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 – mistral/mistral-tiny-eu Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Context

Input

Of the available tools. Which ones will you need to use to successfully complete the task?

Expected output

All tools will need to be used: calendar, flights,memory

Model output

Reasoning: To complete the task of finding the cheapest flights from London to Paris for tomorrow and returning the top 3 options, I will follow these steps:

1. I will first determine the current date, then get the date for tomorrow using the Calendar tool.
2. I will use the Flights tool to search for flights from London to Paris on the determined date. I will filter the results by price to get the cheapest options and sort them by duration to prioritize shorter flights. I will retrieve the top 3 cheapest flights.
3. After getting the top 3 cheapest flights, I will store each flight details in the memory tool using a unique key for each flight.
4. I will present the top 3 cheapest flights in the format requested by the user.

If any tool call fails, I will log the failure, try again up to 3 times, and explain the failure in my response. I will optimize for minimal, effective actions and avoid redundant tool calls.

Response: Top 3 Cheapest Flights from London to Paris for Tomorrow:
1. Flight Details (Key: Flight1)
2. Flight Details (Key: Flight2)
3. Flight Details (Key: Flight3)