evolutionary-metric-ranking
Pass
Audited by Gen Agent Trust Hub on Oct 22, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill defines a quantitative methodology for ranking configurations using percentile normalization and intersection logic, which are standard statistical practices.
- [SAFE]: Dependencies are restricted to reputable libraries (scipy, numpy, optuna) widely used in the scientific and research sectors.
- [SAFE]: The instructions and case studies focus on local data processing and optimization, with no identified vectors for unauthorized data exfiltration or privilege escalation.
- [SAFE]: References to external repositories and tools originate from the author's official GitHub organization (terrylica), representing normal vendor functionality.
Audit Metadata