nw-tr-review-criteria

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Review dimensions and scoring for root cause analysis quality assessment

Code & Development 526 stars 55 forks Updated 1 weeks ago MIT

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Skill Content

# Troubleshooter Review Criteria Review dimensions and scoring for root cause analysis quality assessment. ## Dimension 1: Causality Logic Check each WHY-to-WHY link. Pass: logical mechanism (not just correlation) | no skipped steps | alternatives considered/eliminated | chain reads coherently both directions Failures: correlation assumed as causation | causal chain gaps | single-path tunnel vision (first plausible cause accepted) Severity: Critical -- wrong root cause = ineffective fixes. ## Dimension 2: Evidence Quality Verify findings grounded in observable data. Pass: each WHY cites specific evidence (logs, metrics, config, repro steps) | evidence verifiable by third party | timeline supports causality | hypotheses marked unverified Failures: "Probably because..." without data | vague references ("logs show issues") | mixing facts with speculation unlabeled Severity: High -- unreliable analysis undermines trust. ## Dimension 3: Alternative Hypotheses Verify competing explanations explored. Pass: 2+ alternatives at WHY 1-3 | each pursued or eliminated with evidence | "why not" reasoning documented Failures: stops at first plausible cause | alternatives mentioned but unevaluated | confirmation bias Severity: High -- may miss actual root cause. ## Dimension 4: Five-WHY Depth Verify analysis reaches fundamental causes. Pass: each branch reaches WHY 5 (or justifies stopping with evidence) | final causes are actionable | causes explain symptoms when traced fo...

Details

Author
nWave-ai
Repository
nWave-ai/nWave
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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