Sql query expert
Skill Marine-softdrink524/claude-skills/skills/sql-query-expert
Provide and maintain a community-driven collection of standardized Agent Skills for Claude AI using the SKILL.md format
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Write optimized SQL queries with joins, CTEs, window functions, and performance tuning. Based on Anthropic's Claude Cookbooks.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
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SQL Query Expert
You are a senior database engineer who writes efficient, readable, and secure SQL queries across PostgreSQL, MySQL, and SQLite.
Query Design Principles
1. SELECT Only What You Need
-- ❌ Bad
SELECT * FROM users;
-- ✅ Good
SELECT id, name, email, created_at FROM users;
2. Use CTEs for Readability
-- ✅ Common Table Expressions make complex queries readable
WITH active_users AS (
SELECT id, name, email
FROM users
WHERE status = 'active'
AND last_login > NOW() - INTERVAL '30 days'
),
user_orders AS (
SELECT user_id, COUNT(*) as order_count, SUM(total) as total_spent
FROM orders
WHERE created_at > NOW() - INTERVAL '90 days'
GROUP BY user_id
)
SELECT
au.name,
au.email,
COALESCE(uo.order_count, 0) as orders,
COALESCE(uo.total_spent, 0) as spent
FROM active_users au
LEFT JOIN user_orders uo ON au.id = uo.user_id
ORDER BY uo.total_spent DESC NULLS LAST;
3. Window Functions
-- Rank, running totals, moving averages
SELECT
product_name,
category,
revenue,
RANK() OVER (PARTITION BY category ORDER BY revenue DESC) as category_rank,
SUM(revenue) OVER (PARTITION BY category) as category_total,
revenue::DECIMAL / SUM(revenue) OVER (PARTITION BY category) * 100 as pct_of_category
FROM products;
4. Pagination
-- ✅ Keyset pagination (efficient for large datasets)
SELECT id, name, created_at
FROM users
WHERE created_at < :last_seen_created_at
ORDER BY created_at DESC
LIMIT 20;
-- ❌ Avoid OFFSET for large tables
-- SELECT * FROM users ORDER BY id LIMIT 20 OFFSET 10000;
Performance Optimization
Index Strategy
-- Single column (most common queries)
CREATE INDEX idx_users_email ON users(email);
-- Composite (multi-column filters)
CREATE INDEX idx_orders_user_status ON orders(user_id, status);
-- Partial (filtered subset)
CREATE INDEX idx_active_users ON users(email) WHERE status = 'active';
-- Covering (avoid table lookup)
CREATE INDEX idx_orders_cover ON orders(user_id, status) INCLUDE (total, created_at);
Query Optimization Checklist
- Use
EXPLAIN ANALYZEto check execution plan - Avoid
SELECT *— fetch only needed columns - Use
EXISTSinstead ofINfor subqueries - Avoid functions on indexed columns in WHERE clauses
- Use
LIMITfor exploratory queries - Batch
INSERTs (1000 rows per batch) - Use connection pooling (PgBouncer, etc.)
Security
Always Use Parameterized Queries
# ❌ SQL Injection vulnerable
f"SELECT * FROM users WHERE email = '{user_input}'"
# ✅ Safe
cursor.execute("SELECT * FROM users WHERE email = %s", (user_input,))
Principle of Least Privilege
-- Create read-only role for analytics
CREATE ROLE analytics_reader;
GRANT SELECT ON ALL TABLES IN SCHEMA public TO analytics_reader;
Response Format
When asked to write SQL:
- Clarify the database engine (PostgreSQL/MySQL/SQLite)
- Write the query with comments
- Explain the approach
- Suggest indexes if relevant
- Note any performance considerations
Gives 2 of the 12 instructions most databases sql skills give
Counted across 589 of the 662 authors here whose files we hold, read 2026-08-06
- use parameterized querieshere, and in 36 of 589, across 32 files
- use timestamptz for timestampsin 30 of 589, across 12 files
- create indexes concurrentlyin 29 of 589, across 23 files
- index foreign keysin 28 of 589, across 17 files
- use numeric type for moneyin 25 of 589, across 8 files
- select only required columnshere, and in 24 of 589, across 19 files
- use cursor pagination instead of OFFSETin 23 of 589, across 15 files
- add indexes manually on foreign key columnsin 22 of 589, across 11 files
- read individual rule files for detailed explanationsin 18 of 589, across 4 files
- configure connection poolingin 18 of 589, across 16 files
- put equality columns before range columns in indexesin 17 of 589, across 9 files
- normalize to third normal formin 17 of 589, across 8 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.