{
    "action": "tool_call",
    "reasoning": "The dataset card shows temporal axes in raw.boxing_klitschko: f_boxer_age and s_boxer_age. However, step-1 reveals these columns contain mixed values including 'orthodox' (a stance, not an age), so they are not clean temporal dimensions. I need to check if there's an actual date/timestamp column that could serve as a time dimension. The _ingestion_timestamp column exists but shows only one distinct value (2026-08-07), so it's not useful for trend analysis. Let me search for any date-related columns across all tables to see if there's a proper temporal dimension for analyzing trends.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT table_name, column_name, phys_type, semantic_role FROM meta.columns WHERE semantic_role = 'temporal' OR phys_type IN ('DATE', 'TIMESTAMP') OR column_name ILIKE '%date%' OR column_name ILIKE '%time%' OR column_name ILIKE '%year%'",
        "purpose": "Find all temporal columns across the dataset to identify if there's a proper time dimension for trend analysis",
        "source": "raw"
    }
}