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 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

Asses the current state and decide if we are on track or not

Expected output

We are on track

Model output

Reasoning: We are currently in cycle 3, having just interpreted the calendar tool’s output and confirmed the date (2025-05-29). According to the outlined plan (4 steps total), we have:
1. Determined tomorrow’s date ➜ done.
2. Interpreted the tool result and confirmed date format ➜ done.
Remaining:
3. Call the ‘flights’ tool with from_city=London, to_city=Paris, date=2025-05-29.
4. Compile and present the flight options to the user.
All prerequisite information is ready, no blockers are present, and available tools match the next required action. Therefore, progress aligns perfectly with the plan and schedule.

Response: We are on track. The next immediate action is to invoke the flights tool with: {"from_city": "London", "to_city": "Paris", "date": "2025-05-29"}.