Sql Query Builder

Generates optimized SQL queries from natural language descriptions, supporting SELECT, INSERT, UPDATE, DELETE with JOINs, indexes, and best practices.

What This Command Does

Generated Queries:

• SELECT queries with JOINs
• INSERT, UPDATE, DELETE operations
• Aggregations and GROUP BY
• Subqueries and CTEs
• Indexes and optimization tips
• PostgreSQL, MySQL, SQLite syntax

Output: Production-ready SQL queries

Time: 2-3 minutes

Usage

# Generate query from description
/sql-query-builder "Get all users with their posts"

# Shortcut
/sqb "Find top 10 products by sales"

# Complex query
/sqb "Get users who have made purchases in last 30 days, grouped by country"

# Specific database
/sqb "List orders with customer info" --database postgresql

Example Output

Input:

/sqb "Get all blog posts with author info and comment count, ordered by recent"

Generated SQL:

-- Query: Get all blog posts with author info and comment count
-- Database: PostgreSQL
-- Optimized for performance with proper indexes

-- Main query
SELECT
  p.id,
  p.title,
  p.slug,
  p.content,
  p.published,
  p.created_at,
  p.updated_at,
  -- Author information
  u.id AS author_id,
  u.name AS author_name,
  u.email AS author_email,
  -- Comment count (calculated)
…

Query Examples

1. Simple SELECT

Request: "Get all active users"

SELECT
  id,
  email,
  name,
  created_at
FROM users
WHERE active = true
ORDER BY created_at DESC;

-- Index recommendation
CREATE INDEX idx_users_active ON users(active, created_at DESC);

2. JOIN Queries

Request: "Get orders with customer and product information"

SELECT
  o.id AS order_id,
  o.order_date,
  o.total,
  o.status,
  -- Customer info
  c.id AS customer_id,
  c.name AS customer_name,
  c.email AS customer_email,
  -- Order items
  oi.quantity,
  oi.price AS unit_price,
  -- Product info
  p.id AS product_id,
  p.name AS product_name
FROM orders o
INNER JOIN customers c ON o.customer_id = c.id
INNER JOIN order_items oi ON o.id = oi.order_id
…

3. Aggregations

Request: "Get total sales by product category"

SELECT
  c.name AS category,
  COUNT(DISTINCT o.id) AS order_count,
  SUM(oi.quantity) AS units_sold,
  SUM(oi.quantity * oi.price) AS total_revenue,
  AVG(oi.price) AS avg_price
FROM categories c
INNER JOIN products p ON c.id = p.category_id
INNER JOIN order_items oi ON p.id = oi.product_id
INNER JOIN orders o ON oi.order_id = o.id
WHERE o.status = 'completed'
  AND o.created_at >= CURRENT_DATE - INTERVAL '1 year'
GROUP BY c.id, c.name
HAVING SUM(oi.quantity * oi.price) > 1000
ORDER BY total_revenue DESC;

4. Subqueries

Request: "Get users who have never made a purchase"

SELECT
  u.id,
  u.email,
  u.name,
  u.created_at
FROM users u
WHERE NOT EXISTS (
  SELECT 1
  FROM orders o
  WHERE o.customer_id = u.id
)
ORDER BY u.created_at DESC;

-- Alternative using LEFT JOIN (often faster)
SELECT
  u.id,
  u.email,
  u.name,
…

5. Common Table Expressions (CTEs)

Request: "Get top customers by purchase amount with their order history"

WITH customer_totals AS (
  SELECT
    c.id,
    c.name,
    c.email,
    COUNT(o.id) AS order_count,
    SUM(o.total) AS total_spent
  FROM customers c
  INNER JOIN orders o ON c.id = o.customer_id
  WHERE o.status = 'completed'
  GROUP BY c.id, c.name, c.email
  HAVING SUM(o.total) > 500
)
SELECT
  ct.*,
  o.id AS order_id,
  o.order_date,
  o.total AS order_total
…

6. Window Functions

Request: "Rank products by sales within each category"

SELECT
  p.id,
  p.name AS product_name,
  c.name AS category_name,
  SUM(oi.quantity * oi.price) AS total_sales,
  RANK() OVER (
    PARTITION BY p.category_id
    ORDER BY SUM(oi.quantity * oi.price) DESC
  ) AS rank_in_category
FROM products p
INNER JOIN categories c ON p.category_id = c.id
INNER JOIN order_items oi ON p.id = oi.product_id
INNER JOIN orders o ON oi.order_id = o.id
WHERE o.status = 'completed'
GROUP BY p.id, p.name, p.category_id, c.name
ORDER BY c.name, rank_in_category;