```json { "action": "tool_call", "reasoning": "The question asks for distribution statistics (min, max, mean, median, spread) for each numeric column. The dataset card shows 4 numeric measures in raw.Iris: SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm. I should write ONE SQL query that computes all these statistics for all 4 columns at once, rather than querying one column at a time. I'll calculate min, max, avg (mean), median, and stddev (spread) for each column in a single SELECT.", "tool": "query_sql", "args": { "sql": "SELECT COUNT(*) as total_rows, MIN(SepalLengthCm) as SepalLength_min, MAX(SepalLengthCm) as SepalLength_max, AVG(SepalLengthCm) as SepalLength_mean, MEDIAN(SepalLengthCm) as SepalLength_median, STDDEV(SepalLengthCm) as SepalLength_stddev, MIN(SepalWidthCm) as SepalWidth_min, MAX(SepalWidthCm) as SepalWidth_max, AVG(SepalWidthCm) as SepalWidth_mean, MEDIAN(SepalWidthCm) as SepalWidth_median, STDDEV(SepalWidthCm) as SepalWidth_stddev, MIN(PetalLengthCm) as PetalLength_min, MAX(PetalLengthCm) as PetalLength_max, AVG(PetalLengthCm) as PetalLength_mean, MEDIAN(PetalLengthCm) as PetalLength_median, STDDEV(PetalLengthCm) as PetalLength_stddev, MIN(PetalWidthCm) as PetalWidth_min, MAX(PetalWidthCm) as PetalWidth_max, AVG(PetalWidthCm) as PetalWidth_mean, MEDIAN(PetalWidthCm) as PetalWidth_median, STDDEV(PetalWidthCm) as PetalWidth_stddev FROM raw.Iris", "purpose": "Compute distribution statistics (min, max, mean, median, standard deviation) for all four numeric columns in the Iris dataset", "source": "raw" } } ```