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.

Duration

Input Tokens

1166

Output Tokens

645

Cost

$0.00

Context

Input

The tool call has returned an error. What should you do?

Expected output

Interpret the error and if appropriate, retry the tool call.

Model output

Reasoning: The calendar tool returned an error, so the agent cannot retrieve tomorrow's date automatically. According to the instructions, when a tool fails the next action is to reason about the error and decide on an alternative approach, with a maximum of three retries. The best alternative here is to use the web_search tool to obtain the current date, compute tomorrow’s date from that, and then call the flights tool. This path avoids relying on the unavailable calendar tool and directly addresses the user’s goal of finding flights from London to Paris tomorrow.

Response: Try fetching today’s date using the web_search tool. Once you have the current date, calculate tomorrow’s date, then call the flights tool with from_city = "London", to_city = "Paris", and date = <calculated tomorrow’s date>. This will provide the user with the requested flight information.