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
17s
Input Tokens
1280
Output Tokens
457
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 previous step with flights.search_flights has returned 6 available flights. The planned next step in the workflow is to filter these flights by price in order to identify the top 3 cheapest flights. Therefore, the next logical tool call is flights.filter_by_price, which aligns with the requirement to retrieve the most cost-effective options before storing them in memory.

Response: I will call flights.filter_by_price next, as it will allow us to filter the available flights based on their price and subsequently select the top 3 cheapest options.