What problem does it solve? When standard troubleshooting fails, quick guesses and drive-by fixes waste time and often make bugs worse. This Skill enforces a methodical debugging protocol that gathers evidence, tests hypotheses, and verifies fixes before declaring an issue resolved. ## Core Features & Use Cases - Evidence-First Investigation: Documents exact errors, reproduction steps, and actual vs expected behavior before proposing any solution. - Hypothesis Testing Protocol: Forms falsifiable hypotheses, designs minimal tests for each, and eliminates causes based on evidence rather than intuition. - Domain Expertise Loading: Detects the project type (Python, Rust, Swift, Unity, etc.) and loads matching domain-specific debugging knowledge from expertise skills. - Bias Countermeasures: Treats code you wrote yourself with extra skepticism, since assumptions about "how it should work" blind you to actual implementation errors. - Use Case: A developer has a flaky test that passes locally but fails in CI. Instead of retrying random fixes, the Skill maps the execution path, forms hypotheses about environment differences, tests each one, and confirms the root cause with a verified minimal fix. ## Quick Start Ask the AI to debug a stubborn issue using the debug-like-expert method, providing the exact error message and reproduction steps.
