What problem does it solve? Backend engineers often write SQL that works in development but fails in production: slow queries from missing indexes, deadlocks from inconsistent lock ordering, stale reads from replicas, and connection pool exhaustion. This Skill encodes production-grade MySQL and MariaDB patterns so an AI agent reviews and writes database code with the correct engine-specific syntax and operational safeguards. ## Core Features & Use Cases - Schema and Index Design: Provides table defaults (BIGINT UNSIGNED keys, DECIMAL for money, utf8mb4), composite index ordering rules, and EXPLAIN review signals. - Query Patterns: Covers upserts with cross-engine syntax, keyset pagination, indexed JSON generated columns, and full-text search. - Transactions and Operations: Documents deadlock prevention, SKIP LOCKED queue claiming, connection pool sizing for SQLAlchemy and mysql2, replication lag handling, security hardening, and my.cnf starting points. - Use Case: Before running a migration on a large production orders table, ask the agent to review the SQL; it will check index coverage, lock risk, MySQL versus MariaDB syntax differences, and produce a verification plan with EXPLAIN and rollback criteria. ## Quick Start Ask the agent to review your MySQL schema migration or slow query using the dev-mysql skill and return the risky issues with corrected SQL.