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

Output Tokens

Duration

Cost

Context

Input

You have decided to call the flight tool, update the scratch pad

Expected output

The scratch pad is updated with the new action, example model_output: Current step: Called 'flights' tool with parameters (from_city: London, to_city: Paris, date: 2025-05-29); waiting for tool result.
Remaining goals:
- Receive and process the flight search result.
- Summarize available flight options and present them to the user.
Notes:
- Ensure the result includes key details (flight numbers, times, prices if available).
- Store the raw flight result in working memory for reference.
- Prepare final summary once results are in.
Progress: Step 3 of 4.

Model output

Reasoning: The task is to update the scratch pad after deciding to call the flight tool. The context provided includes the user's request to find information about available flights from London to Paris for tomorrow. The previous actions involved determining tomorrow's date using the calendar tool, which returned '2025-05-29'. The current cycle is 3, and the remaining goals are to use the 'flights' tool to get available flights for the specified date and compile the results for the user. The instructions emphasize understanding the user's intent, breaking the task into steps, and using available tools effectively. The next logical step is to call the 'flights' tool with the required parameters (from_city = London, to_city = Paris, date = 2025-05-29) and update the scratch pad accordingly.

Response: Update the scratch pad to reflect the decision to call the 'flights' tool with the parameters: from_city = London, to_city = Paris, date = 2025-05-29. The scratch pad should now indicate that the next step is to interpret the result from the 'flights' tool and proceed to compile the results for the user.