What problem does it solve? Random fixes and quick patches waste time, mask underlying issues, and introduce new bugs. This Skill enforces a disciplined debugging methodology that finds the actual root cause before any fix is attempted, even under time pressure or social pressure to just patch the symptom. ## Core Features & Use Cases - Four-Phase Process: Root cause investigation, pattern analysis, hypothesis testing, and verified implementation, with mandatory completion of each phase before proceeding. - Supporting Techniques: Includes root-cause tracing through call stacks, defense-in-depth validation at multiple layers, and condition-based waiting to replace flaky arbitrary timeouts in tests. - Pressure Resistance: Explicit anti-patterns, red flags, and rationalization tables that stop shortcut fixes during emergencies, plus a rule to question the architecture after three failed fix attempts. - Use Case: A test suite has flaky failures caused by race conditions. Instead of adding longer sleep delays, apply condition-based waiting to poll for actual events, trace the failure to its source, and add validation at every layer the bad data passes through. ## Quick Start Ask the AI to debug a failing test or production bug using the systematic-debugging process, starting with root cause investigation before proposing any fix.
