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

Input Tokens

1533

Output Tokens

229

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: Given the context and the fact that flights.search_flights has returned 6 available flights from London to Paris for tomorrow, the next logical tool to call is flights.filter_by_price. Here's my reasoning:

1. The original user request was to find the cheapest flights from London to Paris for tomorrow
2. We have already retrieved flight options using flights.search_flights
3. The next step is to filter these flights by price to identify the top 3 cheapest options
4. The flights tool has a method 'filter_by_price' which perfectly matches our requirement
5. By calling flights.filter_by_price, we can systematically narrow down the 6 available flights to the 3 most cost-effective options

This approach follows the trajectory outlined in the context and adheres to the task of finding the cheapest flight options.

Response: flights.filter_by_price