소개
This skill transforms how AI agents handle technical issues by replacing 'guess-and-check' fixes with a scientific debugging framework. It guides the model through systematic root cause investigation, pattern analysis, and minimal hypothesis testing before any code changes are proposed. By prioritizing data flow tracing and evidence gathering across multi-component systems, it prevents the introduction of new bugs and ensures that performance issues, test failures, and production errors are resolved permanently rather than merely patched.
