{
    "action": "tool_call",
    "reasoning": "The quality report flagged critical missing data (99% null availability_id, 100% null places.currency) and the validation query shows 244,970 suspicious description_score values with a range of -10495 to 500 (when scores should be bounded). I need to examine the distribution of these suspicious scores and check for patterns in negative/extreme scores.",
    "tool": "query_sql",
    "purpose": "Profile description_score distribution to understand the 244,970 suspicious values and check for patterns in negative/extreme scores",
    "args": {
        "sql": "SELECT CASE WHEN description_score < 0 THEN 'negative' WHEN description_score > 100 THEN 'over_100' WHEN description_score BETWEEN 0 AND 100 THEN '0_to_100' ELSE 'null' END AS score_range, COUNT(*) AS count, MIN(description_score) AS min_score, MAX(description_score) AS max_score, ROUND(AVG(description_score), 2) AS avg_score FROM raw.beer_ratings GROUP BY 1 ORDER BY count DESC",
        "source": "raw"
    }
}