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

1144

Output Tokens

282

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: Let me analyze the current situation and determine my next action:

1. The user has requested information about flights from London to Paris for tomorrow.
2. We're currently in cycle 3 of this task.
3. In previous cycles, we determined that tomorrow's date is 2025-05-29 using the calendar tool.
4. Available tools include: calendar, flights, and web_search.
5. The logical next step is to use the flights tool to search for available flights between London and Paris on the date we've identified.

Since we now have all the required parameters for the flights tool (from_city: London, to_city: Paris, date: 2025-05-29), the most direct and effective path forward is to query this tool.

Response: My next action is to use the flights tool to search for available flights from London to Paris on 2025-05-29 (tomorrow's date). I will call the flights tool with the parameters:
- from_city: London
- to_city: Paris
- date: 2025-05-29

This will provide the user with the flight information they requested.