I need to systematically examine the data quality issues in this boxing champions dataset. Let me analyze different aspects of data quality. {"action": "tool_call", "reasoning": "First, I'll examine the Days column more closely since it's marked as VARCHAR but should contain numeric values representing reign duration. I need to check for non-numeric values, negative numbers, or other anomalies.", "tool": "query_sql", "args": {"sql": "SELECT Days, COUNT(*) as count, MIN(CAST(NULLIF(REGEXP_REPLACE(Days, '[^0-9-]', '', 'g'), '') AS INTEGER)) as min_days, MAX(CAST(NULLIF(REGEXP_REPLACE(Days, '[^0-9-]', '', 'g'), '') AS INTEGER)) as max_days FROM raw.championsdataset WHERE Days != '' AND Days != '–' AND Days != '−' GROUP BY Days ORDER BY Days", "purpose": "Examine the Days column for data quality issues - non-numeric values, formatting inconsistencies, impossible values", "source": "raw"}}