database-mysql

name	database-mysql
description	MySQL database patterns. Use when querying database schema, exploring data, understanding table relationships, or debugging data issues.
triggers	["mysql","database","db","schema","query","sql","tables","migration"]

MySQL Database Guide

When to Use This Skill

Use when exploring database schema, understanding data relationships, debugging data issues, writing queries, or creating migrations.

MCP Tools

Use the MySQL MCP for read-only access:

list_tables  — List all tables in the database
read_query   — Execute SELECT queries (read-only)

Common Patterns

Explore Schema

SHOW TABLES;
SHOW COLUMNS FROM <table>;
DESCRIBE <table>;
SHOW INDEX FROM <table>;

Understand Relationships

SELECT
  TABLE_NAME, COLUMN_NAME, REFERENCED_TABLE_NAME, REFERENCED_COLUMN_NAME
FROM INFORMATION_SCHEMA.KEY_COLUMN_USAGE
WHERE REFERENCED_TABLE_NAME IS NOT NULL
  AND TABLE_SCHEMA = DATABASE();

Count and Sample

SELECT COUNT(*) FROM <table> WHERE <condition>;
SELECT * FROM <table> WHERE <condition> LIMIT 10;

Soft Delete Patterns

Tables may use different soft delete approaches:

Pattern	Meaning
deleted column (0/1)	Record is soft-deleted
deactivated column	Record is deactivated
disabled column	Record is disabled
active column	Record is active (inverse)
deleted_at timestamp	Null = active, set = deleted

Always check the appropriate status column when querying.

Data Types

Pattern	Type	Notes
Primary keys	int or bigint	Auto increment
Boolean flags	tinyint(1)	0 = false, 1 = true
Percentages	decimal(5,3)	0.000 to 100.000
Timestamps	datetime	UTC
JSON data	json	MySQL 5.7+ native JSON

Security Rules

1. Never expose passwords, tokens, or API keys in query results
2. PII fields (email, name, phone) are sensitive — limit exposure
3. Always use LIMIT on exploratory queries
4. Filter inactive/deleted records unless debugging
5. Never modify data — use read-only queries only

Debugging Queries

Check if record exists with relationships

SELECT t1.id, t1.name,
       t2.id as related_id, t2.status
FROM main_table t1
LEFT JOIN related_table t2 ON t2.main_id = t1.id
WHERE t1.id = ?;

Find duplicates

SELECT <column>, COUNT(*) as count
FROM <table>
GROUP BY <column>
HAVING count > 1;

Check recent changes

SELECT * FROM <table>
WHERE updated_at >= NOW() - INTERVAL 1 HOUR
ORDER BY updated_at DESC
LIMIT 20;