What problem does it solve? Debugging often devolves into guessing, shotgun changes, and symptom patches that leave the real root cause active. This Skill enforces a disciplined investigate-before-fixing workflow that traces the full causal chain from trigger to symptom before any code is changed. ## Core Features & Use Cases - Phased investigation framework: Triage, reproduce, trace the code path, form evidence-grounded hypotheses with testable predictions, then fix test-first with workspace safety checks. - Issue tracker integration: Fetches full issue threads from GitHub, Linear, or Jira to extract symptoms, reproduction steps, and prior failed attempts. - Deep reference playbooks: Covers anti-patterns (shotgun debugging, confirmation bias), intermittent bugs, race conditions, heisenbugs, git bisect, and defense-in-depth layering. - Use Case: A user pastes a failing CI stack trace. The Skill reproduces the failure, instruments component boundaries to localize the fault, confirms the root cause with a prediction, writes a failing regression test, applies the minimal fix, and opens a PR that auto-closes the linked issue. ## Quick Start Ask the AI to debug the pasted error message, failing test path, or issue reference and find its root cause before fixing it.