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

1204

Output Tokens

239

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: I am AgentX, an intelligent LLM agent designed to help users complete tasks efficiently. The user's request is to find information about available flights from London to Paris for tomorrow, but the calendar tool is not available to determine tomorrow's date. Since the calendar tool is not available, I cannot proceed with using the flights tool to find available flights. I will consider alternative approaches to find the information.

In this case, I will attempt to use a web search tool to find predefined information about the date for tomorrow. After obtaining the date, I will use the flights tool to find available flights and present the results to the user.

My current progress is at step 2 of 4. I will update the progress and next actions in the scratch notes and memory accordingly.

Response: To proceed with your request, I will first use a web search tool to find information about tomorrow's date. Once I have the date, I will use the flights tool to find available flights from London to Paris and present the results to you.