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

18s

Input Tokens

1280

Output Tokens

558

Cost

$0.00

Context

Input

You attempted to call flights.search_flights, but the tool failed twice due to a timeout error. What is your next action according to the model instructions?

Expected output

Retry the flights.search_flights call one more time (maximum retries = 3), and if it fails again, log the failure and proceed with fallback steps or inform the user.

Model output

Reasoning: We have already attempted flights.search_flights twice and both attempts have timed out. According to rule #2 (max retries = 3), we are allowed one more retry. Before making any tool call, rule #1 instructs us to confirm available methods and parameters—but since we already know the flights.search_flights signature, we can proceed to retry the call with the same parameters. This will be our third and final attempt before we consider an alternative approach or inform the user of failure.

Response: Retry the flights.search_flights call for the third and final time using the original parameters (from_city='London', to_city='Paris', date='2025-05-29').