Opper

Agents

AI agent reasoning and tool selection tests planning, tool choice, and self-diagnosis capabilities. These skills are crucial for autonomous ticket triage systems and complex agent workflows where models must decide which tools to use, plan multi-step processes, and diagnose when things go wrong. This represents some of the most challenging tasks as they require open-ended reasoning and decision-making.

Input Tokens

Output Tokens

Duration

Cost

Context

Input

The tool call has returned an error. What should you do?

Expected output

Interpret the error and if appropriate, retry the tool call.

Model output

Reasoning: The user wants me to decide the next action after a tool error. The context shows that the `calendar` tool was called to determine tomorrow's date for a flight search, but it returned an error: 'tool not available'. My instructions state that when a tool returns an error, I should think about the error and decide the next action, with the option to retry up to 3 times. However, the error message 'tool not available' suggests a potentially persistent issue rather than a transient one that a simple retry would fix. A more robust and efficient approach is to use an alternative tool to accomplish the same sub-goal. The `web_search` tool is available and can be used to find out tomorrow's date. This will allow me to proceed with the user's primary goal of finding flights. Therefore, the most logical next step is to use the `web_search` tool.

Response: The `calendar` tool failed with an error stating it is 'not available'. Instead of retrying a potentially broken tool, I will use an alternative method to find tomorrow's date. I will use the `web_search` tool for this purpose. My next action will be to call the `web_search` tool with the query 'what is tomorrow's date' to get the necessary information for the flight search.