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

44235

Output Tokens

6570

Duration

419202.264

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 requires finding information on available flights from London to Paris for tomorrow. Based on the provided context, tool failures occurred during the process, but the remaining goal involves using the 'flights' tool to retrieve flight information. The instructions indicate that, due to the trigger type 'user_request', the intent is to provide this specific flight information. All tools are marked as 'available,' implying that another attempt can be made using the 'flights' tool after reconciling any previous errors or tool availability issues. Despite the tool errors experienced, since the task involves retries and the retries have been exhausted, the next logical step is to find an alternative method. Given the ability to use a 'web_search' tool in the context, I would perform a web search to get the required flight information, bypassing the dependencies on the tools that had errors.

Response: Since direct access to the dedicated 'flights' tool reached its retry limit, the alternative approach is to perform a general web search for flights from London to Paris for tomorrow. This would provide current flight options and availability, allowing you to achieve the user's goal without further tool retries.