What problem does it solve? Codebases accumulate shallow modules whose interfaces are nearly as complex as their implementations, making them hard to test and hard for AI agents to navigate. This Skill surfaces that architectural friction and proposes concrete deepening refactors instead of vague cleanup advice. ## Core Features & Use Cases - Hot-spot-driven exploration: Scopes the review using git history and user direction, then explores the codebase for shallow modules, seam leakage, and poor locality. - Visual HTML report: Renders each refactor candidate as a self-contained HTML file with Tailwind and Mermaid before/after diagrams, recommendation-strength badges, and ADR conflict callouts, written to the OS temp directory. - Guided decision loop: After the user picks a candidate, runs a grilling workflow to walk constraints and dependencies, updating CONTEXT.md and offering ADRs as decisions crystallize. - Use Case: A team notices their order intake flow bounces across six tiny wrappers. Run this Skill to get a visual report showing the shallowness, pick the top candidate, and grill through the design of one deep module with a single testable interface. ## Quick Start Ask the assistant to review this repository's architecture for deepening opportunities and show the candidates as an HTML report.
