nw-dr-review-criteria
Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews
Best use case
nw-dr-review-criteria is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews
Teams using nw-dr-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-dr-review-criteria/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How nw-dr-review-criteria Compares
| Feature / Agent | nw-dr-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?
Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews
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.
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SKILL.md Source
# Documentation Review Criteria
## Critique Dimensions
### 1. Classification Accuracy
Verify type assignment against DIVIO decision tree.
Questions: Do cited signals support assigned type? | Contradicting signals ignored? | Confidence appropriate? | Decision tree leads to same classification?
Verification: 1) Run decision tree independently 2) Check positive signals present 3) Check for red flags 4) Verify confidence matches signal strength
Severity: if wrong classification leads to wrong verdict = blocking.
### 2. Validation Completeness
Verify all type-specific criteria checked. Questions: All items checked? | Pass/fail correct? | Issues properly located? | Any criteria missed?
**Tutorial** (required): completable without external refs | steps numbered/sequential | verifiable outcomes | no assumed knowledge | builds confidence
**How-to** (required): clear goal | assumes fundamentals | single task | completion indicator | no basics teaching
**Reference** (required): all params documented | return values | error conditions | examples | no narrative
**Explanation** (required): addresses "why" | context/reasoning | alternatives considered | no task steps | conceptual model
### 3. Collapse Detection Correctness
Verify all five anti-patterns checked with accurate findings.
- Tutorial creep: explanation >20% | How-to bloat: teaching basics | Reference narrative: prose in entries
- Explanation task drift: steps in explanation | Hybrid horror: 3+ quadrants
Verification: independently scan, count lines per quadrant, compare to documentarist's findings, flag discrepancies.
### 4. Recommendation Quality
Criteria: **Specific** (exact what/where) | **Actionable** (author knows next step) | **Prioritized** (important first) | **Justified** (why it matters) | **Root cause** (underlying issue)
Bad: "Improve the documentation", "Make it clearer"
Good: "Move explanation in section 3.2 (lines 45-60) to separate doc", "Add return value docs for login()"
### 5. Quality Score Accuracy
Verify six characteristics: Accuracy (factual claims verified?) | Completeness (gap analysis thorough?) | Clarity (Flesch 70-80?) | Consistency (style 95%+?) | Correctness (errors counted?) | Usability (structural assessment?)
Note: Documentarist cannot fully measure accuracy (needs expert) or usability (needs user testing). Verify limitations properly scoped.
### 6. Verdict Appropriateness
Verify verdict matches findings per decision matrix below.
## Severity Framework
| Level | Definition | Action |
|-------|-----------|--------|
| Blocking | Wrong classification/verdict, missed collapse making doc unusable | Must fix |
| High | Multiple criteria missed, collapse missed but usable | Should fix; may block |
| Medium | Single criterion missed, miscalibrated confidence, false positive | Recommended |
| Low | Format inconsistency, wording clarity | Optional |
**Reject**: any blocking | 3+ high | classification wrong | verdict contradicts findings
**Conditionally approve**: 1-2 high not affecting verdict | multiple medium but core correct
**Approve**: no blocking/high | medium noted but not blocking
## Verdict Decision Matrix
- **Approved**: all checks pass or low-only failures | no collapse | quality gates met (Flesch 70-80, purity 80%+)
- **Needs Revision**: medium/low failures only | no collapse | fixable without restructuring
- **Restructure Required**: collapse detected | purity <80% | multiple user needs | requires splitting
### Verification Algorithm
1. Count issues by severity 2. Check collapse_detection.clean 3. Check quality gates 4. Apply matrix 5. Compare to documentarist verdict 6. Flag discrepancy
## Review Output Format
```yaml
documentation_assessment_review:
review_id: "doc_rev_{timestamp}"
reviewer: "nw-documentarist-reviewer (Quill)"
assessment_reviewed: "{path}"
original_document: "{path}"
classification_review:
accurate: [boolean]
confidence_appropriate: [boolean]
independent_classification: "[your type]"
match: [boolean]
issues: [{issue, evidence, severity, recommendation}]
validation_review:
complete: [boolean]
criteria_checked: "[X/Y required + Z/W additional]"
missed_criteria: [list]
issues: [{issue, severity, recommendation}]
collapse_detection_review:
accurate: [boolean]
independent_findings: "[anti-patterns found]"
false_positives: [count]
missed_patterns: [list]
issues: [{issue, severity, recommendation}]
recommendation_review:
quality: [high|medium|low]
actionable: [boolean]
properly_prioritized: [boolean]
issues: [{issue, severity, improvement}]
quality_score_review:
accurate: [boolean]
issues: [{score, issue, correction}]
verdict_review:
appropriate: [boolean]
documentarist_verdict: "[their verdict]"
recommended_verdict: "[your verdict]"
verdict_match: [boolean]
rationale: "{justification}"
overall_assessment:
assessment_quality: [high|medium|low]
approval_status: [approved|rejected_pending_revisions|conditionally_approved|escalate_to_human]
issue_summary: {blocking: N, high: N, medium: N, low: N}
blocking_issues: [list]
recommendations: [{priority, action}]
```
## Review Iteration Limits
Maximum 2 revision cycles. After cycle 2: escalate to human, return `approval_status: escalate_to_human` with rationale.Related Skills
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