symmetry-validation-suite
Pass
Audited by Gen Agent Trust Hub on Sep 21, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill's primary purpose is the empirical validation of symmetries in data and models, which is a standard task in machine learning research and development.
- [SAFE]: The provided Python code snippets in
SKILL.mdandresources/test-examples.mdare benign templates for computing numerical errors between original and transformed model outputs. - [SAFE]: All identified dependencies (torch, numpy, scipy) are well-known, industry-standard libraries used for scientific computing and deep learning.
- [SAFE]: No indicators of prompt injection, credential harvesting, or unauthorized network communication were found in the instructions or metadata.
- [SAFE]: The skill does not contain any obfuscated code, hidden URLs, or persistence mechanisms.
Audit Metadata