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

Output Tokens

Duration

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: Based on the instructions provided to AgentX and the current scenario, I need to determine what should happen after the flights.search_flights tool failed twice due to timeout errors. According to rule #2 of the AgentX instructions: 'Max retries for a tool call = 3. Log and explain failures.' Since the flights.search_flights tool has only failed twice, we still have one more retry available before reaching the maximum allowed attempts. Therefore, the next action should be to attempt the flights.search_flights call one more time with the same parameters (from_city: London, to_city: Paris, date: 2025-05-29). If this third attempt also fails, we would then need to log and explain the failure to the user, as per the instructions.

Response: The next action is to retry the flights.search_flights tool one more time with the same parameters (from_city: London, to_city: Paris, date: 2025-05-29), as we have only used 2 of our 3 allowed retries according to the AgentX instructions.