SkyRL provides a unified framework for reinforcement learning with LLMs, combining training, inference, and agent systems. It includes modular training components for RL on custom hardware, a cross-platform Tinker API backend with a unified training and inference engine, an agent layer for long-horizon real-world tasks, and a gymnasium of tool-use environments spanning math, coding, search, and SQL domains.