{
    "action": "tool_call",
    "reasoning": "I have already identified several data quality issues from the evidence: 18 restaurants with zero cost, 2148 with zero ratings, 1094 with zero votes, and 12 different currencies mixing units. I also found one suspicious outlier: a max cost of 800,000 (Indonesian Rupiah). Now I need to investigate potential outliers in the rating field more carefully - the step-2 result shows max_rating is 4.9, but I should check if there are any ratings above the typical 0-5 scale that might indicate data issues. I also want to examine the Price range field for consistency, and check for any duplicate Restaurant IDs that would violate the grain.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT COUNT(*) as total_restaurants, COUNT(DISTINCT \"Restaurant ID\") as distinct_ids, COUNT(*) - COUNT(DISTINCT \"Restaurant ID\") as duplicate_count, COUNT(CASE WHEN \"Aggregate rating\" > 5.0 THEN 1 END) as ratings_above_5, COUNT(CASE WHEN \"Aggregate rating\" < 0 THEN 1 END) as ratings_below_0, MIN(\"Price range\") as min_price_range, MAX(\"Price range\") as max_price_range, COUNT(DISTINCT \"Price range\") as distinct_price_ranges FROM raw.\"Zomato Restaurant Dataset\"",
        "purpose": "Check for duplicate Restaurant IDs, validate rating bounds more carefully, and examine Price range consistency",
        "source": "raw"
    }
}