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

1040

Output Tokens

154

Cost

$0.00

Context

Input

What is your next action?

Expected output

The next action is to call the flight tool with the date 2025-05-29,from_city: London, to_city: Paris

Model output

Reasoning: The user wants to find flights from London to Paris for tomorrow. The current date is 2025-05-29, so 'tomorrow' is 2025-05-30. The user has already determined tomorrow's date in a previous cycle. The next logical step is to use the flights tool to search for available flights on this date. The flights tool requires three parameters: from_city ('London'), to_city ('Paris'), and date ('2025-05-30'). All required parameters are known from the context.

Response: call flights tool with parameters {from_city: 'London', to_city: 'Paris', date: '2025-05-30'}