dummy-dataset

Generate customizable dummy datasets in CSV, JSON, SQL, and Python scripts.

Updated Mar 15, 2026
One-click install
npx skills add https://github.com/bowiemax/pm-skills --skill dummy-dataset-bowiemax
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dummy-dataset
Source: https://github.com/bowiemax/pm-skills/tree/main/pm-execution/skills/dummy-dataset
Command: npx skills add https://github.com/bowiemax/pm-skills --skill dummy-dataset-bowiemax

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the creation of realistic dummy datasets, saving developers and testers significant time and effort in generating sample data for various applications.

Core Features & Use Cases

  • Customizable Data Generation: Define specific columns, data types, and constraints for your datasets.
  • Multiple Output Formats: Generate data as CSV, JSON, SQL INSERT statements, or a Python script.
  • Use Case: You need to populate a new user profile database with 1000 realistic entries for testing. Use this Skill to generate names, emails, and creation dates in a CSV format.

Quick Start

Generate 500 rows of customer feedback data in CSV format.

Frequently Asked Questions about dummy-dataset

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate realistic test data for a database in CSV or JSON format?

To generate realistic test data in CSV or JSON format, you can define specific columns, data types, and constraints to automatically create datasets for your development environment.

Can I create mock data with SQL INSERT statements directly?

Yes, you can create mock data with SQL INSERT statements directly by specifying your row counts and column definitions to populate test databases without manual data entry.

What is the best way to generate sample data with specific column constraints for testing?

The best way to generate sample data with specific column constraints for testing is to automate creation using customizable columns, data types, and required row counts.

Does this approach support generating Python scripts for mock data creation?

Yes, this approach supports generating Python scripts for mock data creation, allowing you to output your customized dummy datasets directly as executable code.

How many rows of dummy dataset can I specify for my test environment?

You can specify your required row counts for the dummy dataset, ensuring the generated mock data matches the exact scale needed for your test environment.