## Jev + Gymnasium Evaluate TypeSafe Jev as a policy in Gymnasium and Atari environments. Game-specific adapters convert observations into structured JSON; Jev selects a legal action through a single Choice question. This project evaluates a fixed model. It records rewards and decisions without training or updating model weights. A seeded random policy provides a local baseline. Three games, one shared action-selection question. Joysticks and probability bars show Jev's recorded decisions at 2× game speed. See recording details for the source runs, rendering command, and smaller gameplay-only…