Gymnasium & Raylib Environment Development

This skill provides a foundation for building Reinforcement Learning (RL) environments using gymnasium for the API and raylib for high-performance simulation and visualization.

Core Philosophy

1. Gymnasium First: The environment must strictly adhere to the gym.Env interface (reset, step, render, close).
2. Inheritance of Standards: This skill inherits and enforces all "Power of 10" rules and hexagonal architecture principles defined in the core python-app developer skill.
3. Simulation/Visualization Split: Keep the simulation logic (physics, state updates) separate from the Raylib rendering logic. The environment must run "headless" at maximum speed.
4. Scene-Based Orchestration: Use the Scene Pattern to coordinate game/logic, ui/renderer, and state-machine transitions between game modes and RL phases.

Environment Structure

The gym.Env Wrapper & Scenes

import gymnasium as gym
from gymnasium import spaces
import pyray as pr