Why is reversibility mandatory for migrations in this skill?

Reversibility ensures that you can safely roll back changes if a deployment fails, preventing database corruption and minimizing production downtime.

How does this skill handle zero-downtime deployments?

It implements multi-step patterns such as adding columns before removing old ones, using server defaults for NOT NULL constraints, and utilizing concurrent index creation to avoid table locking.

Why should schema and data migrations be kept separate?

Schema changes are structural and fast, while data migrations are often slow and operational; separating them allows for better rollback safety and prevents long-running transactions from blocking schema updates.

Which database frameworks are supported by these standards?

The skill provides specific patterns for Alembic (Python), Rails ActiveRecord (Ruby), and Sequelize (JavaScript), but the core principles apply to any migration tool.

Backend Migration Standards

Name: Backend Migration Standards
Author: Activer007

byActiver007

Database Management

Enforces safe, reversible, and zero-downtime database schema evolutions following industry best practices.

About

This skill provides Claude Code with a comprehensive framework for managing backend database migrations across various environments and frameworks like Alembic, Rails, and Sequelize. It enforces critical safety standards such as mandatory reversibility, separation of schema and data changes, idempotent data scripts, and non-blocking index creation to ensure database integrity and minimize deployment risks. By applying these standards, developers can confidently manage database versioning while ensuring backwards compatibility for zero-downtime production deployments.

Key Features

Safe concurrent index creation patterns for large production tables
Clear separation of structural schema changes from operational data scripts
0 GitHub stars
Mandatory reversibility with validated up/down migration methods
Zero-downtime deployment strategies for non-breaking schema changes
Framework-specific patterns for Python, Ruby, and Node.js ecosystems

Use Cases

Executing complex schema changes in high-traffic production environments without downtime
Performing safe, idempotent data transformations and backfills on large datasets
Standardizing database versioning and naming conventions across distributed engineering teams

About

Key Features

Safe concurrent index creation patterns for large production tables
Clear separation of structural schema changes from operational data scripts
0 GitHub stars
Mandatory reversibility with validated up/down migration methods
Zero-downtime deployment strategies for non-breaking schema changes
Framework-specific patterns for Python, Ruby, and Node.js ecosystems

Use Cases

Executing complex schema changes in high-traffic production environments without downtime
Performing safe, idempotent data transformations and backfills on large datasets
Standardizing database versioning and naming conventions across distributed engineering teams