propose-decomposition

You can plan a safe codebase refactor by generating a human-readable decomposition proposal that analyzes structure and coverage gaps. This approach surfaces candidate targets and risk callouts while remaining completely inert, requiring a mandatory human checkpoint before any execution.

Polymorphic decomposition is a codebase modularization technique that inspects dependency graphs and coverage gaps to identify safe splitting points. You need it when preparing for harness or genome modularization scenarios and want a controlled, human-gated plan rather than automated refactoring.

To find coverage gaps and coupling hotspots, use dependency graph analysis combined with topic modeling to motivate candidate splits. This process generates a filesystem-backed proposal artifact containing lineage depth estimates and risk callouts for targeted decomposition points.

Yes, you can focus your refactor proposal on a specific codebase section by providing a focus section parameter. This constrains the decomposition analysis to generate targeted candidate targets and risk callouts for the specified area rather than the entire codebase.

Automated decomposition planning in Phase 1 is strictly limited by an inert mode and a depth guard constraint, meaning it cannot execute refactor actions. Additionally, the planning process requires Phase B sensory availability to function and only emits a proposal artifact for human review.

Dependency graph analysis works for generating refactor plans by inspecting the codebase structure to identify coupling hotspots and candidate splits. It produces a filesystem-backed proposal artifact with lineage depth estimates while enforcing governed execution through a mandatory human checkpoint.