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 task involves handling a situation where a tool call (specifically the calendar tool) has returned an error. The user's goal is to find available flights from London to Paris for tomorrow. The calendar tool is used to determine tomorrow's date but it returned an error indicating the tool might be temporarily unavailable. According to the instructions, when a tool call returns an error, I should first analyze the error and then decide the next action, with a maximum of 3 retries allowed. Since the calendar tool is essential to get the date for the flights tool, I should retry calling the calendar tool up to two more times to see if it becomes available. If after 3 attempts the calendar tool still fails, I need an alternative approach. A reasonable backup action would be to use the 'web_search' tool to find tomorrow's date or directly search for flights on the web with a natural language query as a fallback. This approach aligns with the instructions to be efficient, avoid unnecessary loops, and remain focused on the goal. Therefore, the next step is to retry the calendar tool call one more time; if error persists after 3 total retries, then switch approach to use web_search to obtain date or flight info.

Response: You should retry the calendar tool call up to a total of 3 attempts to get tomorrow's date. If it continues to return an error after 3 tries, then switch to an alternative approach such as using the web_search tool to find the date or flight information directly. This ensures you follow the retry limit and still pursue the user's goal efficiently.