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

18s

Input Tokens

1192

Output Tokens

716

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 user requested flights from London to Paris for tomorrow, so we needed tomorrow's date. We called the calendar tool, which returned an error 'tool not available'. Checking the available tools, the calendar tool status is 'available', indicating the error might be transient. The instructions say that when a tool returns an error, we should think about the error and decide the next action, with a maximum of 3 retries per tool. Since this is the first attempt, retrying the calendar tool is a logical next step. If it fails again, we can switch to the web_search tool to find the current date and calculate tomorrow's date, then proceed to the flights tool.

Response: Retry the calendar tool once more. If the error persists, use the web_search tool to obtain the current date, then calculate tomorrow's date and call the flights tool with that date in YYYY-MM-DD format.