--- name: sql-toolkit description: Query, design, migrate, and optimize SQL databases. Use when working with SQLite, PostgreSQL, or MySQL — schema design, writing queries, creating migrations, indexing, backup/restore, and debugging slow queries. No ORMs required. metadata: {"clawdbot":{"emoji":"🗄️","requires":{"anyBins":["sqlite3","psql","mysql"]},"os":["linux","darwin","win32"]}} ---

SQL Toolkit

Work with relational databases directly from the command line. Covers SQLite, PostgreSQL, and MySQL with patterns for schema design, querying, migrations, indexing, and operations.

When to Use

• Creating or modifying database schemas
• Writing complex queries (joins, aggregations, window functions, CTEs)
• Building migration scripts
• Optimizing slow queries with indexes and EXPLAIN
• Backing up and restoring databases
• Quick data exploration with SQLite (zero setup)

SQLite (Zero Setup)

SQLite is included with Python and available on every system. Use it for local data, prototyping, and single-file databases.

Quick Start

# Create/open a database
sqlite3 mydb.sqlite

# Import CSV directly
sqlite3 mydb.sqlite ".mode csv" ".import data.csv mytable" "SELECT COUNT(*) FROM mytable;"

# One-liner queries
sqlite3 mydb.sqlite "SELECT * FROM users WHERE created_at > '2026-01-01' LIMIT 10;"

# Export to CSV
sqlite3 -header -csv mydb.sqlite "SELECT * FROM orders;" > orders.csv

# Interactive mode with headers and columns
sqlite3 -header -column mydb.sqlite

Schema Operations

-- Create table
CREATE TABLE users (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    email TEXT NOT NULL UNIQUE,
    name TEXT NOT NULL,
    created_at TEXT DEFAULT (datetime('now')),
    updated_at TEXT DEFAULT (datetime('now'))
);

-- Create with foreign key
CREATE TABLE orders (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    user_id INTEGER NOT NULL REFERENCES users(id) ON DELETE CASCADE,
    total REAL NOT NULL CHECK(total >= 0),
    status TEXT NOT NULL DEFAULT 'pending' CHECK(status IN ('pending','paid','shipped','cancelled')),
    created_at TEXT DEFAULT (datetime('now'))
);

-- Add column
ALTER TABLE users ADD COLUMN phone TEXT;

-- Create index
CREATE INDEX idx_orders_user_id ON orders(user_id);
CREATE UNIQUE INDEX idx_users_email ON users(email);

-- View schema
.schema users
.tables

PostgreSQL

Connection

# Connect
psql -h localhost -U myuser -d mydb

# Connection string
psql "postgresql://user:pass@localhost:5432/mydb?sslmode=require"

# Run single query
psql -h localhost -U myuser -d mydb -c "SELECT NOW();"

# Run SQL file
psql -h localhost -U myuser -d mydb -f migration.sql

# List databases
psql -l

Schema Design Patterns

-- Use UUIDs for distributed-friendly primary keys
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
    email TEXT NOT NULL,
    name TEXT NOT NULL,
    password_hash TEXT NOT NULL,
    role TEXT NOT NULL DEFAULT 'user' CHECK(role IN ('user','admin','moderator')),
    created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    CONSTRAINT users_email_unique UNIQUE(email)
);

-- Auto-update updated_at
CREATE OR REPLACE FUNCTION update_modified_column()
RETURNS TRIGGER AS $$
BEGIN
    NEW.updated_at = NOW();
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER update_users_modtime
    BEFORE UPDATE ON users
    FOR EACH ROW EXECUTE FUNCTION update_modified_column();

-- Enum type (PostgreSQL-specific)
CREATE TYPE order_status AS ENUM ('pending', 'paid', 'shipped', 'delivered', 'cancelled');

CREATE TABLE orders (
    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
    user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
    status order_status NOT NULL DEFAULT 'pending',
    total NUMERIC(10,2) NOT NULL CHECK(total >= 0),
    metadata JSONB DEFAULT '{}',
    created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

-- Partial index (only index active orders — smaller, faster)
CREATE INDEX idx_orders_active ON orders(user_id, created_at)
    WHERE status NOT IN ('delivered', 'cancelled');

-- GIN index for JSONB queries
CREATE INDEX idx_orders_metadata ON orders USING GIN(metadata);

JSONB Queries (PostgreSQL)

-- Store JSON
INSERT INTO orders (user_id, total, metadata)
VALUES ('...', 99.99, '{"source": "web", "coupon": "SAVE10", "items": [{"sku": "A1", "qty": 2}]}');

-- Query JSON fields
SELECT * FROM orders WHERE metadata->>'source' = 'web';
SELECT * FROM orders WHERE metadata->'items' @> '[{"sku": "A1"}]';
SELECT metadata->>'coupon' AS coupon, COUNT(*) FROM orders GROUP BY 1;

-- Update JSON field
UPDATE orders SET metadata = jsonb_set(metadata, '{source}', '"mobile"') WHERE id = '...';

MySQL

Connection

mysql -h localhost -u root -p mydb
mysql -h localhost -u root -p -e "SELECT NOW();" mydb

Key Differences from PostgreSQL

-- Auto-increment (not SERIAL)
CREATE TABLE users (
    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
    email VARCHAR(255) NOT NULL UNIQUE,
    name VARCHAR(255) NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

-- JSON type (MySQL 5.7+)
CREATE TABLE orders (
    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
    user_id BIGINT UNSIGNED NOT NULL,
    metadata JSON,
    FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
);

-- Query JSON
SELECT * FROM orders WHERE JSON_EXTRACT(metadata, '$.source') = 'web';
-- Or shorthand:
SELECT * FROM orders WHERE metadata->>'$.source' = 'web';

Query Patterns

Joins

-- Inner join (only matching rows)
SELECT u.name, o.total, o.status
FROM users u
INNER JOIN orders o ON o.user_id = u.id
WHERE o.created_at > '2026-01-01';

-- Left join (all users, even without orders)
SELECT u.name, COUNT(o.id) AS order_count, COALESCE(SUM(o.total), 0) AS total_spent
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
GROUP BY u.id, u.name;

-- Self-join (find users with same email domain)
SELECT a.name, b.name, SPLIT_PART(a.email, '@', 2) AS domain
FROM users a
JOIN users b ON SPLIT_PART(a.email, '@', 2) = SPLIT_PART(b.email, '@', 2)
WHERE a.id < b.id;

Aggregations

-- Group by with having
SELECT status, COUNT(*) AS cnt, SUM(total) AS revenue
FROM orders
GROUP BY status
HAVING COUNT(*) > 10
ORDER BY revenue DESC;

-- Running total (window function)
SELECT date, revenue,
    SUM(revenue) OVER (ORDER BY date) AS cumulative_revenue
FROM daily_sales;

-- Rank within groups
SELECT user_id, total,
    RANK() OVER (PARTITION BY user_id ORDER BY total DESC) AS rank
FROM orders;

-- Moving average (last 7 entries)
SELECT date, revenue,
    AVG(revenue) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma_7
FROM daily_sales;

Common Table Expressions (CTEs)

-- Readable multi-step queries
WITH monthly_revenue AS (
    SELECT DATE_TRUNC('month', created_at) AS month,
           SUM(total) AS revenue
    FROM orders
    WHERE status = 'paid'
    GROUP BY 1
),
growth AS (
    SELECT month, revenue,
           LAG(revenue) OVER (ORDER BY month) AS prev_revenue,
           ROUND((revenue - LAG(revenue) OVER (ORDER BY month)) /
                 NULLIF(LAG(revenue) OVER (ORDER BY month), 0) * 100, 1) AS growth_pct
    FROM monthly_revenue
)
SELECT * FROM growth ORDER BY month;

-- Recursive CTE (org chart / tree traversal)
WITH RECURSIVE org_tree AS (
    SELECT id, name, manager_id, 0 AS depth
    FROM employees
    WHERE manager_id IS NULL
    UNION ALL
    SELECT e.id, e.name, e.manager_id, t.depth + 1
    FROM employees e
    JOIN org_tree t ON e.manager_id = t.id
)
SELECT REPEAT('  ', depth) || name AS org_chart FROM org_tree ORDER BY depth, name;

Migrations

Manual Migration Script Pattern

...