Data Validation Skill

Verify business logic, data integrity, and processing correctness.

Features

📊 Data Integrity

• Referential integrity checks
• Data type validation
• Range and constraint validation
• Null/required field checks

🔄 Business Logic

• Workflow validation
• Calculation verification
• State machine validation
• Rule engine checks

📈 Data Quality

• Duplicate detection
• Consistency checks
• Completeness analysis
• Accuracy verification

Trigger Patterns

"数据验证", "data validation", "validate"
"逻辑验证", "logic verification"
"数据检查", "data check"
"业务逻辑", "business logic"
"数据质量", "data quality"

Output Format

┌─────────────────────────────────────────────────────┐
│ Data Validation Report                              │
├─────────────────────────────────────────────────────┤
│ Table: {table_name}                                 │
│ Records: {count}                                    │
├─────────────────────────────────────────────────────┤
│ ✓ Passed: {pass_count}                              │
│ ✗ Failed: {fail_count}                              │
│ ⚠ Warnings: {warn_count}                           │
├─────────────────────────────────────────────────────┤
│ Issues:                                             │
│ • {issue_description}                               │
│ • {issue_description}                               │
└─────────────────────────────────────────────────────┘

Validation Types

Schema Validation

Business Rules

Learning Integration

This skill supports FlowMind learning:

• Validation Rules: Learns your business rules
• Error Tolerance: Learns acceptable error rates
• Output Format: Learns preferred report format

User: "金额不能为负数"
FlowMind: ✓ Learned: Amount must be non-negative

User: [Next validation]
FlowMind: [Checks for negative amounts]

Examples

Example 1: Order Validation

User: 验证订单数据的正确性

FlowMind:
┌─────────────────────────────────────────────────────┐
│ Order Validation Report                             │
├─────────────────────────────────────────────────────┤
│ Table: orders                                       │
│ Records: 1,000                                      │
├─────────────────────────────────────────────────────┤
│ ✓ Passed: 985                                       │
│ ✗ Failed: 15                                        │
│ ⚠ Warnings: 5                                       │
├─────────────────────────────────────────────────────┤
│ Critical Issues:                                    │
│ • 10 orders with negative total                     │
│ • 5 orders with missing customer_id                 │
├─────────────────────────────────────────────────────┤
│ Warnings:                                           │
│ • 5 orders with future dates                        │
└─────────────────────────────────────────────────────┘

Example 2: Calculation Verification

User: 验证订单金额计算是否正确

FlowMind:
┌─────────────────────────────────────────────────────┐
│ Calculation Verification                            │
├─────────────────────────────────────────────────────┤
│ Formula: subtotal + tax = total                     │
│ Records Checked: 500                                │
├─────────────────────────────────────────────────────┤
│ ✓ Correct: 498 (99.6%)                              │
│ ✗ Incorrect: 2 (0.4%)                               │
├─────────────────────────────────────────────────────┤
│ Errors:                                             │
│ • Order #1234: Expected 110.00, Got 100.00          │
│ • Order #5678: Expected 55.50, Got 55.00            │
└─────────────────────────────────────────────────────┘

Configuration

{
  "data-validation": {
    "rules": {
      "required": ["id", "created_at", "status"],
      "types": {
        "id": "integer",
        "email": "email",
        "phone": "phone"
      },
      "ranges": {
        "age": { "min": 0, "max": 150 },
        "amount": { "min": 0 }
      }
    },
    "business": {
      "calculations": [
        {
          "name": "order_total",
          "formula": "subtotal + tax = total",
          "tolerance": 0.01
        }
      ]
    }
  }
}

Custom Rules

Define Custom Validation

{
  "data-validation": {
    "customRules": [
      {
        "name": "valid_email",
        "field": "email",
        "pattern": "^[\\w.-]+@[\\w.-]+\\.\\w+$",
        "message": "Invalid email format"
      }
    ]
  }
}

Business Rule Validation

{
  "data-validation": {
    "businessRules": [
      {
        "name": "order_amount",
        "condition": "amount > 0",
        "message": "Order amount must be positive"
      }
    ]
  }
}