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.

Duration

10s

Input Tokens

1345

Output Tokens

148

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 user wants the cheapest flights from London to Paris for tomorrow (2025-05-29). The flights.search_flights tool has been called and returned 6 available flights. The next step is to filter these flights by price to identify the top 3 cheapest options. According to the available tools, the filter_by_price method can be used to achieve this. After filtering, the results will be stored in memory.

Response: Call filter_by_price on the flights tool with parameters: from_city='London', to_city='Paris', date='2025-05-29', and then sort the results by price to get the top 3 cheapest options.