This article focuses on a core technical challenge in Agent development: how to accurately calculate the context window size occupied by user messages (prompts). The author points out that in practical development, the context window is limited and needs to include system prompts, model return results, and tool calls, so effective estimation tools are needed to avoid overflow. The article explores visualization tools and other practical methods to help developers optimize Agent performance and improve resource utilization efficiency. This guide is highly valuable for AI developers, especially applicable to large model application scenarios, effectively solving context management challenges and promoting the implementation of Agent technology.
