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 Task | Opper AI

Input Tokens

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Output Tokens

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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 that tomorrow's date is '2025-05-29'
3. I'm now in cycle 3, which means it's time to use the flights tool to search for available flights

I have all the necessary information:
- Departure city: London
- Arrival city: Paris
- Date: 2025-05-29 (tomorrow's date from the calendar tool)

The flights tool is available and requires exactly these three parameters. This is the logical next step to fulfill the user's request.

Response: I will call the flights tool to search for available flights from London to Paris on 2025-05-29. This action directly addresses the user's request now that we have confirmed tomorrow's date.