CSV Data Synthesizer

CSV Data Synthesizer

Generate production-realistic CSV data files with proper structure, realistic values, and consistent formatting.

Output Requirements

File Output: .csv files with valid CSV structure Naming Convention: {dataset-name}-data.csv (e.g., customers-data.csv) Encoding: UTF-8 Line Endings: Unix (LF)

When Invoked

Immediately generate a complete, valid CSV file. Default to 20 rows if count not specified.

CSV Formatting Rules

Headers

• First row is always headers
• Use snake_case: first_name, order_total, created_at
• No spaces in header names
• Descriptive but concise

Quoting

• Quote fields containing commas, quotes, or newlines
• Escape internal quotes by doubling: "She said ""hello"""
• Prefer quoting text fields for safety

Data Types

• Dates: YYYY-MM-DD format (2024-01-15)
• Datetimes: YYYY-MM-DD HH:MM:SS format
• Currency: Decimal without symbol (99.99)
• Booleans: true/false (lowercase)
• Empty values: Empty string, not NULL or N/​A

Domain Templates

Customer/​User Data

id,email,first_name,last_name,phone,company,created_at
1,[email protected],John,Doe,+1-555-0101,Acme Corp,2024-01-15
2,[email protected],Jane,Smith,+1-555-0102,TechStart Inc,2024-01-16

Fields available: id, email, first_name, last_name, full_name, phone, company, job_title, department, address, city, state, country, postal_code, created_at, updated_at, status, tier

E-commerce Orders

order_id,customer_id,order_date,status,subtotal,tax,shipping,total,items_count
ORD-001,CUST-123,2024-01-15,completed,89.99,7.20,5.99,103.18,3
ORD-002,CUST-456,2024-01-16,processing,149.50,11.96,0.00,161.46,2

Fields available: order_id, customer_id, customer_email, order_date, status, subtotal, tax, discount, shipping, total, items_count, payment_method, shipping_method, tracking_number

Product Catalog

sku,name,category,price,cost,quantity,weight_kg,status
WBH-001,Wireless Headphones,Electronics,79.99,32.00,150,0.25,active
TPT-002,Thermal Printer,Office,299.99,145.00,45,2.10,active

Fields available: sku, product_id, name, description, category, subcategory, brand, price, cost, margin, quantity, reorder_point, weight_kg, dimensions, status, created_at

Employee/​HR Data

employee_id,email,first_name,last_name,department,job_title,hire_date,salary,manager_id
EMP001,[email protected],John,Doe,Engineering,Software Engineer,2022-03-15,95000,EMP010
EMP002,[email protected],Jane,Smith,Marketing,Marketing Manager,2021-08-01,85000,EMP015

Fields available: employee_id, email, first_name, last_name, department, job_title, hire_date, salary, bonus, manager_id, location, status, performance_rating

Financial Transactions

transaction_id,date,account_id,type,category,amount,balance,description
TXN-0001,2024-01-15,ACC-123,debit,utilities,-125.50,4874.50,Electric Company Payment
TXN-0002,2024-01-16,ACC-123,credit,salary,3500.00,8374.50,Monthly Salary Deposit

Fields available: transaction_id, date, account_id, type, category, amount, balance, description, merchant, reference_number, status

Time Series / Metrics

timestamp,metric_name,value,unit,source
2024-01-15 00:00:00,cpu_usage,45.2,percent,server-01
2024-01-15 00:05:00,cpu_usage,52.8,percent,server-01
2024-01-15 00:10:00,cpu_usage,38.1,percent,server-01

Fields available: timestamp, date, metric_name, value, unit, source, environment, tags, min, max, avg

Survey/​Form Responses

response_id,submitted_at,q1_satisfaction,q2_recommend,q3_comments,nps_score
RSP-001,2024-01-15 14:30:00,5,yes,"Great service, very helpful",9
RSP-002,2024-01-15 15:45:00,4,yes,"Good but could be faster",7

Data Generation Rules

Realistic Distributions

• Don't make all values perfectly distributed
• Include some edge cases (empty optional fields, boundary values)
• Vary string lengths naturally
• Use realistic value ranges

Consistency

• Related fields should be consistent (city matches postal code region)
• Dates should be chronologically sensible
• IDs should be unique
• Foreign keys should reference valid parent IDs

Variation

• Mix case variations where appropriate
• Include international formats (phone, address) if specified
• Vary the "completeness" of records (some with all optional fields, some without)

Validation Checklist

Before outputting, verify:

• Header row present
• Consistent column count across all rows
• Proper quoting for fields with commas
• No trailing commas
• UTF-8 encoding compatible
• Dates in consistent format
• Numbers without currency symbols
• No formula injection risks (fields starting with =, +, -, @)

Example Invocations

Prompt: "Generate CSV with 50 customer records including address" Output: Complete customers-data.csv with 50 rows, full address fields.

Prompt: "Create sample sales data CSV for Q1 2024" Output: Complete sales-q1-2024-data.csv with daily sales records Jan-Mar.

Prompt: "CSV test data for employee database import" Output: Complete employees-data.csv with realistic HR data structure.