Atlas / Skills / nwave-ai / Nw Rr Critique Dimensions

Nw Rr Critique DimensionsSAFE

skills/nwave-ai/nw-rr-critique-dimensions

AI agents that guide you from idea to working code, with you in control at every step.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
617
01

Overview

AI agents that guide you from idea to working code, with you in control at every step.

Read from source at commit 1a864ec81cdeOBSERVED · 2026-10-14
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02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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:
```yaml
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

```yaml
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: 2
```
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-14 · audit v0.4.1 · source sha 1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-rr-critique-dimensions.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-141a864ec81cdeSAFEB89first audit
05

Questions

What does the Nw Rr Critique Dimensions skill do?

AI agents that guide you from idea to working code, with you in control at every step.

Is Nw Rr Critique Dimensions safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Nw Rr Critique Dimensions access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (1a864ec81cde), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

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