Run a six-step diagnosis loop with evidence gates for reproducible failures.
npx skills add https://github.com/cropsgg/skills --skill diagnose-cropsgg
Please help me install this Agent Skill. Skill: diagnose Source: https://github.com/cropsgg/skills/tree/main/skills/engineering/diagnose Command: npx skills add https://github.com/cropsgg/skills --skill diagnose-cropsgg
This skill provides a disciplined, evidence-gated debugging loop that ensures failures are diagnosed with repeatable, artifact-backed steps.
Run a disciplined six-step diagnosis loop on a reproducible failure, enforcing evidence gates before advancing through each step.
High-intent search queries and answers about installing and using this skill.
A structured debugging workflow enforces a six-step loop: reproduce, minimise, hypothesise, instrument, fix, and regression-test. Strict gates between each stage require concrete artifacts before advancing, ensuring complex production failures are isolated through repeatable steps.
Evidence-driven debugging validates root-cause hypotheses by requiring instrumented checks and concrete artifacts at each stage. This disciplined approach ensures fault isolation is backed by repeatable, artifact-backed steps rather than assumptions, preventing premature conclusions in complex systems.
Creating a minimal reproducer requires capturing the production environment and isolating the specific conditions triggering the failure. This reproducible failure analysis serves as a gate-kept artifact, ensuring the diagnostic loop progresses only with validated reproductions.
Yes, this disciplined diagnosis loop applies to complex fault isolation scenarios across distributed production-grade systems. It requires environment capture, a minimal reproducer, and instrumented checks to validate hypotheses across systems before advancing through gate-enforced diagnostic stages.
Gate-enforced debugging requires a reproducible failure, complete environment capture, and a minimal reproducer as prerequisites. These artifacts must be collected before entering the structured diagnosis loop, ensuring complex fault isolation begins with validated, instrumented inputs.
ThejanaJayalathDiagnose AI agent execution failures through structured root-cause analysis.
santanapolDiagnose failing tests, build errors, and runtime issues with structured triage workflows.
YukiIto1999Collect, parse, and correlate Windows EVTX, Linux syslog, and web access logs into a unified forensic timeline.
openeuler-mirrorGenerate structured root cause analysis reports from system logs and performance metrics.
