Nw Sa Critique DimensionsSAFE
AI agents that guide you from idea to working code, with you in control at every step.
Overview
AI agents that guide you from idea to working code, with you in control at every step.
1a864ec81cdeOBSERVED · 2026-10-14What 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-sa-critique-dimensions
description: Architecture quality critique dimensions for peer review. Load when invoking solution-architect-reviewer or performing self-review of architecture documents.
user-invocable: false
disable-model-invocation: true
---
# Architecture Quality Critique Dimensions
## Dimension 1: Architectural Bias Detection
### Technology Preference Bias
Pattern: tech chosen by preference, not requirements. Detection: ADR lacks comparison matrix, choice not mapped to requirements, justified only as "best practice." Severity: HIGH.
### Resume-Driven Development
Pattern: complex/trendy tech without requirement justification. Examples: microservices for 3-person team, Kafka for 100 req/day, service mesh without complexity. Detection: complexity exceeds team size/requirements, tech adds resume value not solves problem. Severity: CRITICAL.
### Latest Technology Bias
Pattern: unproven tech (<6 months, small community) for production. Detection: check maturity, community, LTS, fallback plan. Severity: HIGH.
## Dimension 2: ADR Quality Validation
### Missing Context
ADR lacks business problem, technical constraints, or quality attribute requirements. Future maintainers cannot validate. Severity: HIGH.
### Missing Alternatives Analysis
No alternatives (min 2 required). Each must be evaluated against requirements with rejection rationale. Severity: HIGH.
### Missing Consequences
Omits positive/negative consequences and trade-offs. Quality attribute impact not analyzed. Severity: MEDIUM.
## Dimension 3: Completeness Validation
### Missing Quality Attributes
Architecture doesn't address required attributes. Verify: performance (latency, throughput) | scalability | security (auth, data protection) | maintainability (modularity, testability) | reliability (fault tolerance, recovery) | observability (logging, monitoring, alerting). Severity: CRITICAL.
### Missing Performance Architecture
Performance requirements exist but no optimization strategy (caching, indexing, rate limiting, CDN). Severity: CRITICAL.
## Dimension 4: Implementation Feasibility
### Team Capability Mismatch
Requires expertise team lacks. Verify learning curve reasonable, training plan exists. Severity: HIGH.
### Budget Constraints
Infrastructure costs exceed budget. Verify cost estimate exists and aligns. Severity: HIGH.
### Testability Validation
Architecture prevents effective testing. Components must enable isolated testing with ports/adapters. Severity: CRITICAL.
## Dimension 5: Priority Validation
Validate roadmap addresses largest bottleneck.
**Q1**: Largest bottleneck? (timing data must confirm primary problem)
**Q2**: Simpler alternatives considered? (rejected alternatives required)
**Q3**: Constraint prioritization correct? (quantified by impact, constraint-free first)
**Q4**: Data-justified? (key decision with quantitative data)
Failure: Q1=NO (wrong problem) | Q2=MISSING (no alternatives) | Q3=INVERTED (>50% solution for <30% problem) | Q4=NO_DATA for performance
## Review Output Format
```yaml
review_id: "arch_rev_{timestamp}"
reviewer: "solution-architect-reviewer"
artifact: "docs/product/architecture/brief.md, docs/product/architecture/adr-*.md"
iteration: {1 or 2}
strengths:
- "{Positive decision with ADR reference}"
issues_identified:
architectural_bias:
- issue: "{pattern detected}"
severity: "critical|high|medium|low"
location: "{ADR or section}"
recommendation: "{actionable fix}"
decision_quality:
- issue: "{ADR quality issue}"
severity: "high"
location: "ADR-{number}"
recommendation: "{add missing section}"
completeness_gaps:
- issue: "{quality attribute not addressed}"
severity: "critical"
recommendation: "{add architecture section}"
implementation_feasibility:
- issue: "{capability, budget, testability concern}"
severity: "high"
recommendation: "{simplify or add mitigation}"
priority_validation:
q1_largest_bottleneck:
evidence: "{data or NOT PROVIDED}"
assessment: "YES|NO|UNCLEAR"
q2_simple_alternatives:
assessment: "ADEQUATE|INADEQUATE|MISSING"
q3_constraint_prioritization:
assessment: "CORRECT|INVERTED|NOT_ANALYZED"
q4_data_justified:
assessment: "JUSTIFIED|UNJUSTIFIED|NO_DATA"
approval_status: "approved|rejected_pending_revisions|conditionally_approved"
critical_issues_count: {number}
high_issues_count: {number}
```
## Severity Classification
- **Critical**: resume-driven dev, missing critical quality attributes, untestable, wrong problem
- **High**: technology bias, incomplete ADRs, feasibility concerns, missing data
- **Medium**: missing consequences, minor completeness gaps
- **Low**: documentation improvements, naming consistencyTrust 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.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (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.
1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-sa-critique-dimensions.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-14 | 1a864ec81cde | SAFE | B | 89 | first audit |
Questions
What does the Nw Sa Critique Dimensions skill do?
AI agents that guide you from idea to working code, with you in control at every step.
Is Nw Sa 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 Sa 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.