synthdata-extend

Extend synthetic datasets with rows or columns while preserving FK integrity and ID sequencing.

Updated Apr 5, 2026
One-click install
npx skills add https://github.com/rappdw/synthdata --skill synthdata-extend
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: synthdata-extend
Source: https://github.com/rappdw/synthdata/tree/main/skills/synthdata-extend
Command: npx skills add https://github.com/rappdw/synthdata --skill synthdata-extend

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl, faker, numpy, pyyaml, mcp, and includes scripts (resource) components.

What problem does it solve?

Extend an existing synthetic dataset by adding more rows or new columns while preserving FK integrity, ID continuity, and column distributions. It enables growing datasets without regenerating from scratch, while keeping the statistical properties and relationships intact across related tables.

Core Features & Use Cases

  • Extend datasets by appending rows that follow the original distributions and preserve column stats.
  • Add new columns while maintaining existing IDs and FK links.
  • Use cases include expanding e-commerce orders, customer profiles, or product catalogs without re-generating the entire dataset.

Quick Start

Use synthdata-extend to add 500 rows to the orders table while preserving ID sequencing and FK relationships.

Frequently Asked Questions about synthdata-extend

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

FAQPage Schema
How do I add rows to an existing synthetic dataset while preserving foreign key integrity?

To extend a synthetic dataset while preserving FK integrity, append new rows that follow original column distributions and maintain ID sequencing, ensuring relationships across related tables remain intact without regenerating from scratch.

Can I add new columns to a CSV file without breaking existing ID continuity and FK links?

Yes, you can add new columns to CSV files while maintaining existing IDs and FK links. The skill uses companion schemas and basic type inference to ensure seamless integration of new attributes into your current dataset.

What is the best way to grow synthetic data across xlsx, csv, and json formats?

The best way to grow synthetic data across xlsx, csv, and json formats is to use deterministic augmentation that preserves column distributions and utilizes companion schemas to guide data generation for seamless integration.

Does extending a dataset with pandas and faker support deterministic data augmentation?

Yes, extending a dataset with pandas and faker supports deterministic augmentation. The skill preserves column statistics and uses companion schemas to guide generation, ensuring statistically consistent data expansion.

When should I not use synthetic data extension instead of full dataset regeneration?

You should not use synthetic data extension when you need to fundamentally alter original column distributions or schema structures. It is designed for appending rows or columns while preserving existing statistical properties, not for complete schema overhauls.