Opper

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.

Agents – anthropic/claude-opus-4.1 Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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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 trajectory, I can see that:
1. The user requested information about flights from London to Paris for tomorrow
2. In a previous cycle, the calendar tool was called and returned '2025-05-29' as tomorrow's date
3. This is cycle 3, so we've already obtained the date information
4. Now I need to use the flights tool to search for available flights using the information we have:
   - From city: London
   - To city: Paris
   - Date: 2025-05-29 (tomorrow's date from the calendar tool)

The next logical step is to call the flights tool with these parameters to get the flight information the user requested.

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