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 an error from a tool call. The context provides detailed information about the trigger, past trajectory, available tools, and the current state of the task. The error occurred when trying to call the calendar tool to determine tomorrow's date, which is necessary for the next step of finding flights from London to Paris. Given the instructions, the next steps should be systematic and focused on resolving the error efficiently. Since the calendar tool is unavailable, an alternative approach is needed to get the date. The web_search tool can be used to find the current date indirectly, which can then be formatted correctly for the flights tool. The task remains focused on the user's request and must not deviate from the goal.

Response: Given the error with the calendar tool, I will use the web_search tool to find the current date and calculate tomorrow's date manually. Once the date is confirmed, I will proceed to use the flights tool to search for available flights from London to Paris for the specified date. This approach directly addresses the error and keeps the task on track towards the user's original request.