Temporal knowledge graph for codebases that captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook.
Enables AI coding agents to retrieve focused context from a local structural code graph, including entities, relationships, Git co-change, and recorded mistakes. It helps inspect relevant code and carry prior session mistakes forward without reading entire files.
Enables AI coding agents to query a local structural code graph for focused context, inspect relationships and impact, and carry recorded mistakes into later sessions.
Enables AI coding agents to efficiently navigate and understand large codebases by providing tools for entry point location, call chain analysis, and impact assessment, reducing context consumption and model costs.
Enables AI coding agents to retrieve bounded, focused context from a local structural code graph, including source entities, Git relationships, and recorded project memory. It supports exploring structure, inspecting callers, callees, and impact, and carrying prior mistakes into later sessions without reading full files.