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.

Input Tokens

Output Tokens

Duration

Cost

Context

Input

You have received responses from all tools after 3 retries. They are all unavailable. Can you still achieve your goal?

Expected output

No, I cannot achieve my goal.

Model output

Reasoning: The remaining goals explicitly require live data from the tools (Calendar to confirm tomorrow’s date and Flights to fetch real-time availability). After three failed retries each tool is still returning an error, meaning we have exhausted the allowed attempts. Without at least the Flights tool (or an alternative data source) we cannot retrieve up-to-date flight listings for the requested date. My internal knowledge does not contain real-time inventories, so I cannot substitute that information. I could offer general guidance (e.g., usual airlines on the route, how to book, approximate schedules), but that would not satisfy the original request for actual available flights. Therefore the core goal—“use ‘flights’ tool to get available flights from London to Paris and present results”—is unattainable under the current constraints.

Response: Unfortunately, because every required tool remains unavailable after the maximum number of retries, I’m unable to pull real-time flight data. As a result I cannot complete the task of listing tomorrow’s available flights from London to Paris. I can still offer general advice on typical airlines or booking strategies if that would be helpful.