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data-migration-expert

Validate data migrations and backfills against production data alignment.

1|Updated Apr 4, 2026
Search Tags:#code review#schema validation#data migration#backfill#production data#rollback safety#enum conversion
One-click install
npx skills add https://github.com/ybbms777/compound-engineering --skill data-migration-expert-ybbms777
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-migration-expert
Source: https://github.com/ybbms777/compound-engineering/tree/main/skills/agent-data-migration-expert
Command: npx skills add https://github.com/ybbms777/compound-engineering --skill data-migration-expert-ybbms777

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data migrations, backfills, and schema changes frequently cause production data corruption, outages, and broken functionality when validated against test fixtures or incorrect assumptions instead of real production data. This Skill eliminates that risk by enforcing rigorous validation of all data transformation changes against live production reality.

Core Features & Use Cases

  • Production Data Alignment: Verifies that ID mappings, column renames, enum conversions, and schema changes match actual production data values, not test fixtures.
  • High-Risk Bug Detection: Catches common dangerous migration errors including swapped IDs, incomplete dual-writes, orphaned associations, and missing error handling.
  • Use Case Example: When a team is rolling out a migration to rename a user status enum column, this Skill reviews the PR to confirm the value mappings match live production data, validates the rollback plan, and ensures no user records are corrupted during deployment.

Quick Start

Use the data-migration-expert skill to review the pending user status enum migration PR to confirm the value mappings match production data and validate the rollback plan.

Frequently Asked Questions about data-migration-expert

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

FAQPage Schema
How do I validate data migrations against production data?▼

Validate data migrations against production data by verifying ID mappings, column renames, and enum conversions match live values. This prevents data corruption caused by testing against incorrect assumptions or synthetic test fixtures.

What is the best way to ensure rollback safety during schema changes?▼

Ensure rollback safety during schema changes by enforcing verification of production data alignment and dual-write completeness. This guarantees that any deployment can be safely reversed without corrupting user records.

How do I detect incomplete dual-writes during a data backfill?▼

Detect incomplete dual-writes during a data backfill by reviewing pull requests for missing error handling and orphaned associations. This catches dangerous migration errors before they cause production outages.

When do I need to verify enum conversion mappings in production?▼

Verify enum conversion mappings in production whenever you rename a user status column or alter schema values. This ensures the value mappings reflect actual production data rather than outdated test fixtures.

Can I use this approach to review pull requests involving ID mappings?▼

Yes, you can review pull requests involving ID mappings to confirm they match actual production data. This prevents common dangerous migration errors like swapped IDs and missing error handling.

Why does data backfill fail when validated against test fixtures?▼

Data backfill fails when validated against test fixtures because fixtures rarely reflect live production reality. Validating transformations against actual production data prevents broken functionality and data corruption.

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