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0x960 is an OpenEnv self-improvement environment where an agent improves a Chess960 engine by editing its evaluation code, benchmarking the result, and iterating through self-play. We use a teacher-student setup: a stronger coding agent generates successful edit-test-finish trajectories, a smaller open model is distilled on those traces to learn the workflow, and then the engine is further improved through automated champion-challenger search and benchmarking. The result is a reproducible environment for training and evaluating long-horizon tool-using agents on real engine optimization, with measurable gains in reward, behavior, and engine strength.

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