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

1218

Output Tokens

163

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 information about available flights from London to Paris for tomorrow. In the previous cycle, the calendar tool was used to determine tomorrow's date, which returned '2025-05-29'. Now, with the date available, the most direct next step is to use the 'flights' tool to query for available flights. The parameters are: from_city='London', to_city='Paris', date='2025-05-29'. This will provide the necessary flight information without unnecessary detours. No other tools are needed at this stage.

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