Agent skill · software engineering · aiskillstore
seed-data-generator
Generate realistic test data for database development, testing, and demos.
Why this skill is useful
Adds executable scripts for generating realistic test data across multiple database systems with referential integrity and customization options.
What it needs
Requires django, faker, prisma, rails, sequelize installed locally. About 8k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Seed Data Generator Skill Generate realistic test data for database development, testing, and demos. Instructions You are a test data generation expert. When invoked: 1. Analyze Schema: Identify tables and relationships Understand column types and constraints Detect foreign key dependencies Recognize data patterns (email, phone, dates, etc.) 2. Generate Realistic Data: Use faker libraries for realistic data Maintain referential integrity Follow business logic constraints Create diverse but realistic scenarios 3. Seed Database: Insert data in correct order (respect foreign keys) Handle different database systems Provide both SQL and ORM-based seeders Support incremental seeding 4. Customize Generation: Allow quantity specification Support different data scenarios (edge cases, happy path) Enable data relationships customization Provide reproducible seeds (with random seed values) Supported Tools JavaScript/TypeScript: Faker.js, Chance.js, Casual Python: Faker, Factory Boy, Mimesis Ruby: Faker, FactoryBot Raw SQL: Generate INSERT statements ORMs: Prisma, TypeORM, Sequelize, Django, Rails Usage Examples SQL Seed Data PostgreSQL - Basic Insert Generated Seed with Functions JavaScript/TypeScript Seeders Faker.js + Prisma TypeORM Seeder Python Seeders Django Fixtures Factory Boy (Python) `python factories.py import factory from factory.django import DjangoModelFactory from faker import Faker from app.models import User, Product, Category, Order, OrderItem fake = Faker() class CategoryFactory(DjangoModelFactory): class Meta: model = Category name = factory.Faker('word') slug = factory.LazyAttribute(lambda obj: obj.name.lower()) class UserFactory(DjangoModelFactory): class Meta: model = User username = factory.Faker('username') email = factory.Faker('email') passwordhash = factory.Faker('sha256') active = factory.Faker('boolean', chanceofgettingtrue=90) createdat = factory.Faker('datetimethisyear') class ProductFactory(DjangoModelFactory): class Meta: model = Product name = …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/seed-data-generator