reward-shaping-engineering

Pass

Audited by Gen Agent Trust Hub on Jun 22, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill provides instructional content and Python code examples for Reinforcement Learning (RL) reward engineering. All code blocks are benign examples of reward calculation, normalization, and validation logic using standard libraries like NumPy and PyTorch. No network operations, sensitive file access, or suspicious command executions were detected.
Audit Metadata
Risk Level
SAFE
Analyzed
Jun 22, 2026, 07:50 AM
Security Audit — agent-trust-hub — reward-shaping-engineering