Reinforcement Learning Skill
RL training for robot control using simulation with sim-to-real transfer
npx skills add a5c-ai/babysitter --skill rl-robotics --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Reinforcement Learning Skill ## Overview Expert skill for training reinforcement learning agents for robot control tasks, including environment design, training pipelines, and sim-to-real transfer. ## Capabilities - Configure Gym/Gymnasium environments for robots - Set up Stable Baselines3 training (PPO, SAC, TD3) - Implement custom observation and action spaces - Design reward shaping strategies - Configure parallel environment training - Implement domain randomization for sim-to-real - Set up curriculum learning - Configure vision-based RL with CNNs - Implement policy distillation - Export policies for deployment (ONNX, TorchScript) ## Target Processes - rl-robot-control.js - imitation-learning.js - sim-to-real-validation.js - nn-model-optimization.js ## Dependencies - Stable Baselines3 - Gymnasium - Isaac Gym - rsl_rl ## Usage Context This skill is invoked when processes require RL-based robot control, learning from simulation, or transferring learned policies to real robots. ## Output Artifacts - Gymnasium environment implementations - Training configurations - Reward function designs - Domain randomization configs - Trained policy checkpoints - Deployment-ready models (ONNX)
- Overview
- Capabilities
- Target Processes
- Dependencies
- Usage Context
- Output Artifacts
What does the Reinforcement Learning Skill skill do?
RL training for robot control using simulation with sim-to-real transfer
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill rl-robotics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.