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 – fireworks/glm-4.5-air Task | Opper AI

Input Tokens

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Output Tokens

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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 user has requested help with adding a yearly company dinner to their calendar and setting a reminder. Based on the instructions, when I receive a user request trigger, my first step should be to fully understand the user's intent and identify any missing information needed to complete the task. The user has mentioned seeing an email with more information, so the first logical action would be to search for this email to gather essential details like the exact date of the dinner. This approach follows the instruction to reason carefully, break the problem into steps, and use available tools before asking the user for more information.

Response: I'll search for emails related to the yearly company dinner to find the details you mentioned. This will help me gather the necessary information (like the exact date) before adding it to your calendar and setting the reminder.