In this article, you will learn how to transform a basic tool-calling script into a resilient agent that gracefully handles failures from misbehaving tools, malformed model outputs, and unavailable services. Topics we will cover include: How to structure an iterative agent loop with a safety cap on iteration count. The four distinct categories of failure an agent encounters when calling tools, and how to handle each one. How to design tool error messages that teach the model how to recover, reducing wasted iterations. Building a Multi-Tool Gemma 4 Agent with Error Recovery Introduction In a previous article , we wired up Gemma 4 to a handful of Python functions using Ollama’s tool-calling API. That gave us a working single-turn dispatcher: the model picks a tool, our code runs it, the model answers. It’s a useful starting point, but it’s a long way from an agent. One of the things that turns a tool-calling demo into an actual agent is how it handles things going wrong. Tools fail.…