validating-schema-evolution

Classify schema changes as breaking, non-breaking, or ambiguous.

2|Updated May 23, 2026

Search Tags:#validation #migration #breaking-changes #postgres #schema-evolution #api-compatibility

Ready to run

npx skills add https://github.com/rocklambros/rcs --skill validating-schema-evolution

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: validating-schema-evolution
Source: https://github.com/rocklambros/rcs/tree/main/skills/workflow/validating-schema-evolution
Command: npx skills add https://github.com/rocklambros/rcs --skill validating-schema-evolution

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you review schema changes before they reach production, catching breaking edits like drops, type narrowing, and nullability tightening before they disrupt downstream systems.

Core Features & Use Cases

Compares old and new schemas and classifies each change as breaking, non-breaking, or ambiguous.
Detects likely renames, identifies affected consumers, and recommends safe migration scaffolds for databases, datasets, and APIs.
Use it when a table, dataset, or contract is being versioned, when a downstream pipeline starts failing after refresh, or when a release needs a compatibility check.

Quick Start

Ask the skill to compare the old and new schemas, classify every change, and produce a safe migration plan for the affected consumers.

Frequently Asked Questions about validating-schema-evolution

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I check database schema changes for breaking edits before release?▼

To check database schema changes for breaking edits, compare old and new schema versions to classify changes like column drops and type narrowing before they disrupt downstream systems.

What is schema evolution validation and when do I need it?▼

Schema evolution validation identifies breaking modifications during column additions, drops, renames, and constraint updates. You need it when versioning tables, datasets, or API contracts to prevent downstream pipeline failures.

How do I detect column renames during a Postgres schema migration?▼

To detect column renames during a Postgres schema migration, compare old and new schemas to identify likely renames, classify changes as breaking or non-breaking, and generate safe migration scaffolds.

Can I validate API compatibility for nullability and type changes?▼

Yes, you can validate API compatibility for nullability tightening and type changes by comparing old and new API contracts to classify changes and identify affected consumers.

What is the best way to generate safe migration scaffolds for schema evolution?▼

The best way to generate safe migration scaffolds for schema evolution is to compare schema versions and produce change classifications that preserve data unless breaking changes are explicitly allowed.

Why does my downstream pipeline fail after a dataset schema refresh?▼

Your downstream pipeline fails after a dataset schema refresh because breaking changes like column drops or type narrowing were introduced, which schema validation catches before release.