nw-der-review-criteria
SolidEvaluation criteria and scoring for data engineering artifact reviews
Code & Development 526 stars
55 forks Updated 1 weeks ago MIT
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# Data Engineer Review Criteria
Evaluation criteria for each review dimension. Load when performing reviews.
## Dimension 1: Research Citation Quality
Evaluate whether recommendations trace to specific evidence.
**Checks**: Each major recommendation cites a specific research finding | Citations are accurate (finding number matches content) | Vendor-specific claims have multiple independent sources | General best practices distinguished from research-validated guidance
**Scoring**: 10: All cited, verified | 7: Most cited, 1-2 missing on non-critical points | 4: Major recommendations lack citations | 0: No citations
## Dimension 2: Security Coverage
Evaluate defense-in-depth for data layer.
**Checks**: Encryption at rest (TDE) | Encryption in transit (TLS) | Access control model (RBAC/ABAC) | SQL injection prevention (parameterized queries) | OWASP/NIST standards referenced | Credential handling (no hardcoded secrets)
**Scoring**: 10: All 6 checks with standard references | 7: 4-5 checks | 4: 2-3 checks, missing encryption or injection prevention | 0: Security not mentioned
## Dimension 3: Trade-off Analysis
Evaluate balanced presentation of alternatives.
**Checks**: Multiple technology options (minimum 2) | Pros/cons for each | Context factors identified (scale, consistency, latency, cost) | Recommendation justified by context fit | Limitations acknowledged
**Scoring**: 10: Comprehensive trade-offs with context-driven justification | 7: Trade-offs present, some al...
Details
- Author
- nWave-ai
- Repository
- nWave-ai/nWave
- Created
- 3 months ago
- Last Updated
- 1 weeks ago
- Language
- Python
- License
- MIT
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