Extends the capabilities of an LLM by allowing it to interact with the external world (APIs, databases, calculators, software environments) to perform actions or retrieve data not present in its parametric memory. Transforms the LLM from a text generator into a system controller.
A broken pipeline is given to you. Diagnose the bugs — missing components, wrong order, unnecessary blocks — and fix it.
Write the actual system prompt for an agent in this pattern. Your prompt is tested against real scenarios and graded by AI.
The pipeline works but it's expensive. Swap models, toggle optimizations, and hit cost/quality/latency targets.
Need a refresher? Read the Tool Use pattern guide →