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: The user is asking for the next action after a tool call has failed twice. I need to consult the provided instructions to determine the correct procedure.

1.  **Analyze the instructions:** I will review the rules given in the 'instructions' field.
2.  **Locate the relevant rule:** Instruction #2 states: "Max retries for a tool call = 3. Log and explain failures."
3.  **Analyze the context:** The `flights.search_flights` tool has failed twice due to a timeout error.
4.  **Determine the next action:** According to the rule, there is a maximum of 3 retries. Since the tool has failed twice, there is one attempt remaining.
5.  **Conclusion:** The next action is to retry the `flights.search_flights` tool call for the third and final time. If it fails again, the model should log the failure and consider an alternative approach.

Response: Based on the instructions, my next action is to **retry the `flights.search_flights` tool call one more time**. This is the third and final attempt, as the rules state a maximum of 3 retries for any tool call.