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Systematic methodology for debugging bugs, test failures, and unexpected behavior.
Passed 18 of 22 test cases with the skill, and 11 of 22 without it.
and 6 more in the full report
7 fixed11 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
I've attempted three different patches to stop our worker queue from hanging on large jobs, but each patch just creates a new memory leak or race condition somewhere else in the worker module. Please help me approach this properly. Generate a comprehensive troubleshooting report that evaluates why prior fixes didn't work, evaluates if our current queue architecture itself is fundamentally flawed, and outlines a rigorous step-by-step diagnostic path to locate the true root problem.
| Checked | Without skill | With skill |
|---|---|---|
| The response advises stopping further code patches to evaluate the fundamental worker queue architecture. | Passed | Passed |
| The response refrains from proposing a fourth code patch or quick refactor. | Missed | Passed |
The instructions your model reads when the skill loads.
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
Core principle: Investigate before guessing and separate a verified repair from a temporary mitigation. During an incident, an authorized rollback or containment action may restore service while root-cause work continues.
Violating the letter of this process is violating the spirit of debugging.
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
Start with the observable failure and the smallest useful evidence check. Label any emergency mitigation explicitly and preserve evidence for the later root-cause investigation.
Use for ANY technical issue:
Use this ESPECIALLY when:
Don't skip when:
test cases passed, vs 11 / 22 without
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