algo-ecom-ranking
Pass
Audited by Gen Agent Trust Hub on Sep 18, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill is entirely educational and instructional, focusing on algorithmic design for e-commerce ranking systems.
- [SAFE]: All code snippets provided in the reference files (
references/lambdamart.md,references/position-debiasing.md) and examples (examples/sample_scenario.md) use standard, well-known Python libraries such asnumpy,pandas,scikit-learn,xgboost, andlightgbmfor data processing and model training. - [SAFE]: There are no signs of prompt injection, data exfiltration, or obfuscation. The technical content accurately matches the stated purpose of the skill.
- [SAFE]: External references, such as the link to the TensorFlow Ranking repository, point to highly trusted organizations.
- [SAFE]: No use of dynamic context injection (
!command) or suspicious privilege-escalating commands was found.
Audit Metadata