← Glossary AI

Tool Use

When an AI can call external functions to do things it can't do itself.

Explained simply.

An LLM on its own can only output text. It can't actually send an email, query a database, or check a calendar. Tool use is the mechanism by which the model says 'I want to use tool X with these arguments' - and your code runs the tool and gives the result back. The model then reads the result and decides what to do next. With tools, an LLM stops being a chat partner and becomes something much more capable.

An example.

You give Claude a 'search_database' tool. User asks 'what's our biggest account?'. Claude decides to call search_database(query="top accounts by revenue, limit 1"), reads the result, and replies: 'Your biggest account is Acme, with $1.2M in ARR.' Without tools, it would just guess or say it couldn't answer.

Why it matters.

Tools are how LLMs become agents. Every autonomous system is really an LLM plus a good set of tools plus a loop that lets it call them repeatedly. The tools you give it are what define what your agent can do.