Can I specify the amount of data to be generated?

Yes, you can request specific volumes in your prompt, such as 'generate 50 users' or 'populate the posts table with 200 entries.'

Are the generated scripts idempotent?

The skill follows best practices to create scripts that can be run multiple times without causing duplicate entry errors, typically using 'upsert' logic or 'truncate' commands.

What formats are supported for the seed scripts?

The skill can generate scripts in various formats including raw SQL, JavaScript (using TypeORM or Knex), and other common database migration formats.

How does the skill handle relationships between tables?

It analyzes foreign key constraints in your schema and generates data that links records correctly across tables to ensure referential integrity is maintained.

Does it work with existing database schemas?

Yes, the skill uses file analysis tools to read your current schema definitions before generating data that matches your specific table structures.

Database Data Seeder

Name: Database Data Seeder
Author: intent-solutions-io

byintent-solutions-io

データベース管理

Generates realistic test data and database seed scripts to populate development and testing environments while maintaining relational integrity.

概要

The Database Data Seeder skill automates the creation of high-quality sample data for development, testing, and demonstration purposes. By analyzing your database schema and leveraging Faker libraries, it produces consistent, realistic records across multiple tables while strictly respecting foreign key constraints and data types. This tool is ideal for developers who need to quickly spin up pre-populated environments or create idempotent seed scripts without manually crafting complex SQL insert statements or JSON files.

主な機能

Support for multiple output formats including SQL and JavaScript/TypeORM
Schema-aware data generation using Faker libraries
0 GitHub stars
Relational integrity maintenance for foreign key constraints
Configurable data volumes for scalable environment testing
Automated analysis of existing table structures and data types

ユースケース

Populating a local development database with hundreds of realistic user profiles.
Generating consistent test data for automated CI/CD pipeline integration tests.
Creating complex, linked datasets for blog posts, comments, and authors for UI testing.

概要

主な機能

Support for multiple output formats including SQL and JavaScript/TypeORM
Schema-aware data generation using Faker libraries
0 GitHub stars
Relational integrity maintenance for foreign key constraints
Configurable data volumes for scalable environment testing
Automated analysis of existing table structures and data types

ユースケース

Populating a local development database with hundreds of realistic user profiles.
Generating consistent test data for automated CI/CD pipeline integration tests.
Creating complex, linked datasets for blog posts, comments, and authors for UI testing.