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$12.00developer-toolsUniversal

data-faker

Generate realistic JSON or CSV test data from plain-English schema descriptions with up to 1,000 rows.

skill install https://www.promptspace.in/skills/data-faker

What it does

Data Faker is a high-utility developer tool that transforms plain-English schema descriptions into high-quality, realistic datasets for testing and development. It moves beyond generic lorem ipsum by understanding the semantic meaning behind your field names to generate contextually accurate data points like UUIDs, US-formatted addresses, realistic prices, and ISO dates.

Why use this skill

Instead of manually writing scripts or using generic online generators that require tedious form-filling, you can simply describe what you need in one sentence. This skill is superior to basic LLM prompting because it handles large-scale generation (up to 1,000 rows) without data truncation, ensures cross-record uniqueness to prevent primary key collisions, and enforces strict formatting for CSV and JSON output files—saving you from parsing errors in your test suites.

Supported tools and formats

  • Smart Type Detection: Automatically maps over 30 field patterns (e.g., 'revenue', 'sku', 'ip_address', 'status').
  • Flexible Export: Generates valid JSON arrays or RFC 4180 compliant CSV files.
  • Custom Enums: Detects bracketed or parenthetical status lists directly from your prompt.
  • Contextual Logic: Matches phone formats to countries and ensures realistic numeric distributions.

Use cases

  • Generate realistic datasets for database seeding and migrations
  • Create bulk CSV files for testing import/upload functionality
  • Populate UI prototypes with varied, non-repeating mock data
  • Simulate transaction logs for data visualization and analytics testing

Example

Prompt

Generate 50 users with name, email, age, and status (active, trial, expired) --format csv

Sample output preview is available after purchase.

Frequently asked questions

Data Faker uses semantic understanding to recognize specific requirements like UUIDs, ISO dates, and country-specific address formats, ensuring you get functional data that won't break your database constraints or validation logic.
data-faker — AI Agent Skill | PromptSpace