{
    "action": "tool_call",
    "reasoning": "The question asks for distinct value counts across categorical columns. I already have inspect_columns output showing all 25 columns with their distinct counts. The categorical columns (role=dimension or role=attribute, excluding identifiers and spatial) are: Cuisines (~1851 distinct), Currency (~11 distinct), Has Table booking (~2 distinct), Has Online delivery (~2 distinct), Is delivering now (~2 distinct), Switch to order menu (~1 distinct), Price range (~4 distinct), Rating color (~6 distinct), Rating text (~6 distinct), Restaurant Name (~7003 distinct), and Address (~8428 distinct). However, the inspect_columns output shows approximate distinct counts (indicated by ~). To provide exact counts for the answer, I should query the actual distinct counts with SQL.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(DISTINCT \"Restaurant Name\") as restaurant_name_distinct, COUNT(DISTINCT \"Cuisines\") as cuisines_distinct, COUNT(DISTINCT \"Currency\") as currency_distinct, COUNT(DISTINCT \"Has Table booking\") as has_table_booking_distinct, COUNT(DISTINCT \"Has Online delivery\") as has_online_delivery_distinct, COUNT(DISTINCT \"Is delivering now\") as is_delivering_now_distinct, COUNT(DISTINCT \"Switch to order menu\") as switch_to_order_menu_distinct, COUNT(DISTINCT \"Price range\") as price_range_distinct, COUNT(DISTINCT \"Rating color\") as rating_color_distinct, COUNT(DISTINCT \"Rating text\") as rating_text_distinct, COUNT(DISTINCT \"Address\") as address_distinct FROM raw.\"Zomato Restaurant Dataset\"",
        "purpose": "Get exact distinct counts for all categorical columns in the dataset",
        "source": "raw"
    }
}