About
This skill provides a foundational framework for understanding and engineering the context available to language models during inference. It covers critical concepts like the attention budget, progressive disclosure, and the anatomy of context—including system prompts, tool definitions, and message history. By applying these fundamentals, developers can build more reliable agent systems that maintain high performance even as task complexity scales, ensuring that only high-signal information reaches the model's limited attention window.
