Tool Use in Prompts
Tool use in prompts lets LLMs call external functions, APIs, and tools by embedding schema definitions directly in the prompt context.
The model reads available tool signatures, decides when to invoke them, and returns structured calls your application executes — unlocking real-world actions like querying databases, running code, and fetching live data that go beyond text generation. Also known as: Function Calling, Tool Calling
What this topic covers
- Foundations — Tool use in prompts transforms LLMs from text generators into action-capable systems by embedding function schemas directly in the context.
- Implementation — The practical guides cover writing effective tool descriptions, structuring function calling schemas, and handling the failure modes that appear when models select the wrong tool or return malformed parameters.
- What's changing — Function calling capabilities are evolving rapidly across model providers, with benchmark performance diverging sharply from real-world reliability.
- Risks & limits — When LLMs call external APIs, the consequences are real and often irreversible.
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