AI agents and tool calling

You describe each tool with a name, a plain-language description and a JSON Schema for its inputs. Instead of answering, the model can reply with a request such as get_order_status with order_id 1042. Your code runs the function, sends the result back and the model continues, possibly calling more tools, until it can give a final answer. The model never runs anything itself: your code decides what actually executes.

An agent wraps this in a loop with a goal, a budget and a stopping rule, and may plan, browse, write code or hand work to other agents. Agents fail in new ways: they can loop, run up token bills, act on a misunderstanding, or follow instructions hidden in a web page or email (prompt injection). Keep tools narrow, require confirmation for anything destructive or costly, log every step and cap the number of turns.