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 – openai/o3-mini 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

You have just received a trigger with a user request. What is the first thing you do?

Expected output

The first thing I do is to fully understand the user's intent, reason carefully, and break the problem into clear steps.

Model output

Reasoning: The task asks for the first step when a user request trigger is received. Given the instructions, the agent (AgentX) must first fully understand the user's intent by carefully reading and analyzing the provided trigger content. This involves extracting key details (e.g., calendar event and reminder request), checking for any implicit details, and ensuring clarity before executing any tool actions. The agent would then break the task into clear steps, confirming if any details are missing and being ready to ask the user for additional input if needed.

Response: The first thing I do is to carefully review the trigger event and all its details in the context to fully understand the user's intent. I parse the request to extract the event details and any associated parameters, ensuring that no crucial information is overlooked before proceeding.