How does it handle invalid data during testing?

The skill includes a verification step that tests constraints with both valid and invalid data to ensure the rules are functioning correctly before deployment.

What databases does the Data Validation Engine support?

The skill is designed for multi-database environments, supporting common SQL and NoSQL systems by generating compatible constraints and validation logic.

Does it provide application-level validation?

Yes, it can implement validation logic at both the database schema level and within the application code to provide multi-layered data protection.

Can I use this skill on existing database tables?

Yes, the skill can analyze existing schemas and apply new validation rules or constraints to ensure data consistency in legacy systems.

Data Validation Engine

Name: Data Validation Engine
Author: BbgnsurfTech

byBbgnsurfTech

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Database Management

Ensures database integrity by automatically enforcing data types, ranges, formats, and complex business rules across application schemas.

About

The Data Validation Engine skill empowers Claude to maintain high-quality data by automatically implementing and enforcing validation constraints within database schemas and application logic. It streamlines the process of defining referential integrity, regex-based formatting, and range checks, making it an essential tool for developers building production-ready systems. Whether you are setting up a new database or securing an existing environment, this skill helps prevent invalid data entry and ensures consistent data quality throughout the development lifecycle.

Key Features

3 GitHub stars
Support for multi-database production environments
Regex-based format validation for fields like email and phone numbers
Automated data type and range enforcement
Automatic generation of validation constraints and application logic
Referential integrity and business rule implementation

Use Cases

Implementing complex format validation for user input fields
Enforcing strict data types on legacy database columns
Maintaining referential integrity across relational database schemas

About

Key Features

3 GitHub stars
Support for multi-database production environments
Regex-based format validation for fields like email and phone numbers
Automated data type and range enforcement
Automatic generation of validation constraints and application logic
Referential integrity and business rule implementation

Use Cases

Implementing complex format validation for user input fields
Enforcing strict data types on legacy database columns
Maintaining referential integrity across relational database schemas