{
    "action": "tool_call",
    "reasoning": "I have good evidence on ranges, nulls, and basic statistics. Now I need to check for specific data quality issues: (1) inconsistent date formats in the 'First Operational Date Note' field (I saw varied formats in step-5), (2) potential outliers beyond the p99 values I found, (3) check for impossible combinations (e.g. systems with power but no chips, or cost but no hardware), (4) examine the 'Status' field which shows only 1 distinct value despite being a dimension, and (5) look at the certainty levels and their distribution.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Certainty, COUNT(*) as count, COUNT(DISTINCT \"Chip type (primary)\") as distinct_chips, AVG(\"H100 equivalents\") as avg_h100, AVG(\"Power Capacity (MW)\") as avg_power FROM raw.ai_supercomputers GROUP BY Certainty ORDER BY count DESC",
        "purpose": "Check distribution of certainty levels and whether data quality varies by certainty",
        "source": "raw"
    }
}