ClawGym II: Exploring Black-Box RL on Agent Harness

TL;DR - ClawGym II introduces a black-box reinforcement-learning framework for optimizing agents through opaque, complex harnesses. It enables stable, scalable, and unified training across heterogeneous agent execution systems.

• Sandbox isolation supports large-scale concurrent rollouts.
• A serving proxy captures model calls and reconstructs multi-turn trajectories as prefix trees for PPO or GRPO optimization.
• Mix-harness training jointly optimizes one model through multiple harnesses.
• Qwen3-30A3B gained 9.98 and 14.81 Pass@1 points on ClawGym-Bench through OpenClaw and Claude Code, respectively.