nw-dr-review-criteria

name	nw-dr-review-criteria
description	Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews
user-invocable	false
disable-model-invocation	true

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

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: []
     []
     [{, , }]

  
     []
     [{, , }]

  
     []
     
     
     []
     

  
     []
     []
     { ,  ,  ,  }
     []
     [{, }]

Review Iteration Limits

Maximum 2 revision cycles. After cycle 2: escalate to human, return approval_status: escalate_to_human with rationale.