Test Data Strategy

概要

This skill empowers Claude to design and implement robust test data management plans, ensuring that testing environments have high-quality, realistic data while maintaining security and privacy compliance. It provides structured guidance on synthetic data generation using libraries like Bogus and AutoFixture, PII anonymization techniques, and data versioning across different development stages. Whether you are setting up unit tests with minimal data or pre-production environments requiring masked production clones, this skill provides the patterns and best practices needed for scalable and compliant data testing.

主な機能

• Compliance mapping for GDPR and HIPAA requirements
• Synthetic data generation patterns for Bogus and AutoFixture
• Environment-specific data refresh and volume strategies
• Data versioning and baseline management for regression
• 12 GitHub stars
• PII anonymization and masking techniques for data privacy

ユースケース

• Generating realistic synthetic data sets for unit and integration testing
• Anonymizing production data subsets for safe use in QA environments
• Designing data scaling and seeding strategies for performance testing