How does Claude generate the test data?

It uses the test-data-generator plugin to produce realistic records based on your natural language prompts, predefined patterns, or provided schemas.

Can it handle custom business-specific data models?

Absolutely. You can provide a specific schema or data model, and the skill will generate realistic values that adhere strictly to your defined structure.

What formats can the test data be delivered in?

The skill typically provides data in structured formats like JSON, making it easy to use as API mock responses or for direct database insertion.

Can I generate data for specific geographic regions?

Yes, the skill supports locale considerations, allowing you to generate region-specific names, addresses, and phone numbers to match your target market.

Is the generated data reproducible for regression testing?

Yes, you can use seed values to ensure the generated data remains consistent across multiple runs, which is essential for stable automated testing.

Test Data Generator

Name: Test Data Generator
Author: intent-solutions-io

byintent-solutions-io

安全与测试

Generates realistic, schema-aligned test data for software applications, including user profiles, e-commerce transactions, and custom datasets.

关于

This skill automates the creation of diverse and comprehensive datasets for software development and QA testing. By leveraging the test-data-generator plugin, it allows developers to quickly populate databases, simulate user behavior, and create realistic fixtures for automated tests. It supports custom schema definitions, locale-specific formatting for regional accuracy, and reproducible seed values, ensuring that testing environments are consistent and representative of real-world scenarios.

主要功能

Seed value support for reproducible and consistent datasets
E-commerce data simulation including products, categories, and orders
Locale-sensitive formatting for regional data accuracy
Realistic user profile generation with names, emails, and addresses
Custom schema-based generation for specific data models
0 GitHub stars

使用场景

Populating testing databases with thousands of realistic records for load and performance testing
Creating mock user accounts and transaction history for product demonstrations and training
Generating schema-compliant JSON fixtures for automated unit and integration tests

关于

主要功能

Seed value support for reproducible and consistent datasets
E-commerce data simulation including products, categories, and orders
Locale-sensitive formatting for regional data accuracy
Realistic user profile generation with names, emails, and addresses
Custom schema-based generation for specific data models
0 GitHub stars

使用场景

Populating testing databases with thousands of realistic records for load and performance testing
Creating mock user accounts and transaction history for product demonstrations and training
Generating schema-compliant JSON fixtures for automated unit and integration tests