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

44s

Input Tokens

1388

Output Tokens

921

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: According to the model instructions, rule 2 states 'Max retries for a tool call = 3. Log and explain failures.' I have attempted flights.search_flights twice with timeout errors, which means I have 1 retry remaining. The instruction requires me to log and explain failures when they occur. Therefore, my next action is to: 1) Log the timeout failures that have occurred so far, explaining the issue, and then 2) Attempt to call flights.search_flights one final time (3rd attempt) with the same parameters (from_city='London', to_city='Paris', date='2025-05-29'). If this third attempt also fails, I would then need to inform the user of the persistent issue and consider alternative approaches or request user guidance.

Response: My next action is to log the two timeout failures and then attempt to call flights.search_flights one final time (3rd attempt) with parameters: from_city='London', to_city='Paris', date='2025-05-29', as permitted by the max retry limit of 3.