How to Build Tools for AI Agents

AI agents perform tasks by making a series of Large Language Model (LLM) calls and utilizing tools, which are essentially functions the agent can invoke. Creating effective tools requires clear naming, descriptive docstrings, and precise type definitions for both inputs and outputs. Tools should be designed with a singular, specific purpose and should parse their results into a clean, structured output for the agent to easily understand. To avoid overwhelming the agent's context, it is also important to limit the number of returned results. Implementing informative error handling is also crucial to guide the agent when issues arise and a tool fails.