{
    "action": "tool_call",
    "reasoning": "The dataset contains NFL game scores from 2010-2026. To identify natural segmentation approaches, I should examine the dimensional columns and their distributions. From step-1, I can see key dimensions: Season, Week, GameStatus, GameSlot, AwayTeam, HomeTeam. I'll query the raw scores table to understand the distribution of these dimensions and identify meaningful groupings.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Season, COUNT(*) as games, COUNT(DISTINCT AwayTeam) as away_teams, COUNT(DISTINCT HomeTeam) as home_teams, COUNT(DISTINCT Week) as weeks, COUNT(DISTINCT GameSlot) as time_slots, COUNT(DISTINCT GameStatus) as statuses FROM raw.2010_2026_scores GROUP BY Season ORDER BY Season",
        "purpose": "Understand the temporal structure and dimensional coverage by season to identify natural segmentation patterns",
        "source": "raw"
    }
}