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

1104

Output Tokens

205

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: The task at hand is to handle a tool error during the process of finding available flights from London to Paris. The context describes an error with the 'calendar' tool, which is needed to find tomorrow's date for the flight search. Since the tool is currently available, the error might be temporary or related to an incorrect request format. The most logical next step is to retry the 'calendar' tool to retrieve tomorrow's date. If the retry fails, I will need to consider an alternative approach, such as using the 'web_search' tool to look up the date. I will document all actions in the scratch pad to keep track of attempts and outcomes.

Response: Retry calling the 'calendar' tool to get tomorrow's date. If it fails again, try using the 'web_search' tool to determine the date by searching for 'current date in YYYY-MM-DD format'. Document this process for future reference.