inspect_columns.js

import { createClient } from '@supabase/supabase-js';

const SUPABASE_URL = process.env.VITE_SUPABASE_URL || "https://vawouugtzwmejxqkeqqj.supabase.co";
const SUPABASE_KEY = process.env.VITE_SUPABASE_PUBLISHABLE_KEY || "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6InZhd291dWd0endtZWp4cWtlcXFqIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NTI3Njk3MTIsImV4cCI6MjA2ODM0NTcxMn0.qtZk3zk5RMqzlPNhxCkTM6fyVQX5ULGt7nna_XOUr00";

const supabase = createClient(SUPABASE_URL, SUPABASE_KEY);

async function inspectColumns() {
    console.log('Fetching columns for superduper_execution_log...');

    // We can't query information_schema directly via supabase-js easily unless exposed.
    // Instead, let's try to query the table with `.select('*').limit(0)` which usually works to get structure if typed, but raw JS client returns strict data.
    // Actually, let's try to infer from the error of selecting a non-existent column, but we already got the error.

    // Use a known method: try to select specific columns we EXPECT and see which one fails, or just assume the error "task_id does not exist" is true.
    // The error was explicit. 

    console.log('Fetching columns for tasks...');
    // We saw keys earlier: assigned_agent_id is likely the one.
    // Let's verify by just printing a task again.

    const { data: tasks } = await supabase.from('tasks').select('*').limit(1);
    if (tasks && tasks.length) {
        console.log('Task Keys:', Object.keys(tasks[0]));
    }
}

inspectColumns();