diff --git a/atlasbot/engine/answerer.py b/atlasbot/engine/answerer.py
index 6010d4c..72b0421 100644
--- a/atlasbot/engine/answerer.py
+++ b/atlasbot/engine/answerer.py
@@ -217,7 +217,8 @@ class AnswerEngine:
             classify.setdefault("focus_entity", "unknown")
             classify.setdefault("focus_metric", "unknown")
             _debug_log("route_parsed", {"classify": classify, "normalized": normalized})
-            force_metric = bool(re.search(r"\bhow many\b|\bcount\b|\btotal\b", normalized.lower()))
+            lowered_question = f"{question} {normalized}".lower()
+            force_metric = bool(re.search(r"\bhow many\b|\bcount\b|\btotal\b", lowered_question))
             cluster_terms = (
                 "atlas",
                 "cluster",
@@ -241,7 +242,7 @@ class AnswerEngine:
                 "pvc",
                 "storage",
             )
-            if any(term in normalized.lower() for term in cluster_terms):
+            if any(term in lowered_question for term in cluster_terms):
                 classify["needs_snapshot"] = True
             lowered_norm = normalized.lower()
             if (
@@ -251,11 +252,19 @@ class AnswerEngine:
             ):
                 classify["question_type"] = "metric"
                 classify["needs_snapshot"] = True
-            if re.search(r"\b(how many|count|number of|list)\b", normalized.lower()):
+            if re.search(r"\b(how many|count|number of|list)\b", lowered_question):
                 classify["question_type"] = "metric"
+            if any(term in lowered_question for term in ("postgres", "connections", "db")):
+                classify["question_type"] = "metric"
+                classify["needs_snapshot"] = True
+            if any(term in lowered_question for term in ("pvc", "persistentvolume", "persistent volume", "storage")):
+                if classify.get("question_type") not in {"metric", "diagnostic"}:
+                    classify["question_type"] = "metric"
+                classify["needs_snapshot"] = True
+            if "ready" in lowered_question and classify.get("question_type") not in {"metric", "diagnostic"}:
+                classify["question_type"] = "diagnostic"
             hottest_terms = ("hottest", "highest", "lowest", "most")
             metric_terms = ("cpu", "ram", "memory", "net", "network", "io", "disk", "load", "usage", "pod", "pods", "namespace")
-            lowered_question = f"{question} {normalized}".lower()
             if any(term in lowered_question for term in hottest_terms) and any(term in lowered_question for term in metric_terms):
                 classify["question_type"] = "metric"