AI SQL Query Generator

How It Works

Describe your table structure (or paste your schema) and what you want to find out. The generator returns the SQL query, a plain-English breakdown of each clause, and a note on any assumptions it made about your schema.

What to Provide

SQL Query + Explanation

Replace [[tokens]] with your details. This is the finished deliverable.

Query

[[the SQL query]]

Plain-English Breakdown

Assumptions Made

[[Any assumptions about column names, data types, or relationships that should be verified against your actual schema]]

Worked Examples

Example 1: "Which customers spent the most last month?"

SELECT customer_id, SUM(order_total) AS total_spent
FROM orders
WHERE order_date >= DATE_TRUNC('month', CURRENT_DATE) - INTERVAL '1 month'
  AND order_date < DATE_TRUNC('month', CURRENT_DATE)
GROUP BY customer_id
ORDER BY total_spent DESC
LIMIT 10;

Explanation: Filters to last calendar month, sums order totals per customer, sorts highest first, returns top 10.

Example 2: "Find users who signed up but never made a purchase"

SELECT u.id, u.email
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE o.id IS NULL;

Explanation: LEFT JOIN keeps all users even without a matching order; filtering where the order side is NULL isolates users with zero orders.

Common Mistakes to Avoid

• Not verifying column names against your actual schema before running: the generator guesses reasonable names but yours may differ
• Running an UPDATE/DELETE query without a WHERE clause test first: always test the SELECT equivalent before a destructive query
• Ignoring timezone/date handling differences between database engines
• Not indexing columns used in WHERE/JOIN on large tables, causing slow queries
• Trusting output on production data without testing on a sample first

Always run the SELECT version of a query and eyeball the results before converting it to an UPDATE or DELETE.