Database

Skill slogsdon/skills-engineering-reference/skills/database

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Relational database schema design, normalization, indexing, and query optimization. Use when the user says "design the schema for X", "how should this table be structured", "this query is slow", "do I need an index here", "denormalize this", or when starting a new feature that needs persistence. Covers Postgres, MySQL, SQLite. Do NOT use for ORM-specific syntax — covers conceptual design first, ORM second.

SKILL.md

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Provide database design expertise for schema architecture, migration management, query optimization, and scaling strategies for MySQL, PostgreSQL, and relational databases.

Core Database Domains

Schema Design: Create normalized database schemas with:

Proper relationships (one-to-one, one-to-many, many-to-many)
Data integrity constraints (foreign keys, unique constraints, check constraints)
Appropriate data types and indexes
Denormalization strategies when performance requires it

Migration Management: Design safe, reversible database migrations with:

Forward (up) and backward (down) migration paths
Data transformation strategies for complex changes
Rollback procedures for failed migrations
Version control and deployment safety

Performance Optimization: Optimize database performance through:

Query analysis with EXPLAIN plans
Strategic indexing (single-column, composite, covering, partial)
N+1 query problem resolution
Connection pooling and query caching
Slow query identification and remediation

Scalability Planning: Design for growth with:

Read replicas for horizontal scaling
Vertical and horizontal partitioning strategies
Sharding for massive datasets
Connection pooling and load balancing
Cache-aside patterns with Redis/Memcached

Data Security & Compliance: Implement security measures:

Column-level encryption for sensitive data
Row-level security policies
Audit logging for compliance (GDPR, HIPAA)
Access control and privilege management
Secure backup and recovery strategies

Archival & Retention: Manage data lifecycle with:

Time-based archival strategies
Partitioning by date for efficient archival
Automated archival procedures
Compliance-driven retention policies

Example Schema Pattern

CREATE TABLE users (
    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
    email VARCHAR(255) NOT NULL UNIQUE,
    password_hash VARCHAR(255) NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
    deleted_at TIMESTAMP NULL, -- Soft deletes

    INDEX idx_email (email),
    INDEX idx_created_at (created_at),
    INDEX idx_deleted_at (deleted_at)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

Provide specific SQL examples, migration code, index recommendations with EXPLAIN plan analysis, scaling architecture diagrams, and performance benchmarks where applicable.

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What its author says it does

SKILL.md

Core Database Domains

Example Schema Pattern

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