nw-tr-review-criteria
Review dimensions and scoring for root cause analysis quality assessment
Best use case
nw-tr-review-criteria is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Review dimensions and scoring for root cause analysis quality assessment
Teams using nw-tr-review-criteria should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/nw-tr-review-criteria/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How nw-tr-review-criteria Compares
| Feature / Agent | nw-tr-review-criteria | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Review dimensions and scoring for root cause analysis quality assessment
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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 forward
Failures: stopping at WHY 2-3 | WHY 5 vague/philosophical not actionable | branches abandoned
Severity: High -- shallow analysis = band-aid fixes that recur.
## Dimension 5: Completeness and Coverage
Verify all symptoms accounted for.
Pass: all symptoms have causal branch | root causes collectively explain all | no orphan symptoms | cross-cause validation (no contradictions)
Failures: symptoms ignored | root causes explain primary but not secondary | contradictory causes without reconciliation
Severity: Medium -- incomplete analysis leaves unaddressed failures.
## Dimension 6: Solution Traceability
Verify solutions map to root causes.
Pass: every root cause has solution | immediate mitigations vs permanent fixes distinguished | no orphan solutions | prevention addresses systemic factors
Failures: solutions address symptoms not causes | root cause without fix | generic recommendations untied to findings
Severity: Medium -- untraceable solutions are guesses.
## Review Output Format
```yaml
review_id: "rca_rev_{timestamp}"
reviewer: "nw-troubleshooter-reviewer"
dimensions:
causality_logic:
score: 0-10
issues: [{issue, severity, recommendation}]
evidence_quality:
score: 0-10
issues: [{issue, severity, recommendation}]
alternative_hypotheses:
score: 0-10
issues: [{issue, severity, recommendation}]
five_why_depth:
score: 0-10
issues: [{issue, severity, recommendation}]
completeness:
score: 0-10
issues: [{issue, severity, recommendation}]
solution_traceability:
score: 0-10
issues: [{issue, severity, recommendation}]
overall_score: "average of dimension scores"
approval_status: "approved | revisions_required"
summary: "1-2 sentence assessment"
```
## Scoring Guide
- **9-10**: Exemplary. No issues or minor style only.
- **7-8**: Good. Minor issues not affecting conclusions.
- **5-6**: Adequate. Issues weaken but don't invalidate.
- **3-4**: Poor. Issues may lead to incorrect conclusions.
- **1-2**: Failing. Fundamental flaws invalidate analysis.
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