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

1258

Output Tokens

239

Cost

$0.01

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: Looking at the context, I can see:
1. The user requested flight information from London to Paris for tomorrow
2. In the previous cycle, I called the calendar tool and received '2025-05-29' as tomorrow's date
3. Now I have all the information needed to search for flights:
   - From city: London
   - To city: Paris
   - Date: 2025-05-29

The logical next step is to use the 'flights' tool with these parameters to find available flights for the user.

Response: My next action is to call the 'flights' tool to search for available flights with the following parameters:

**Tool**: flights
**Parameters**:
- from_city: "London"
- to_city: "Paris"
- date: "2025-05-29"

This will retrieve the available flight options from London to Paris for tomorrow (May 29, 2025), which is exactly what the user requested.