diff --git a/nexus/mnemosyne/archive.py b/nexus/mnemosyne/archive.py
index 76e2f7e4..d71ac54f 100644
--- a/nexus/mnemosyne/archive.py
+++ b/nexus/mnemosyne/archive.py
@@ -1308,3 +1308,88 @@ class MnemosyneArchive:
 
         self._save()
         return total_links
+    # ─── Discovery ──────────────────────────────────────────────
+
+    def discover(
+        self,
+        count: int = 5,
+        prefer_fading: bool = True,
+        topic: Optional[str] = None,
+    ) -> list[dict]:
+        """Serendipitous entry discovery — surface forgotten knowledge.
+
+        Selects entries probabilistically, weighting toward fading (low vitality)
+        entries when prefer_fading=True, or toward vibrant entries when False.
+        Optionally filter by topic.
+
+        Touches selected entries to boost their vitality, preventing the same
+        entries from being repeatedly surfaced.
+
+        Args:
+            count: Number of entries to discover.
+            prefer_fading: If True, weight toward neglected entries. If False,
+                           weight toward vibrant entries.
+            topic: Optional topic filter — only discover entries with this tag.
+
+        Returns:
+            List of dicts with keys: entry_id, title, content_preview, topics,
+            vitality, age_days, last_accessed
+        """
+        import random
+
+        candidates = list(self._entries.values())
+
+        # Filter by topic if specified
+        if topic:
+            topic_lower = topic.lower()
+            candidates = [
+                e for e in candidates
+                if topic_lower in [t.lower() for t in e.topics]
+            ]
+
+        if not candidates:
+            return []
+
+        # Compute vitality for each candidate
+        scored = []
+        for entry in candidates:
+            v = self._compute_vitality(entry)
+            scored.append((entry, v))
+
+        # Build selection weights
+        if prefer_fading:
+            # Lower vitality = higher weight. Invert and normalize.
+            weights = [max(0.01, 1.0 - v) for _, v in scored]
+        else:
+            # Higher vitality = higher weight
+            weights = [max(0.01, v) for _, v in scored]
+
+        # Sample without replacement
+        k = min(count, len(scored))
+        selected_indices = random.choices(range(len(scored)), weights=weights, k=k)
+        # Deduplicate while preserving order
+        seen = set()
+        unique_indices = []
+        for idx in selected_indices:
+            if idx not in seen:
+                seen.add(idx)
+                unique_indices.append(idx)
+
+        results = []
+        for idx in unique_indices:
+            entry, v = scored[idx]
+            # Touch to boost vitality
+            self.touch(entry.id)
+            created = self._parse_dt(entry.created_at)
+            age_days = (datetime.now(timezone.utc) - created).days
+            results.append({
+                "entry_id": entry.id,
+                "title": entry.title,
+                "content_preview": entry.content[:200] + "..." if len(entry.content) > 200 else entry.content,
+                "topics": entry.topics,
+                "vitality": round(v, 4),
+                "age_days": age_days,
+                "last_accessed": entry.last_accessed,
+            })
+
+        return results