Mock Data Creator

The Problem

Every test suite, demo, and prototype needs realistic data — but creating it manually is tedious and error-prone. Copy-pasting “John Doe” and “test@test.com” everywhere makes tests unreliable and demos look unprofessional. You need data that respects constraints (unique IDs, valid emails, realistic dates, proper relationships between entities) and comes in the exact format your code expects.

The Prompt

Generate realistic mock data for my application. The data should look like real production data — no "test123" or "foo bar" placeholders.

DATA MODEL:
[paste your schema, TypeScript interface, database table definition, or describe the structure]

REQUIREMENTS:
- Format: [JSON / SQL INSERT / CSV / TypeScript const / Python dict]
- Records: [number, e.g., 20]
- Language/Locale: [e.g., English, German, mixed]
- Relationships: [describe foreign key or relational constraints]
- Edge cases to include: [e.g., one record with missing optional fields, one with very long name, one with special characters]

CONSTRAINTS:
- [e.g., email must be unique, dates must be in 2024-2026, status must be one of: active/inactive/pending]
- [e.g., each user should have 1-5 orders, prices between 9.99 and 999.99]

Generate the data with inline comments marking any edge-case records.

Example Output

[
  {
    "id": "usr_a1b2c3d4",
    "name": "Maria Gonzalez",
    "email": "m.gonzalez@outlook.com",
    "plan": "premium",
    "createdAt": "2025-03-14T09:22:00Z",
    "orders": 12
  },
  {
    "id": "usr_e5f6g7h8",
    "name": "Takeshi Yamamoto",
    "email": "takeshi.y@company.co.jp",
    "plan": "free",
    "createdAt": "2026-01-02T14:05:00Z",
    "orders": 0
  },
  // Edge case: very long name
  {
    "id": "usr_x9y0z1a2",
    "name": "Jean-Pierre de la Fontaine-Beauregard III",
    "email": "jpf3@gmail.com",
    "plan": "premium",
    "createdAt": "2024-12-31T23:59:59Z",
    "orders": 247
  }
]

When to Use

Use this when setting up test fixtures, building demo environments, seeding development databases, or creating Storybook data for UI components. It’s faster than Faker.js for one-off datasets and produces more contextually appropriate data because you can describe the domain.

Pro Tips

• Include your validation rules — paste your Zod schema or database constraints so the AI generates data that always passes validation.
• Request a factory function — follow up with “Now generate a TypeScript factory function that creates random records following this pattern” for reusable test utilities.
• Ask for edge-case diversity — specify “include one record for each edge case: empty optional field, maximum length string, emoji in name, date at year boundary, zero-value numeric field.”