/nw-rr-critique-dimensions
Critique dimensions and scoring for research document reviews
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Critique dimensions and scoring for research document reviews
SKILL.md
nw-rr-critique-dimensions.SKILL.mdname: nw-rr-critique-dimensions
description: Critique dimensions and scoring for research document reviews
user-invocable: false
disable-model-invocation: true
Critique Dimensions for Research Review
Load when reviewing research documents. Apply each dimension systematically.
Dimension 1: Source Selection Bias
Check: contradictory viewpoints included? | Multiple organizations/authors/perspectives? | Geographic/temporal diversity? | Sources truly independent (not circular)?
Flags: 60%+ from single org/author -> critical | All supporting same conclusion without counterpoint -> critical | Single geographic region -> medium | Clustered publication dates -> medium
Dimension 2: Evidence Quality
Check: every major claim cited | sources reputable (peer-reviewed, official, established) | primary over secondary | technical sources recent (5 years) | confidence matches evidence
Flags: uncited claim -> high | blog/forum for factual claim -> high | all secondary sources -> medium | sources >5 years for tech -> medium | high confidence with 1-2 sources -> high
Dimension 3: Replicability
Check: search strategy documented | source selection criteria explicit | methodology transparent | confidence levels with rationale
Flags: no methodology section -> high | vague methodology ("searched the web") -> medium | no confidence ratings -> medium
Dimension 4: Priority Validation
For research driving architectural/strategic decisions.
Q1: Is this the largest bottleneck? (timing/measurement data?) | Q2: Simpler alternatives considered and rejected with evidence? | Q3: Constraint prioritization correct? (>50% solution for <30% problem = flag) | Q4: Key decision data-justified?
Flags: secondary concern addressed while larger exists -> critical | no measurement data for performance -> high | alternatives not documented -> high | prioritization not explicit -> medium
Output template:
priority_validation:
q1_largest_bottleneck:
evidence: "{timing data or 'NOT PROVIDED'}"
assessment: "YES|NO|UNCLEAR"
q2_simple_alternatives:
assessment: "ADEQUATE|INADEQUATE|MISSING"
q3_constraint_prioritization:
minority_constraint_dominating: "YES|NO"
assessment: "CORRECT|INVERTED|NOT_ANALYZED"
q4_data_justified:
assessment: "JUSTIFIED|UNJUSTIFIED|NO_DATA"
verdict: "PASS|FAIL"Dimension 5: Completeness
Check: knowledge gaps documented (what searched, why insufficient) | conflicting info acknowledged with credibility analysis | all required sections present (summary, findings, sources, gaps, citations) | research metadata included
Flags: missing gaps section when gaps exist -> critical | conflicting sources unacknowledged -> high | missing required sections -> high | no metadata -> medium
Review Output Template
review_id: "research_rev_{timestamp}"
reviewer: "nw-researcher-reviewer (Scholar)"
issues_identified:
source_bias:
- issue: "{specific description with numbers}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
evidence_quality:
- issue: "{specific claim or location}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
replicability:
- issue: "{what is missing}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
priority_validation:
- issue: "{mismatch description}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
completeness:
- issue: "{missing element}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
quality_scores:
source_bias: 0.00
evidence_quality: 0.00
replicability: 0.00
completeness: 0.00
priority_validation: 0.00
approval_status: "approved|rejected_pending_revisions"
blocking_issues:
- "{critical issue 1}"
iteration: 1
max_iterations: 2Read more
name: nw-rr-critique-dimensions description: Critique dimensions and scoring for research document reviews user-invocable: false disable-model-invocation: true
Critique Dimensions for Research Review
Load when reviewing research documents. Apply each dimension systematically.
Dimension 1: Source Selection Bias
Check: contradictory viewpoints included? | Multiple organizations/authors/perspectives? | Geographic/temporal diversity? | Sources truly independent (not circular)?
Flags: 60%+ from single org/author -> critical | All supporting same conclusion without counterpoint -> critical | Single geographic region -> medium | Clustered publication dates -> medium
Dimension 2: Evidence Quality
Check: every major claim cited | sources reputable (peer-reviewed, official, established) | primary over secondary | technical sources recent (5 years) | confidence matches evidence
Flags: uncited claim -> high | blog/forum for factual claim -> high | all secondary sources -> medium | sources >5 years for tech -> medium | high confidence with 1-2 sources -> high
Dimension 3: Replicability
Check: search strategy documented | source selection criteria explicit | methodology transparent | confidence levels with rationale
Flags: no methodology section -> high | vague methodology ("searched the web") -> medium | no confidence ratings -> medium
Dimension 4: Priority Validation
For research driving architectural/strategic decisions.
Q1: Is this the largest bottleneck? (timing/measurement data?) | Q2: Simpler alternatives considered and rejected with evidence? | Q3: Constraint prioritization correct? (>50% solution for <30% problem = flag) | Q4: Key decision data-justified?
Flags: secondary concern addressed while larger exists -> critical | no measurement data for performance -> high | alternatives not documented -> high | prioritization not explicit -> medium
Output template:
priority_validation:
q1_largest_bottleneck:
evidence: "{timing data or 'NOT PROVIDED'}"
assessment: "YES|NO|UNCLEAR"
q2_simple_alternatives:
assessment: "ADEQUATE|INADEQUATE|MISSING"
q3_constraint_prioritization:
minority_constraint_dominating: "YES|NO"
assessment: "CORRECT|INVERTED|NOT_ANALYZED"
q4_data_justified:
assessment: "JUSTIFIED|UNJUSTIFIED|NO_DATA"
verdict: "PASS|FAIL"Dimension 5: Completeness
Check: knowledge gaps documented (what searched, why insufficient) | conflicting info acknowledged with credibility analysis | all required sections present (summary, findings, sources, gaps, citations) | research metadata included
Flags: missing gaps section when gaps exist -> critical | conflicting sources unacknowledged -> high | missing required sections -> high | no metadata -> medium
Review Output Template
review_id: "research_rev_{timestamp}"
reviewer: "nw-researcher-reviewer (Scholar)"
issues_identified:
source_bias:
- issue: "{specific description with numbers}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
evidence_quality:
- issue: "{specific claim or location}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
replicability:
- issue: "{what is missing}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
priority_validation:
- issue: "{mismatch description}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
completeness:
- issue: "{missing element}"
severity: "critical|high|medium"
recommendation: "{actionable fix}"
quality_scores:
source_bias: 0.00
evidence_quality: 0.00
replicability: 0.00
completeness: 0.00
priority_validation: 0.00
approval_status: "approved|rejected_pending_revisions"
blocking_issues:
- "{critical issue 1}"
iteration: 1
max_iterations: 2AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).
Repo: nWave-ai/nWave
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