Agents – groq/moonshotai/kimi-k2-instruct Task | Opper AI

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.

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Context

Input

The user has replied: "Three days before is fine."  According to the plan for the yearly company-dinner task, what is the next action?

Expected output

Call email.search_emails with a query such as "yearly company dinner" (optionally including the current year) to locate the relevant email(s) containing the event details, and store the returned email_id(s) for the subsequent email.read_email step.

Model output

Reasoning: The user has now provided the missing input: they want the reminder set 3 days before the yearly company-dinner. The immediate next step from the scratch-pad plan is to search the user’s emails for information about the yearly company dinner so that I can extract the exact event date. Therefore I will invoke the email tool’s ‘search_emails’ action with a query that should surface the relevant message.

Response: The next action is to search the user’s emails for the yearly company-dinner details. I will execute a search using the email tool with the query “yearly company dinner” to find the message that contains the event date and any other pertinent information.