Tool Use: Giving LLMs Access to External Systems
Tool use lets an LLM call external functions, like a brain accessing a calculator or the internet. This is the core mechanism behind AI agents that can search the web, run code, or query a database to answer questions. The biggest footgun is assuming the model will always generate a valid function call; without enforcing a strict schema to match your function's expected input, your agent can fail unpredictably.
Tool use, or function calling, gives a large language model superpowers by letting it interact with external systems through functions you define. Think of it as a brain that can access a calculator, the internet, or a specific database on demand. It's the core mechanism behind modern AI agents. When you ask an assistant for the weather or to summarize a news article, it's using a tool. The model determines which tool to use based on your prompt and the tool's description, then generates a structured request for your code to execute. The most common footgun is not enforcing schema validation. The model might generate a call with missing parameters or incorrect types, causing your application to crash. Always use features like 'strict tool use' to guarantee the model's output is a valid, parseable call.
Read the original → platform.claude.com
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- #function calling
- #api
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