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

31s

Input Tokens

1103

Output Tokens

1753

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 calendar call failed even though the tool is marked available, which suggests a transient issue. We need a specific YYYY-MM-DD date to use the flights tool. The most efficient path is to retry the calendar tool (up to 3 times). If it still fails, fall back to asking the user for the date directly to avoid blocking. Once we have the date, proceed to call the flights tool and store results for summarization.

Response: Next action: Retry the calendar tool now (attempt 1 of up to 3). If it fails again, promptly ask the user: “To proceed, please provide the travel date for ‘tomorrow’ in YYYY-MM-DD format (and your time zone if you want it interpreted in a specific zone).” With the date in hand, call the flights tool with from_city='London', to_city='Paris', date='<YYYY-MM-DD>', store the results, and then present the available flights.