STACX (Stand Alone Complex) is a modular framework for agentic training, evaluation, and reinforcement learning. It standardizes the full pipeline — dataset config, rollout scheduler, agent and sandbox, verifier reward, trainer — so that new methods and new benchmarks slot into the same infrastructure. STACX supports training with GRPO, SFT, DAgger, and on-policy distillation; evaluating agents across benchmark environments; and integrating new environments. Three engines are coordinated under the hood: a task scheduler driving agents and scaffolds, a Docker-based sandbox environment engine, and Megatron/FSDP training backends. Agents can be implemented in-house, keeping the training loop fully visible, or installed as external black-box agents such as OpenHands and Terminus-2.