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.

Agents – openai/o3-mini Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Context

Input

The flights.search_flights call has returned 6 available flights from London to Paris for tomorrow. What is the next tool you will call, and why?

Expected output

The next tool is memory, to store the flights tool call result.

Model output

Reasoning: The flights.search_flights call has already provided a list of available flights. According to the instructions and the planned next step in the context, the next action is to filter these flights to find the cheapest options. Therefore, the logical next step is to call the flights.filter_by_price method with the available flights to extract the top 3 cheapest flights. This aligns with the user's goal of finding the cheapest flights from London to Paris for tomorrow.

Response: Next, I will call the flights.filter_by_price tool to filter the flights based on price, aiming to retrieve the top 3 cheapest options.