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Data Faker
Generate realistic JSON or CSV test data from plain-English schema descriptions with up to 1,000 rows.
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Works with the AI tools you already use
See it in action
You say
Generate 100 e-commerce orders with product, price, quantity, status, and date in CSV format.
Your agent does
Schema: e-commerce orders Rows: 100 Format: CSV
[Sample] order_id,product,price,quantity,status,date ORD-A1B2C3D4,ProMax Widget,49.99,2,completed,2024-08-15 ORD-E5F6G7H8,CoreSuite Pro,129.00,1,pending,2024-10-02
Saved: ./fake_data.csv
What you get
About this skill
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.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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