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.

Duration

19s

Input Tokens

1103

Output Tokens

904

Cost

$0.00

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: Since the calendar tool returned an error, the next logical step is to verify if we can call it again with correct parameters or if we can use an alternative method to retrieve the required date. We have a maximum of three retries, so it might be worth attempting a second call to the same tool (checking that parameters are correct). If it fails again, we could switch to another approach – for instance, manually determining tomorrow’s date or using other tools/resources. After successfully determining tomorrow’s date, we can proceed with using the flights tool to look up available flights from London to Paris, following the instructions provided.

Response: You should double-check the error details, verify the tool’s parameters, and attempt to call the calendar tool again or use a fallback approach to retrieve the date. Then proceed with the flights tool to find the flights for tomorrow.