inference separation, clearly delineating what is known from what is interpreted and assigning confidence levels to each conclusion.

No, this read-only codebase analysis does not modify your source files. It safely inspects the repository to produce grounded, evidence-backed explanations of behavior and architecture without writing or altering code.

To get confidence-scored conclusions for multi-module dependencies, analyze the repository architecture and behavior. The output provides a ranked synthesis with explicit confidence levels and grounded file references.

You need evidence-vs-inference boundaries when evaluating complex codebases to avoid unsupported assumptions. This process ensures conclusions are grounded with concrete file references and clear confidence levels separating fact from interpretation.