Refactoring Scan

To identify refactoring candidates, this skill cross-references code churn, complexity, and stability metrics across large-scale repositories to surface specific functions that are both complex and frequently modified, categorizing technical debt into actionable high, medium, and low priority tiers.

Finding technical debt hotspots involves moving beyond simple keyword search to analyze code history. This skill uses multi-preset scanning to simultaneously evaluate code for mechanical refactoring needs, decomposition candidates, and stability risks by converging multiple metric signals.

Running a refactoring scan requires pointing the agent at your target source directory. The skill then utilizes search-cascade decision trees to execute multi-preset scans, automatically evaluating the codebase and classifying discovered technical debt into prioritized, actionable tiers.

Yes, this refactoring scan is specifically designed to operate across large-scale repositories. It effectively handles high code churn by cross-referencing those churn metrics with complexity and stability data to surface high-value targets for decomposition or simplification.

Unlike standard code complexity checkers that only evaluate static code, this technical debt analysis cross-references code history and churn with complexity and stability metrics to identify refactoring targets that provide the highest maintenance value and stability improvements.