Instructions

Trigger this skill when you observe a search result page (e.g., containing "Page 1 (Total results: 50)" and multiple product listings).

1. Extract User Requirements

First, parse the user's instruction from the observation. Identify the following key attributes:

• Product Type: (e.g., "woman's us size 5 high heel shoe")
• Specific Attributes: (e.g., "rubber sole", "color patent-beige")
• Price Constraint: (e.g., "price lower than 90.00 dollars")

2. Analyze Search Results

For each product listing in the observation (typically formatted as [ASIN/Product ID] [SEP] [Title] [SEP] [Price Range]):

1. Extract the Product ID (e.g., B09GXNYJCD).
2. Extract the Product Title.
3. Extract the Price. Convert any range (e.g., "$49.99 to $54.99") to its maximum value for comparison against the budget.
4. Perform a textual match between the title/description and the required attributes (size, color, material like "rubber", product type).

3. Score and Prioritize

Use the bundled Python script analyze_results.py to perform a consistent, deterministic analysis.

1. Run the script with the extracted user requirements and the list of product data.
2. The script will output a prioritized list of candidate Product IDs, sorted by a match score.

4. Output and Next Action

Present the analysis in this format: