alterlab-pufferlib
Pass
Audited by Gen Agent Trust Hub on Apr 12, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides legitimate templates and documentation for the PufferLib reinforcement learning framework, which is a high-performance library for speed-optimized training.
- [SAFE]: External dependencies and references target standard, well-known libraries and services in the machine learning ecosystem, such as PyTorch, NumPy, Weights & Biases, and Neptune.
- [SAFE]: Training and environment scripts follow established best practices for reinforcement learning development, including proper neural network initialization and efficient data handling via shared memory buffers.
- [SAFE]: Network operations are confined to official logging integrations that require user-supplied credentials or project names, posing no risk of unauthorized data exfiltration.
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