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

49902

Output Tokens

6255

Duration

454487.384

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 task is to determine the next action after encountering a timeout error while trying to call flights.search_flights. According to the instructions, I should follow these steps: 1. Read the task carefully and understand the user's request - the user wants to find the cheapest flights from London to Paris for tomorrow and present the top 3 options. 2. Think through my approach before acting - I need to retry calling flights.search_flights up to 3 times before considering it unavailable. 3. Provide my reasoning and thought process - as stated above. 4. Execute the task systematically, following the approach and rules in the instructions - I will retry calling flights.search_flights and update the context with the result. 5. Provide a clear final answer or result - the result will be presented in the context. 
Based on the context, the current step is to use flights.search_flights to retrieve flights from London to Paris for 2025-05-29. I will retry this action.

Response: Retrying flights.search_flights for flights from London to Paris for 2025-05-29.