{
    "action": "tool_call",
    "reasoning": "I've computed correlations for several numeric columns, but I need to expand this to cover all numeric columns systematically. The dataset has play-level tables (2010_plays through 2026_plays) and a scores table (2010_2026_scores). I should compute a comprehensive correlation matrix for all numeric columns in the main plays tables to identify the strongest relationships. Let me query one of the larger plays tables to get correlations across all numeric fields.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT CORR(Season, DriveNumber) as season_drive, CORR(Season, PlayNumberInDrive) as season_playnum, CORR(Season, IsScoringDrive) as season_scoringdrive, CORR(Season, IsScoringPlay) as season_scoringplay, CORR(DriveNumber, PlayNumberInDrive) as drive_playnum, CORR(DriveNumber, IsScoringDrive) as drive_scoringdrive, CORR(DriveNumber, IsScoringPlay) as drive_scoringplay, CORR(PlayNumberInDrive, IsScoringDrive) as playnum_scoringdrive, CORR(PlayNumberInDrive, IsScoringPlay) as playnum_scoringplay, CORR(IsScoringDrive, IsScoringPlay) as scoringdrive_scoringplay FROM raw.2015_plays",
        "purpose": "Compute comprehensive correlation matrix for all numeric columns in plays table to identify strongest relationships",
        "source": "raw"
    }
}