using-deep-rl
Pass
Audited by Gen Agent Trust Hub on Oct 9, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill consists of pedagogical Markdown files providing guidance on Reinforcement Learning algorithms and workflows.
- [SAFE]: Code snippets provided are standard RL implementations (Python/PyTorch) including PPO, SAC, DQN, and QMIX. These snippets are purely instructional and do not involve unauthorized network access, sensitive file manipulation, or system commands.
- [SAFE]: External references are limited to established academic research papers and well-known, trusted technology services and libraries within the machine learning ecosystem (e.g., Gymnasium, PettingZoo, MuJoCo, NVIDIA Isaac Lab).
- [SAFE]: No obfuscation, prompt injection markers, or persistence mechanisms were found across the 15 analyzed files.
- [SAFE]: Vectorized environment examples using
SyncVectorEnvandAsyncVectorEnvfollow the standard APIs of the documented libraries and do not present a security risk.
Audit Metadata