{
    "action": "tool_call",
    "reasoning": "I've already found several data quality issues from the evidence: suspicious description_score values in beer_ratings (-10495 to 500, with 244,970 extreme values), and the quality report flagged critical missing data (places.currency 100% null, beer_ratings.availability_id 99% null). Now I need to check for additional issues: temporal inconsistencies (future dates, impossible sequences), text encoding problems, negative values in measures that should be positive, and format inconsistencies. Let me start by checking temporal columns for impossible dates (future dates beyond reasonable data collection, or dates before the platform existed).",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT 'beer_ratings.created_at' AS column_name, COUNT(*) AS future_dates FROM raw.beer_ratings WHERE created_at > CURRENT_TIMESTAMP UNION ALL SELECT 'beer_ratings.updated_at', COUNT(*) FROM raw.beer_ratings WHERE updated_at > CURRENT_TIMESTAMP UNION ALL SELECT 'beers.created_at', COUNT(*) FROM raw.beers WHERE created_at > CURRENT_TIMESTAMP UNION ALL SELECT 'beers.updated_at', COUNT(*) FROM raw.beers WHERE updated_at > CURRENT_TIMESTAMP UNION ALL SELECT 'users.created_at', COUNT(*) FROM raw.users WHERE created_at > CURRENT_TIMESTAMP UNION ALL SELECT 'users.updated_at', COUNT(*) FROM raw.users WHERE updated_at > CURRENT_TIMESTAMP UNION ALL SELECT 'places.created_at', COUNT(*) FROM raw.places WHERE created_at > CURRENT_TIMESTAMP UNION ALL SELECT 'places.updated_at', COUNT(*) FROM raw.places WHERE updated_at > CURRENT_TIMESTAMP",
        "purpose": "Check for future dates in temporal columns that would indicate data quality issues",
        "source": "raw"
    }
}