Context Engineering Fundamentals
Master the principles of LLM context management to optimize agent performance, reduce token costs, and improve reasoning accuracy.
Master the principles of LLM context management to optimize agent performance, reduce token costs, and improve reasoning accuracy.
This skill provides a comprehensive framework for understanding and engineering the state available to language models at inference time. It covers the essential components of context—system prompts, tool definitions, retrieved documents, and message history—while introducing critical concepts like the attention budget constraint and the progressive disclosure principle. By implementing these patterns, developers can move beyond simple prompting to create efficient, high-signal context strategies that prevent model degradation and ensure long-horizon task success.