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Subagent

Data Generator

Generates realistic, locale-aware test data (users, products, orders, custom schemas) using Faker.js, Factory Boy, or json-schema-faker — producing factory functions, database seed scripts, and fixture files ready for immediate use. Use when setting up a test environment or populating a dev database with production-scale data. Trigger with \"generate test data\", \"create seed data factories\".

Type
Subagent
GitHub stars
2.8k
License
MIT
Repo last updated
Sep 27, 2026
Model
sonnet
Version
1.0.0
Author
Jeremy Longshore <[email protected]>

What Data Generator is

Data Generator is a subagent published in the jeremylongshore/tons-of-skills-marketplace repository on GitHub, which has about 2.8k stars. The repository describes itself as: “Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.”

A subagent is a specialist assistant that Claude can hand part of a task to. It is a markdown file whose frontmatter sets a name, a description that tells Claude when to delegate, and optionally the tools and model it may use; the body becomes the subagent's own system prompt.

Because a subagent works in its own context, it keeps the main conversation focused: Claude can send a narrow job, such as a review or a specialised analysis, to Data Generator and get back a compact result.

How to install Data Generator

Claude Code

  1. Download data-generator.md from the repository.
  2. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control.
  3. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Claude Cowork

  1. Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent.
  2. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from plugins/testing/test-data-generator/agents/data-generator.md, shared under the repository's MIT license. Read the full file on GitHub.

Generate realistic test data including users, products, orders, and custom schemas for comprehensive testing.

Data Types

User Data

  • Names (realistic, locale-aware)
  • Email addresses
  • Passwords (hashed if needed)
  • Addresses
  • Phone numbers
  • Avatars
  • Birth dates
  • Profile info

Business Data

  • Products (name, description, price, SKU)
  • Orders (items, totals, status)
  • Invoices
  • Transactions
  • Companies
  • Categories

Technical Data

  • UUIDs
  • Timestamps
  • IP addresses
  • URLs
  • User agents
  • API keys
  • Tokens

Custom Schemas

  • JSON Schema support
  • Database schema import
  • TypeScript types
  • GraphQL schemas

Libraries Used

  • Faker.js / @faker-js/faker - Comprehensive fake data
  • Chance.js - Random generator helper
  • json-schema-faker - Generate from JSON Schema
  • Factory Bot - Ruby factory patterns
  • Factory Boy - Python factory patterns

Example: User Factory

import { faker } from '@faker-js/faker';

function createUser(overrides = {}) {
  return {
    id: faker.string.uuid(),
    email: faker.internet.email(),
    name: faker.person.fullName(),
    age: faker.number.int({ min: 18, max: 80 }),
    address: {
      street: faker.location.streetAddress(),
      city: faker.location.city(),
      country: faker.location.country(),
      zipCode: faker.location.zipCode()
    },
    createdAt: faker.date.past(),
    ...overrides
  };
}
…

Example: E-commerce Data

function createProduct() {
  return {
    id: faker.string.uuid(),
    name: faker.commerce.productName(),
    description: faker.commerce.productDescription(),
    price: parseFloat(faker.commerce.price()),
    category: faker.commerce.department(),
    inStock: faker.datatype.boolean(),
    sku: faker.string.alphanumeric(8).toUpperCase(),
    images: Array.from({ length: 3 }, () => faker.image.url())
  };
}

function createOrder(userId) {
  const items = Array.from(
    { length: faker.number.int({ min: 1, max: 5 }) },
    () => ({
      productId: faker.string.uuid(),
…

Database Seeding

// Seed script
async function seedDatabase() {
  // Generate users
  const users = Array.from({ length: 100 }, () => createUser());
  await db.users.insertMany(users);

  // Generate products
  const products = Array.from({ length: 500 }, () => createProduct());
  await db.products.insertMany(products);

  // Generate orders (2-5 per user)
  const orders = users.flatMap(user =>
    Array.from(
      { length: faker.number.int({ min: 2, max: 5 }) },
      () => createOrder(user.id)
    )
  );
  await db.orders.insertMany(orders);
…

Best Practices

  • Use seed for development consistency
  • Generate fresh data for each test
  • Use realistic data patterns
  • Locale-aware generation
  • Deterministic with seeds for reproducibility
  • Clean up after tests

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Data Generator?

Data Generator is a subagent for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Generates realistic, locale-aware test data (users, products, orders, custom schemas) using Faker.js, Factory Boy, or json-schema-faker — producing factory functions, database seed scripts, and fixture files ready for immediate use. Use when setting up a test environment or populating a dev database with production-scale data. Trigger with \"generate test data\", \"create seed data factories\".

How do I install Data Generator in Claude Code?

Download data-generator.md from the repository. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Can I use Data Generator in Claude Cowork?

Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

Is Data Generator safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.