nw-tr-review-criteria
SolidReview dimensions and scoring for root cause analysis quality assessment
Code & Development 526 stars
55 forks Updated 1 weeks ago MIT
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# 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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