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 reports that the tool call returned an error. Considering the context, the error occurred during a previous attempt to determine the date for flight search, related to a calendar tool that was unavailable. Since the error is from a tool call and the necessary tools for flight information are available, I need to handle the error by either retrying the same operation, checking for alternatives, or proceeding with an assumption. Given that the 'calendar' tool previously failed, I should attempt to determine the date by alternative means or confirm the date. Because the context involves user request for flights from London to Paris 'tomorrow', I should ascertain the date independently if possible, or notify that the previous step failed and proceed accordingly. The logical next step is to reevaluate or retry the date determination, perhaps using the 'web_search' tool to find today's date, or default to assuming 'tomorrow' based on context, then proceed to search for flights. Here, I will proceed with assuming 'tomorrow's date as no further instruction is provided, and re-attempt to use the 'flights' tool with this date.

Response: Since the calendar tool call resulted in an error, I will assume 'tomorrow's date as the task involves scheduling for the next day. I will then re-attempt to find flights from London to Paris for that date using the 'flights' tool.