Agents

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

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.

Reasoning: 
    1. **Task Analysis**:
       - User requested flights from London to Paris for 'tomorrow'.
       - Calendar tool confirmed the date as **2025-05-29** in the previous cycle.
       - Next step: Use the 'flights' tool to fetch available flights for this date.

    2. **Tool Validation**:
       - The 'flights' tool requires `from_city`, `to_city`, and `date` in `YYYY-MM-DD` format.
       - Parameters are validated: London → Paris, date: 2025-05-29.

    3. **Action Plan**:
       - Call the 'flights' tool with the validated parameters.
       - Update scratch pad to reflect this action and prepare for result compilation.

    4. **Progress Tracking**:
       - Current step: Execute flight search (Step 3 of 4).
       - Remaining goal: Compile and present results to the user.
    

Response: ```json
{
  "action": "tool_call",
  "tool_name": "flights",
  "parameters": {
    "from_city": "London",
    "to_city": "Paris",
    "date": "2025-05-29"
  },
  "scratch_pad": {
    "current_step": "Executing flight search for London → Paris on 2025-05-29.",
    "remaining_goals": ["Compile and present flight results to the user."],
    "progress": "Step 3 of 4",
    "notes": [
      "Tool parameters validated (date: 2025-05-29, cities: London/Paris).",
      "Awaiting flight data for summarization in next cycle."
    ]
  }
}
```