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

1155

Output Tokens

784

Cost

$0.00

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 calendar tool returned '2025-05-29' as tomorrow's date. Now I need to interpret this result and proceed with the next step in the trajectory. According to the remaining goals, I must use the 'flights' tool to search for available flights from London to Paris for 2025-05-29. The date format 'YYYY-MM-DD' matches the tool's requirements. The flights tool requires three parameters: from_city (London), to_city (Paris), and date (2025-05-29). This is the logical next action to progress from Step 2 to Step 3. After calling the flights tool, the scratch pad should be updated to reflect that we've moved to the flight search execution phase, and we'll need to compile the results for presentation.

Response: I have interpreted the calendar tool result confirming tomorrow's date as 2025-05-29. The next action is to call the flights tool with the parameters: from_city='London', to_city='Paris', date='2025-05-29'. This will search for available flights matching the user's request. After receiving the flight search results, I'll update the scratch pad to reflect the new state and proceed to compile the results for user presentation. Current progress will advance from Step 2 to Step 3.