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

13s

Input Tokens

1192

Output Tokens

861

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 on the previous cycle. According to the instructions, I should decide the next action after a tool error, with up to 3 retries allowed. However, since the goal is to find tomorrow's date for the flights query, an alternative and more reliable approach is to use the web_search tool to get the current date. This avoids retrying a potentially unreliable tool. After obtaining the current date, I can compute tomorrow's date in YYYY-MM-DD format and then call the flights tool to search for flights from London to Paris. This is the most direct and effective path given the available tools.

Response: Next action: Use the web_search tool with query 'current date' to retrieve today's date. Then compute tomorrow's date, and subsequently call the flights tool with parameters from_city='London', to_city='Paris', date='<computed_tomorrow_date>'.