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

189

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: Step-by-step thought process:
1. The user's request is to find available flights from London to Paris for tomorrow.
2. Previous action: Called calendar tool, which returned '2025-05-29' as tomorrow's date.
3. Now, with the date confirmed, the next logical step is to use the 'flights' tool to query for available flights.
4. Required parameters for flights tool: from_city='London', to_city='Paris', date='2025-05-29'.
5. No need for web_search or calendar at this point, as we have all necessary info.
6. This is the most direct path to fulfilling the user's request.

Response: call_tool:flights{"from_city":"London","to_city":"Paris","date":"2025-05-29"}