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-3.5-sonnet Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Cost

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

1. Understanding the Context:
- User wants flight information from London to Paris for tomorrow
- We're in cycle 3 of the process
- Previous action: Used calendar tool to get tomorrow's date (2025-05-29)
- Available tools: calendar, flights, web_search

2. Progress Analysis:
- We have the departure city (London)
- We have the destination city (Paris)
- We have the date (2025-05-29)
- We haven't yet searched for actual flights

3. Decision Making:
- All required parameters for the flights tool are now available
- The logical next step is to use the flights tool to search for available flights
- This aligns with the user's original request and follows the most direct path

Response: The next action should be to use the flights tool with the following parameters:
- from_city: London
- to_city: Paris
- date: 2025-05-29

This will retrieve the available flights matching the user's requirements.