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libs-synthetic-data

Official

Generate synthetic data for testing.

Software Engineering#testing#data generation#synthetic data#DSL parsing#LLM content#data rendering
Authorforwardimpact
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill provides a robust framework for generating synthetic data, essential for testing software, creating example content, and building realistic data pipelines without relying on sensitive production information.

Core Features & Use Cases

  • DSL Parsing: Parse custom Domain Specific Languages (DSLs) to define data structures and relationships.
  • Deterministic Entity Generation: Create predictable and repeatable datasets for organizations, teams, and individuals.
  • LLM-Powered Content: Generate natural language prose and framework content using Large Language Models.
  • Multi-Format Rendering: Output generated data into various formats like HTML, Markdown, and YAML, with built-in validation.
  • Use Case: Generate a realistic organizational structure with 50 employees, their roles, and project assignments for testing a new HR platform.

Quick Start

Use the libs-synthetic-data skill to parse the 'universe.dsl' file and generate entities.

Dependency Matrix

Required Modules

None required

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: libs-synthetic-data
Download link: https://github.com/forwardimpact/monorepo/archive/main.zip#libs-synthetic-data

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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