{
    "action": "tool_call",
    "reasoning": "AI_Tool labels contain case/spelling variants (e.g. ChatGPT, Chat GPT, chatgpt). Run one normalised query on raw to give a clean productivity-by-tool comparison with sample sizes.",
    "tool": "query_sql",
    "args": {
        "sql": "WITH n AS (SELECT CASE WHEN lower(replace(trim(AI_Tool),' ','')) = 'chatgpt' THEN 'ChatGPT' WHEN lower(trim(AI_Tool)) IN ('copilot','microsoft copilot') THEN 'Microsoft Copilot' WHEN lower(trim(AI_Tool)) IN ('gemini','google gemini') THEN 'Google Gemini' WHEN lower(trim(AI_Tool)) = 'claude' THEN 'Claude' WHEN AI_Tool IS NULL OR trim(AI_Tool) = '' THEN '(blank)' ELSE trim(AI_Tool) END AS tool, Productivity_Score, Satisfaction_Score FROM raw.AI_Usage_and_Impact_on_Students_and_Professionals) SELECT tool, COUNT(*) AS users, ROUND(AVG(Productivity_Score),2) AS avg_productivity, ROUND(MEDIAN(Productivity_Score),2) AS median_productivity, ROUND(STDDEV(Productivity_Score),2) AS sd_productivity, ROUND(AVG(Satisfaction_Score),2) AS avg_satisfaction FROM n GROUP BY tool ORDER BY avg_productivity DESC",
        "purpose": "Productivity score by cleaned AI_Tool",
        "source": "raw"
    }
}