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

1230

Output Tokens

166

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's request is to find available flights from London to Paris for tomorrow. From the previous cycle, the calendar tool was called and returned the date '2025-05-29' as tomorrow. Now, with this date confirmed, the most direct next action is to use the 'flights' tool to query for available flights, providing the required parameters: from_city as 'London', to_city as 'Paris', and date as '2025-05-29'. This will gather the necessary information to fulfill the user's request without unnecessary steps.

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