{"slug":"pauldanielml-mujoco-rl-ur5","name":"MuJoCo RL UR5","description":"A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.","tagline":"A MuJoCo/Gym environment for robot control using Reinforcement Learning. 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The task of agents in this environment is pixel-wise prediction of grasp success chances.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/PaulDanielML/MuJoCo_RL_UR5","github_repo":"PaulDanielML/MuJoCo_RL_UR5","version":"1.0.0","license":"MIT","updated_at":"2026-06-16T00:01:23.185466+00:00","canonical_key":"pauldanielml/mujoco_rl_ur5","recommendation_reasons":["Useful GitHub adoption: 679 stars","Install handoff is available","Repository freshness signal is available"],"urls":{"web":"https://www.openagentskill.com/skills/pauldanielml-mujoco-rl-ur5","api":"https://www.openagentskill.com/api/agent/skills/pauldanielml-mujoco-rl-ur5","install_api":"https://www.openagentskill.com/api/skills/pauldanielml-mujoco-rl-ur5/install","audit":"https://www.openagentskill.com/skills/pauldanielml-mujoco-rl-ur5/audit","repository":"https://github.com/PaulDanielML/MuJoCo_RL_UR5"},"meta":{"endpoint":"/api/registry/manifest/{slug}","canonical_agent_endpoint":"/api/agent/skills/pauldanielml-mujoco-rl-ur5","agent_friendly":true,"api_version":"1.0","generated_at":"2026-08-04T16:07:11.442Z"}}