A new training-free context compression framework, FOCUS, is introduced for LLM agents. FOCUS operates at test time and does not require offline data collection or fine-tuning, making it architecture-agnostic and easy to attach to closed-API frontier models. It achieves state-of-the-art performance on various agentic benchmarks, reducing context and dependency by up to 48% and 73%, respectively, while improving task success by up to 8.9 percentage points.