What problem does it solve? Hard bugs and performance regressions resist casual code reading; without a reproducible signal, debugging devolves into guessing. This Skill enforces a disciplined six-phase diagnosis loop that builds a tight, deterministic pass/fail signal before any hypothesis is tested. ## Core Features & Use Cases - Feedback Loop Construction: Ten ranked strategies for building a red-capable repro, from failing tests and curl scripts to headless browser runs, trace replay, fuzz loops, and git bisect harnesses. - Structured Hypothesis Testing: Generates 3-5 ranked, falsifiable hypotheses, then instruments with tagged debug logs or debugger breakpoints, changing one variable at a time. - Regression Lockdown: Writes the regression test before the fix at a correct seam, then runs cleanup with grep-based removal of tagged instrumentation and a post-mortem. - Use Case: A user reports intermittent checkout failures. The Skill guides building a loop that replays the failing request 100 times to raise the reproduction rate, minimises the scenario, tests ranked hypotheses, and lands a fix with a regression test. ## Quick Start Ask the AI to diagnose the bug where the export button throws an error, and have it build a failing reproduction loop before proposing any fix.
