How do I define the structure of the dataset?

You can provide a list of specific columns, data types, and any relevant constraints to the skill, which will then generate the appropriate schema and values.

Can I generate large datasets for performance testing?

Absolutely. You can configure the number of rows to generate high-volume datasets suitable for load testing and database performance benchmarking.

What formats can this skill export?

The Dummy Dataset Generator supports CSV for spreadsheets, JSON for APIs, SQL INSERT statements for databases, and executable Python scripts for custom generation logic.

Is the data generated truly realistic?

The skill uses patterns for common entities like names, valid email formats, and industry-specific categories to ensure the data looks and behaves like real-world information.

Can I apply custom business rules to the data?

Yes, you can specify constraints such as value distributions (e.g., 40% 5-star ratings), date ranges, and conditional logic between different columns.

Dummy Dataset Generator

Name: Dummy Dataset Generator
Author: bowiemax

bybowiemax

0•

데이터베이스 관리

Generates realistic, structured dummy datasets for application testing and development across multiple formats.

The Dummy Dataset Generator skill enables developers to quickly create high-quality, realistic mock data for populating databases, testing APIs, or building product demos. By allowing users to define custom columns, business constraints, and data patterns, it produces executable Python scripts or direct data files in CSV, JSON, and SQL formats. This ensures that test environments reflect real-world scenarios and respect complex business logic without the need to use sensitive production data.

주요 기능

01Allows custom business logic and data distribution constraints

02Implements realistic data patterns for names, emails, timestamps, and categories

03Generates large-scale datasets with configurable row counts and field types

040 GitHub stars

05Provides ready-to-execute scripts for repeatable data generation

06Supports multiple output formats including CSV, JSON, SQL, and Python scripts

사용 사례

01Populating local or staging databases with realistic sample records for development

02Generating edge-case datasets to validate system constraints and business logic

03Creating mock API responses and JSON payloads for frontend UI/UX testing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add bowiemax/pm-skills dummy-dataset

For use in Claude.ai and ChatGPT