Tool Use (AI)
Simple Definition
Tool use is the ability of an AI model to call external tools — like a web search engine, a calculator, a code interpreter, or a database — instead of relying solely on what it has memorized.
Without tool use, an AI is limited to what’s in its training data. With tool use, it can look things up, run calculations, write and execute code, and interact with external systems.
Why Tool Use Matters
Language models have key limitations that tools can address:
| Limitation | Tool That Solves It |
|---|---|
| Knowledge cutoff date | Web search |
| Math errors | Calculator / code interpreter |
| Can’t access real data | API calls |
| Can’t take actions | Automation tools, APIs |
| Limited to text | Image generation, file reading |
Common Tools AI Models Use
- Web search — look up current information
- Code interpreter — write and run Python to do real calculations
- File reading/writing — access documents, spreadsheets, images
- Calendar and email — schedule meetings, draft and send messages
- Database queries — retrieve structured data
- External APIs — weather, stock prices, CRM systems
Tool Use vs. Function Calling
These terms are often used interchangeably. Function calling is the technical mechanism (the model outputs a structured request to call a specific function). Tool use is the broader concept of using external capabilities.
Related Terms
- Function Calling — the technical implementation of tool use
- AI Agent — agents rely heavily on tool use to complete tasks
- Autonomous Agent — combines planning with tool use for multi-step tasks
- LLM — the models that now have tool use capabilities
See AI terms in action
Browse practical AI workflows that use the concepts in this glossary.
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