skrl is a reinforcement learning framework written in Python that implements RL algorithms across multiple numerical backends. It provides a modular architecture for implementing and training RL agents, with built-in support for common RL environments including Gymnasium, Isaac Lab, and MuJoCo. The library emphasizes readable and transparent algorithm implementations suitable for research and development in reinforcement learning.