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.

100
Duration
7s
Input Tokens
1309
Output Tokens
842
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 user task is to update the scratch pad, reflecting the decision to call the `flights` tool. 
1. I confirmed the necessary inputs are available: 'London' (from), 'Paris' (to), and '2025-05-29' (date), retrieved in the previous cycle.
2. I formulated the specific tool call: `call flights(from_city='London', to_city='Paris', date='2025-05-29')`.
3. I updated the `scratch_pad` to reflect this active step, shifting the focus from interpreting the calendar result to executing the flight search.
4. I updated the progress from Step 2 of 4 to Step 3 of 4.

Response: Current step: Calling the 'flights' tool to retrieve available flights from London to Paris for the confirmed date. 
Action: call flights(from_city='London', to_city='Paris', date='2025-05-29')
Remaining goals:
- Compile and present the results to the user.
Notes:
- Awaiting the output from the flight search tool.
Progress: Step 3 of 4.