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: <think>
1. I see that there was an error with the calendar tool call. The error message indicates that the tool is not available.
2. However, in the context, it shows that the calendar tool status is 'available'. This suggests that there might be a temporary issue or a misconfiguration.
3. According to the instructions, if a tool returns an error, I should think about the error and decide the next action. The instructions also mention that I can retry calling a tool up to 3 times if it returns an error.
4. Since this is the first attempt (as per the trajectory), I can try calling the calendar tool again.
5. Looking at the available tools, the calendar tool is listed as available, so it's reasonable to attempt another call.
6. Before retrying, I should ensure that the tool call parameters are correct and that there are no obvious issues with the request.
7. The trajectory shows that the previous action was to call the calendar tool to determine tomorrow's date.
8. Since the calendar tool is essential to get the correct date for the flight search, it's crucial to get this information.
9. I will retry the calendar tool call once more. If it fails again, I might consider alternative ways to get the date or proceed with an assumed date if context allows.
</think>

Response: Re-try calling the calendar tool. If it fails again, consider alternative methods to obtain the current date.