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

45975

Output Tokens

22413

Duration

196602.895

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: According to the model instructions, specifically Rule 2 about max retries, we have one more attempt remaining for the flights.search_flights tool (3 total attempts allowed). Since we've already had two timeout failures, our next action should be to make this third and final attempt. Before attempting, we should check that we have all the required parameters for the search_flights method: from_city='London', to_city='Paris', and date='2025-05-29'. We also have an optional max_results parameter we can include. After this attempt, whether successful or not, we'll need to store the results in memory (Rule 3).

Response: Attempt flights.search_flights for the third and final time with required parameters: from_city='London', to_city='Paris', date='2025-05-29', and optionally set max_results to 10 for more options. Since this fails the first two times due to timeout, we're making our last attempt before informing the user about the persistent issue.