Does it support different regions for names and addresses?

Absolutely, you can specify locale considerations to generate regionally accurate names, phone numbers, and physical addresses.

Is the generated data reproducible for regression testing?

Yes, by using seed values during the generation process, you can ensure the same dataset is produced across multiple runs for consistency.

What formats does the skill output?

The skill typically presents data in structured formats like JSON or data files ready for database insertion or API request payloads.

Can I generate data based on my specific database schema?

Yes, the skill supports custom schema definitions to ensure the generated data matches your specific data model and constraints.

Test Data Generator

Name: Test Data Generator
Author: jeremylongshore

byjeremylongshore

•

883

セキュリティとテスト

Generates realistic, schema-compliant synthetic data to populate testing environments and simulate complex user behavior.

概要

This skill automates the creation of diverse and realistic datasets, including user profiles, product catalogs, and transaction records, for software development and testing. By leveraging customizable schemas and locales, it allows developers to quickly fill databases, perform load testing, and create consistent fixtures for automated test suites without manual data entry or the privacy risks associated with using real production data. It is an essential tool for developers needing to simulate realistic edge cases and volume during the QA process.

主な機能

Support for custom schema definitions to match specific data models
Structured data output in JSON and database-ready formats
883 GitHub stars
Automated generation of realistic user, product, and order datasets
Locale-specific data generation for accurate regional formatting
Seed-based generation for consistent and reproducible test results

ユースケース

Simulating high-volume transaction data for performance and load testing scenarios
Creating realistic sample data for product demonstrations and sales training environments
Populating staging databases with hundreds of unique user profiles for authentication testing

概要

主な機能

Support for custom schema definitions to match specific data models
Structured data output in JSON and database-ready formats
883 GitHub stars
Automated generation of realistic user, product, and order datasets
Locale-specific data generation for accurate regional formatting
Seed-based generation for consistent and reproducible test results

ユースケース

Simulating high-volume transaction data for performance and load testing scenarios
Creating realistic sample data for product demonstrations and sales training environments
Populating staging databases with hundreds of unique user profiles for authentication testing