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

10s

Input Tokens

1144

Output Tokens

267

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:
1. The user requested flight information from London to Paris for tomorrow
2. We're on cycle 3 of the task
3. Previous actions:
   - Determined we needed tomorrow's date
   - Used calendar tool to get the date (2025-05-29)
4. Available tools:
   - calendar (already used)
   - flights (available)
   - web_search (available)
5. We have all required parameters for the flights tool:
   - from_city: London
   - to_city: Paris
   - date: 2025-05-29

Based on this analysis:
- We have the necessary date information
- The next logical step is to search for available flights using the flights tool
- This is the most direct way to fulfill the user's request

Response: The next action should be to use the flights tool with parameters: from_city='London', to_city='Paris', date='2025-05-29' to search for available flights between these cities for tomorrow.