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

1038

Output Tokens

326

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 information about available flights from London to Paris for tomorrow. In the previous cycle we used the calendar tool to determine tomorrow's date, which returned 2025-05-29. The next logical step is to retrieve flight options for that date using the available 'flights' tool. Therefore, the next action should be a call to the flights tool with the parameters: from_city = 'London', to_city = 'Paris', date = '2025-05-29'.

Response: Call the flights tool with parameters: { "from_city": "London", "to_city": "Paris", "date": "2025-05-29" }.