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

45480

Output Tokens

5744

Duration

73683.385

Cost

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: The flights.search_flights tool has failed twice due to a timeout error. According to the instructions, the maximum number of retries for a tool call is 3. Since we have already attempted the call twice, we are allowed one more retry. Before retrying, I should ensure that the parameters are correct and that no redundant call is being made. The intended action — searching for flights from London to Paris on 2025-05-29 — is valid and necessary for the task. Given that the tool is still available and the failure was due to a transient timeout, a third attempt is justified. If this retry fails, alternative strategies may need to be considered, but for now, following the retry rule is appropriate.

Response: Retry the flights.search_flights call with the same parameters (from_city='London', to_city='Paris', date='2025-05-29') as this is within the allowed maximum of 3 retries. If this attempt also fails, proceed to assess alternative approaches such as checking for potential service issues or informing the user of the persistent failure.