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/gpt-4o-mini Task | Opper AI

Input Tokens

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Output Tokens

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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 user has requested the cheapest flights from London to Paris for tomorrow and six available flights have been returned. The next logical step is to filter these flights by price and select the top three cheapest options. This approach aligns with the user's request and follows the instructions provided, ensuring that I am storing meaningful results in memory after filtering the options.

Response: The next tool I will call is 'flights.filter_by_price' to retrieve the top 3 cheapest flight options.