diff --git a/docs/dqx/docs/guide/data_contract_quality_rules_generation.mdx b/docs/dqx/docs/guide/data_contract_quality_rules_generation.mdx
index 1fac02f0a..1578797d2 100644
--- a/docs/dqx/docs/guide/data_contract_quality_rules_generation.mdx
+++ b/docs/dqx/docs/guide/data_contract_quality_rules_generation.mdx
@@ -196,6 +196,7 @@ Predefined rules are automatically derived from schema field constraints defined
         properties:
           - name: order_id
             logicalType: string
+            physicalType: string
             required: true              # → is_not_null
             unique: true                # → is_unique
             logicalTypeOptions:
@@ -203,9 +204,10 @@ Predefined rules are automatically derived from schema field constraints defined
           
           - name: customer_email
             logicalType: string
+            physicalType: string
             required: true              # → is_not_null
             logicalTypeOptions:
-              pattern: '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$'  # → regex_match
+              pattern: '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'  # → regex_match
           
           - name: order_total
             logicalType: number
@@ -217,6 +219,7 @@ Predefined rules are automatically derived from schema field constraints defined
           
           - name: order_status
             logicalType: string
+            physicalType: string
             required: true              # → is_not_null
             logicalTypeOptions:
               pattern: '^(pending|confirmed|shipped|delivered|cancelled)$'  # → regex_match
@@ -235,6 +238,7 @@ Predefined rules are automatically derived from schema field constraints defined
     )
 
     # Generated rules will include:
+    # - has_valid_schema (dataset-level, derived from the contract schema)
     # - is_not_null for order_id, customer_email, order_total, order_status
     # - is_unique for order_id
     # - regex_match for order_id (pattern validation)
@@ -313,11 +317,13 @@ Explicit rules are defined in the `quality` section of a property or schema usin
         properties:
           - name: transaction_id
             logicalType: string
+            physicalType: string
             required: true
             unique: true
             
           - name: account_id
             logicalType: string
+            physicalType: string
             required: true
             quality:
               # Property-level explicit check
@@ -451,6 +457,7 @@ Text-based expectations are defined using `type: text` in the quality section:
         properties:
           - name: email
             logicalType: string
+            physicalType: string
             required: true
             quality:
               # Field-level text expectation
@@ -462,6 +469,7 @@ Text-based expectations are defined using `type: text` in the quality section:
           
           - name: consent_date
             logicalType: date
+            physicalType: date
             required: true
             quality:
               # Another text expectation
@@ -529,9 +537,12 @@ Here's a complete example showing contract-based rule generation with all three
     id: urn:datacontract:iot:sensor_readings
     name: IoT Sensor Readings
     version: 2.1.0
-    description: Quality contract for IoT sensor data
     status: active
-    owner: IoT Platform Team
+    description:
+      purpose: Quality contract for IoT sensor data
+    team:
+      - username: iot-platform-team
+        role: owner
 
     schema:
       - name: sensor_readings
@@ -565,6 +576,7 @@ Here's a complete example showing contract-based rule generation with all three
         properties:
           - name: sensor_id
             logicalType: string
+            physicalType: string
             required: true           # Predefined: is_not_null
             unique: true             # Predefined: is_unique
             logicalTypeOptions:
@@ -572,6 +584,7 @@ Here's a complete example showing contract-based rule generation with all three
           
           - name: temperature
             logicalType: decimal
+            physicalType: decimal(5,2)
             required: true           # Predefined: is_not_null
             logicalTypeOptions:
               minimum: -40.0           # Predefined: sql_expression (range check)
@@ -585,12 +598,10 @@ Here's a complete example showing contract-based rule generation with all three
           
           - name: status
             logicalType: string
+            physicalType: string
             required: true           # Predefined: is_not_null
             logicalTypeOptions:
-              enum:                    # Predefined: regex_match
-                - active
-                - maintenance
-                - offline
+              pattern: '^(active|maintenance|offline)$'  # Predefined: regex_match
     ```
   </TabItem>
   <TabItem value="Python" label="Python Code">
@@ -766,23 +777,28 @@ id: urn:datacontract:marketing:customer_360
 name: Customer 360 View
 version: 1.2.0
 status: active
-owner: Marketing Analytics Team
-  
+team:
+  - username: marketing-analytics-team
+    role: owner
+
 schema:
   - name: customer_360
     physicalType: table
     properties:
       - name: customer_id
         logicalType: string
+        physicalType: string
         required: true
         unique: true
       - name: email
         logicalType: string
+        physicalType: string
         required: true
         logicalTypeOptions:
           pattern: '^[a-zA-Z0-9._%+-]+@.+$'
       - name: lifetime_value
         logicalType: decimal
+        physicalType: decimal(18,2)
         logicalTypeOptions:
           minimum: 0
 """
@@ -813,9 +829,11 @@ schema:
     properties:
       - name: email
         logicalType: string
+        physicalType: string
         required: true
       - name: consent_date
         logicalType: date
+        physicalType: date
         required: true
         quality:
           - type: text