```json { "action": "tool_call", "reasoning": "I've found significant missing data in temporal columns (52-303 missing values out of 306 subjects). Now I need to check for outliers and impossible values in the numeric measures (AGE, TRTDURD) and examine the temporal formats more closely. I'll profile TRTDURD since it's VARCHAR and may contain non-numeric values, and check for date format inconsistencies.", "tool": "query_sql", "args": { "sql": "SELECT COUNT(*) as total_rows, COUNT(CASE WHEN TRTDURD = '..MISSING..' THEN 1 END) as trtdurd_missing_marker, COUNT(CASE WHEN TRY_CAST(TRTDURD AS INTEGER) IS NULL AND TRTDURD != '..MISSING..' THEN 1 END) as trtdurd_non_numeric, MIN(TRY_CAST(TRTDURD AS INTEGER)) as min_duration, MAX(TRY_CAST(TRTDURD AS INTEGER)) as max_duration, AVG(TRY_CAST(TRTDURD AS INTEGER)) as avg_duration, COUNT(CASE WHEN TRY_CAST(TRTDURD AS INTEGER) < 0 THEN 1 END) as negative_duration, COUNT(CASE WHEN TRY_CAST(TRTDURD AS INTEGER) > 365 THEN 1 END) as duration_over_year FROM raw.adsl", "purpose": "Check TRTDURD for non-numeric values, negative durations, and extreme outliers", "source": "raw" } } ```