{
    "action": "tool_call",
    "reasoning": "Rank the four measures by how strongly they separate species using eta-squared (share of variance explained by Species), computed over raw.Iris in one query.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH u AS (SELECT Species, 'SepalLengthCm' AS metric, SepalLengthCm AS v FROM raw.Iris UNION ALL SELECT Species, 'SepalWidthCm', SepalWidthCm FROM raw.Iris UNION ALL SELECT Species, 'PetalLengthCm', PetalLengthCm FROM raw.Iris UNION ALL SELECT Species, 'PetalWidthCm', PetalWidthCm FROM raw.Iris), g AS (SELECT metric, Species, VAR_POP(v)*COUNT(*) AS ssw FROM u GROUP BY metric, Species), t AS (SELECT metric, VAR_POP(v)*COUNT(*) AS sst FROM u GROUP BY metric) SELECT g.metric, ROUND(1 - SUM(g.ssw)/MAX(t.sst), 4) AS eta_squared FROM g JOIN t ON g.metric = t.metric GROUP BY g.metric ORDER BY eta_squared DESC",
        "purpose": "Rank the four numeric measures by share of variance explained by species",
        "source": "raw"
    }
}