algo-ecom-ranking
Pass
Audited by Gen Agent Trust Hub on Apr 10, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill is purely educational and instructional, providing architectural patterns for e-commerce search algorithms.
- [SAFE]: Code implementation examples provided in the reference files use legitimate, well-known data science libraries such as XGBoost, LightGBM, and Scikit-Learn.
- [SAFE]: No evidence of prompt injection, data exfiltration, or obfuscation was found in any of the analyzed files.
- [SAFE]: External repository references point to official, trusted resources such as the TensorFlow Ranking project.
- [SAFE]: The algorithm descriptions focus on legitimate business logic like relevance, conversion rates, and inventory management.
Audit Metadata