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/deepseek-r1 Task | Opper AI

Input Tokens

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Output Tokens

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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 provided confirmation that the reminder should be set 3 days before the event. According to the pre-defined plan (scratch_pad) and context trajectory:
1. Completed: Requested reminder days (Step 2)
2. Next Action: Search emails for "yearly company dinner" details to locate the event date (Step 3)
3. Following Steps: Read email content -> Add calendar event with 3-day reminder -> Check conflicts
This progression ensures we first obtain the critical missing information (event date) before creating the calendar entry with the confirmed reminder preference.

Response: Next action: Perform email search using the 'email' tool with search query: {"query":"yearly company dinner"}. Required to locate the event date before proceeding with calendar operations.