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 task involves finding information about available flights from London to Paris for tomorrow. The context indicates that all tools have been tried three times and are still unavailable. Given this, direct access to tools such as the calendar, flights, and web search is not possible. However, to still aim for the user's goal, alternative methods need to be considered. Since the flight search cannot be performed directly due to tool unavailability, the next logical step is to inform the user about the situation and suggest manual methods such as checking airline websites or contacting travel agencies directly. This approach maintains transparency with the user and provides them with actionable alternatives despite the system limitations.

Response: I regret to inform you that all attempts to access the necessary tools have failed after multiple retries. Therefore, I cannot retrieve flight information for your journey from London to Paris tomorrow using the automated tools. I recommend checking airline websites or contacting a travel agency directly to get the most updated and accurate flight options. Please accept my apologies for any inconvenience this may cause.