What is the Database Data Validation skill?

It is a specialized Claude Code skill that automates the definition and enforcement of data integrity rules, ensuring databases follow specific formats and business logic.

Can I use this for production databases?

Yes, the skill is designed for production-ready implementations and supports multi-database environments to maintain high data quality standards.

Is it compatible with other Claude Code tools?

Absolutely. It integrates seamlessly with schema design tools, migration utilities, and application frameworks within the Claude Code ecosystem.

Does it provide feedback if validation fails?

Yes, Claude will report any errors or conflicts during the implementation process and provide clear feedback to guide necessary corrections.

How does it handle email or format validation?

The skill utilizes the data-validation-engine plugin to apply regular expressions and specific formatting rules to columns, verifying they meet standard requirements.

Database Integrity & Validation

Name: Database Integrity & Validation
Author: BbgnsurfTech

byBbgnsurfTech

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Database Management

Ensures database reliability by automatically enforcing data types, ranges, formats, and complex business logic rules.

About

This skill empowers developers to maintain high-quality data standards by leveraging a specialized validation engine within Claude Code. It automates the implementation of constraints—such as email format verification, numeric range checks, and referential integrity—across multiple database environments. By integrating these checks directly into the development workflow, the skill prevents invalid data entry, simplifies schema management, and ensures that production databases remain consistent and reliable.

Key Features

3 GitHub stars
Multi-database environment support for production-ready scaling
Real-time verification of validation rules with test data
Automated enforcement of data types and numeric ranges
Seamless integration with existing database schemas and application logic
Regex-based validation for complex formats like emails and phone numbers

Use Cases

Implementing strict data type constraints on legacy database columns
Enforcing business rules and formatting during new schema migrations
Preventing application-level data corruption through automated input validation

About

Key Features

3 GitHub stars
Multi-database environment support for production-ready scaling
Real-time verification of validation rules with test data
Automated enforcement of data types and numeric ranges
Seamless integration with existing database schemas and application logic
Regex-based validation for complex formats like emails and phone numbers

Use Cases

Implementing strict data type constraints on legacy database columns
Enforcing business rules and formatting during new schema migrations
Preventing application-level data corruption through automated input validation