Financial Data Validation Skill

This skill helps validate financial data returned from MCP servers to ensure accuracy and completeness.

Validation Process

1. •

   Verify Data Structure

   • •Check that all required fields are present
   • •Validate data types match expectations
   • •Ensure nested objects are properly formatted
2. •

   Validate Financial Values

   • •Verify prices are positive numbers
   • •Check that percentages are in valid ranges (-100% to +∞)
   • •Ensure volumes are non-negative
   • •Validate that market cap values are reasonable
3. •

   Check Data Freshness

   • •Verify timestamps are recent (within market hours or last close)
   • •Ensure data is not stale (check update frequency)
   • •Validate timezone information is correct
4. •

   Cross-Reference Validation

   • •Compare values across multiple data sources if available
   • •Verify calculated metrics match raw data
   • •Check for anomalies or outliers
5. •

   Market-Specific Validation

   • •Verify ticker symbols are valid
   • •Check that market hours are respected
   • •Ensure currency codes are ISO 4217 compliant
   • •Validate exchange identifiers

Example Validation Checks

def validate_stock_quote(quote_data):
    """Validate a stock quote from market data server."""
    required_fields = ['symbol', 'price', 'volume', 'timestamp']
    
    # Check required fields
    for field in required_fields:
        assert field in quote_data, f"Missing required field: {field}"
    
    # Validate values
    assert quote_data['price'] > 0, "Price must be positive"
    assert quote_data['volume'] >= 0, "Volume cannot be negative"
    
    # Check timestamp is recent
    timestamp = datetime.fromisoformat(quote_data['timestamp'])
    assert datetime.now() - timestamp < timedelta(minutes=15), "Data is stale"
    
    return True

Common Data Issues

• •Missing fields: Always check for null/undefined values
• •Incorrect precision: Financial data should have appropriate decimal places
• •Currency mismatches: Ensure all values use consistent currency
• •Timezone errors: Always use UTC or specify timezone explicitly
• •Split/dividend adjustments: Verify if prices are adjusted

Error Handling

When validation fails:

1. •Log the specific validation error
2. •Include the problematic data in error message
3. •Suggest corrective actions
4. •Never proceed with invalid data
5. •Consider fallback data sources