Critique dimensions, severity framework, verdict decision matrix, and review output format for documentation assessment reviews
npx skills add https://github.com/nWave-ai/nWave --skill nw-dr-review-criteria
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.
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
Verify all five anti-patterns checked with accurate findings.
Verification: independently scan, count lines per quadrant, compare to documentarist's findings, flag discrepancies.
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()"
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.
Verify verdict matches findings per decision matrix below.
| 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
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}]
Maximum 2 revision cycles. After cycle 2: escalate to human, return approval_status: escalate_to_human with rationale.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take nwave-ai/nw-dr-review-criteria from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.