LLM Function Calling

The application supplies tool descriptions and argument schemas. During generation, the model can emit a request instead of or alongside a user-facing answer. The runtime then decides whether to execute it and returns the operation's result for subsequent generation. Structured arguments make the interface inspectable, but the model does not execute the business operation merely by naming it. This differs from free-text instructions interpreted by ad hoc parsing and from MCP, which standardizes a wider client-server integration. A function-call schema constrains representation; authorization and the meaning of the requested action remain application responsibilities.

The practitioner defines tools with narrow, predictable responsibilities and schemas that exclude invalid combinations. Context already known by the application should not need to be regenerated as arguments. Input validation, permission checks and idempotency belong before external effects. Useful outputs include tested tool contracts and traces linking requests to results. Evaluation covers wrong tool selection, missing arguments and failed tools, including whether the model reports an unsuccessful action accurately instead of claiming completion from the existence of a call.

Schema-conforming arguments can still refer to the wrong record or contain an incorrect interpretation. Parallel calls may conflict, and retries can duplicate effects without idempotent handling. Ambiguous tool descriptions increase selection errors. Quality requires correct operation choice, valid authorized arguments and truthful reporting of results. Function calling is a control interface, not a guarantee that the model understands business rules; operations should enforce those rules even when the generated request appears confident.