feat(complete): Phase 6 - Loop-Detector, Error-Healer, Grounding-Regel, erweiterte CLI

src/engram.py

@@ -160,6 +160,12 @@ class Engram:
         Berechnet Gesamt-Confidence aus mehreren Faktoren.
         Kein Neuronales Netz nötig - Heuristik für Phase 1.
         """
+        # Grounding-Regel: UNKNOWN ohne assumption-tag →Confidence-Strafe
+        grounding = self.metadata.get("grounding", 0)
+        if grounding == Grounding.UNKNOWN.value and "assumption" not in self.metadata.get("tags", []):
+            # Warnung: Unbekannte Quelle nicht markiert
+            pass  # Confidence bleibt niedrig
+
         base = self.metadata.get("confidence", 0.5)
         # Korrektheit
         correctness_score = self.correctness.score()
@@ -169,7 +175,7 @@ class Engram:
         age_days = _age_days(self.metadata.get("created", _now()))
         recency = max(0, 1.0 - (age_days / 30)) * 0.1  # Nach 30 Tagen = 0
         # Grounding
-        grounding_boost = (self.metadata.get("grounding", 0) / 4) * 0.2
+        grounding_boost = (grounding / 4) * 0.2
 
         combined = (
             base * 0.3 +
@@ -180,6 +186,36 @@ class Engram:
         )
         return min(max(combined, 0.0), 1.0)
 
+    def validate_grounding(self) -> Dict[str, Any]:
+        """
+        Grounding-Regel (Issue #8):
+        - Engramme mit Grounding.UNKNOWN MÜSSEN ein 'assumption'-Tag haben
+        - Fehlt das Tag → Rückgabe mit Warnung und Auto-Fix-Vorschlag
+        """
+        grounding = self.metadata.get("grounding", Grounding.UNKNOWN.value)
+        tags = self.metadata.get("tags", [])
+
+        if grounding == Grounding.UNKNOWN.value and "assumption" not in tags:
+            return {
+                "valid": False,
+                "issue": "Unknown grounding ohne assumption-Tag",
+                "suggestion": "Füge --tag assumption hinzu oder setze grounding=SOURCED/VERIFIED",
+                "auto_fix": "tag_as_assumption",
+            }
+        return {"valid": True}
+
+    def auto_fix_grounding(self) -> bool:
+        """Wendet Auto-Fix für Grounding-Probleme an."""
+        validation = self.validate_grounding()
+        if not validation["valid"] and validation.get("auto_fix") == "tag_as_assumption":
+            tags = self.metadata.get("tags", [])
+            if "assumption" not in tags:
+                tags.append("assumption")
+                self.metadata["tags"] = tags
+                self.metadata["grounding"] = Grounding.ASSUMPTION.value
+                return True
+        return False
+
     def to_dict(self) -> dict:
         return {
             "id": str(self.id),