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

1280

Output Tokens

426

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: The tool call to flights.search_flights has failed twice, but the instructions allow up to 3 retries (Rule 2). Because we still need the flight data to continue the planned workflow (filtering, storing, and summarising), and we have not exceeded the retry limit, the logical next step is to perform the third (and final) retry of flights.search_flights, logging the attempt. If it fails again, we would stop retrying, log the failure, and consider alternative actions or inform the user.

Response: Retry flights.search_flights one final time (3rd attempt), as we have one retry left according to the max-retry rule.