fix(memory): address review findings from Issue #88

Fixes based on multi-agent review:

Model Improvements:
- Remove duplicate index ix_procedures_agent_type (already indexed via Column)
- Fix postgresql_where to use text() instead of string literal in Fact model
- Add thread-safety to Procedure.success_rate property (snapshot values)

Data Integrity Constraints:
- Add CheckConstraint for Episode: importance_score 0-1, duration >= 0, tokens >= 0
- Add CheckConstraint for Fact: confidence 0-1
- Add CheckConstraint for Procedure: success_count >= 0, failure_count >= 0

Migration Updates:
- Add check constraints creation in upgrade()
- Add check constraints removal in downgrade()

Note: SQLAlchemy Column default=list is correct (callable factory pattern)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

backend/app/models/memory/episode.py

@@ -8,6 +8,7 @@ with context, actions, outcomes, and lessons learned.
 
 from sqlalchemy import (
     BigInteger,
+    CheckConstraint,
     Column,
     DateTime,
     Enum,
@@ -119,6 +120,19 @@ class Episode(Base, UUIDMixin, TimestampMixin):
         Index("ix_episodes_project_time", "project_id", "occurred_at"),
         # For importance-based pruning
         Index("ix_episodes_importance_time", "importance_score", "occurred_at"),
+        # Data integrity constraints
+        CheckConstraint(
+            "importance_score >= 0.0 AND importance_score <= 1.0",
+            name="ck_episodes_importance_range",
+        ),
+        CheckConstraint(
+            "duration_seconds >= 0.0",
+            name="ck_episodes_duration_positive",
+        ),
+        CheckConstraint(
+            "tokens_used >= 0",
+            name="ck_episodes_tokens_positive",
+        ),
     )
 
     def __repr__(self) -> str:

backend/app/models/memory/fact.py

@@ -7,6 +7,7 @@ triple format with confidence scores and source tracking.
 """
 
 from sqlalchemy import (
+    CheckConstraint,
     Column,
     DateTime,
     Float,
@@ -15,6 +16,7 @@ from sqlalchemy import (
     Integer,
     String,
     Text,
+    text,
 )
 from sqlalchemy.dialects.postgresql import (
     ARRAY,
@@ -86,7 +88,7 @@ class Fact(Base, UUIDMixin, TimestampMixin):
             "predicate",
             "object",
             unique=True,
-            postgresql_where="project_id IS NOT NULL",
+            postgresql_where=text("project_id IS NOT NULL"),
         ),
         # Query patterns
         Index("ix_facts_subject_predicate", "subject", "predicate"),
@@ -94,6 +96,11 @@ class Fact(Base, UUIDMixin, TimestampMixin):
         Index("ix_facts_confidence_time", "confidence", "last_reinforced"),
         # For finding facts by entity (subject or object)
         Index("ix_facts_subject", "subject"),
+        # Data integrity constraints
+        CheckConstraint(
+            "confidence >= 0.0 AND confidence <= 1.0",
+            name="ck_facts_confidence_range",
+        ),
     )
 
     def __repr__(self) -> str:

backend/app/models/memory/procedure.py

@@ -7,6 +7,7 @@ derived from successful task execution patterns.
 """
 
 from sqlalchemy import (
+    CheckConstraint,
     Column,
     DateTime,
     ForeignKey,
@@ -91,22 +92,35 @@ class Procedure(Base, UUIDMixin, TimestampMixin):
         ),
         # Query patterns
         Index("ix_procedures_project_name", "project_id", "name"),
-        Index("ix_procedures_agent_type", "agent_type_id"),
+        # Note: agent_type_id already has index=True on Column definition
         # For finding best procedures
         Index("ix_procedures_success_rate", "success_count", "failure_count"),
+        # Data integrity constraints
+        CheckConstraint(
+            "success_count >= 0",
+            name="ck_procedures_success_positive",
+        ),
+        CheckConstraint(
+            "failure_count >= 0",
+            name="ck_procedures_failure_positive",
+        ),
     )
 
     @property
     def success_rate(self) -> float:
         """Calculate the success rate of this procedure."""
-        total = self.success_count + self.failure_count
+        # Snapshot values to avoid race conditions in concurrent access
+        success = self.success_count
+        failure = self.failure_count
+        total = success + failure
         if total == 0:
             return 0.0
-        return self.success_count / total
+        return success / total
 
     @property
     def total_uses(self) -> int:
         """Get total number of times this procedure was used."""
+        # Snapshot values for consistency
         return self.success_count + self.failure_count
 
     def __repr__(self) -> str: