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.

0
Duration
16s
Input Tokens
1281
Output Tokens
132
Cost
$0.00
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 task is to determine which tool to call next after retrieving available flights from London to Paris. The context indicates that the user is interested in the cheapest flights and that I have already retrieved the flights. The next logical step is to filter the results by price to find the top 3 cheapest options before storing that information in memory. Therefore, I will call the 'filter_by_price' method from the flights tool to get the desired results.

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