code-atlas:query

To query a code dependency graph for impact analysis, you execute operations like dependencies_of or transitive_dependents against the semantic graph. This returns a filtered subgraph and a readable summary of matched nodes and edges for architectural risk assessment.

Yes, you can use natural language to find dependents of a code module. The query interprets your natural-language intent and maps it to supported JSON operations like dependents_of, validating the input and returning the relevant dependency subgraph.

The maximum depth allowed when exploring transitive dependencies is 5. The query explicitly clamps the max_depth parameter to a range between 1 and 5, ensuring controlled architectural exploration across code modules without excessive graph traversal.

Yes, the dependency query supports filtering by specific code modules. You can supply a JSON query using the filter operation to return a matched subgraph containing only the targeted nodes and edges, enabling focused architectural change impact assessments.

The best way to assess architectural risk is to run a transitive_dependents query on the target module. This surfaces the full dependency surface across code modules, returning a subgraph and summary that clarify what will be impacted by the change.