diff --git a/src/agentunit/adapters/autogen_ag2.py b/src/agentunit/adapters/autogen_ag2.py
index 377f209..51ff324 100644
--- a/src/agentunit/adapters/autogen_ag2.py
+++ b/src/agentunit/adapters/autogen_ag2.py
@@ -318,7 +318,7 @@ def end_session(self, session_id: SessionID) -> ScenarioResult:
             case_id=session_id,
             success=True,
             metrics=metrics,
-            duration_ms=0.0,  # TODO: Track actual duration
+            duration_ms=((session["end_time"] - session["start_time"]).total_seconds() * 1000),
             trace=trace,
         )
 
@@ -340,6 +340,19 @@ def _calculate_session_metrics(self, session_id: SessionID) -> dict[str, Any]:
             interaction for interaction in self.interactions if interaction.session_id == session_id
         ]
 
+        response_times = []
+
+        # Go through messages one by one
+        for i in range(1, len(session_interactions)):
+            previous_message_time = session_interactions[i - 1].timestamp
+            current_message_time = session_interactions[i].timestamp
+
+            time_difference = (current_message_time - previous_message_time).total_seconds()
+
+            response_times.append(time_difference)
+
+        average_response_time = sum(response_times) / len(response_times) if response_times else 0.0
+
         # Basic metrics
         metrics = {
             "total_messages": len(session_interactions),
@@ -347,7 +360,7 @@ def _calculate_session_metrics(self, session_id: SessionID) -> dict[str, Any]:
             "duration_seconds": (
                 session.get("end_time", datetime.now()) - session["start_time"]
             ).total_seconds(),
-            "average_response_time": 0.0,  # Would need timing data
+            "average_response_time": average_response_time,
             "conversation_turns": session.get("message_count", 0),
         }
 
diff --git a/src/agentunit/datasets/base.py b/src/agentunit/datasets/base.py
index 093ba9f..9582fd5 100644
--- a/src/agentunit/datasets/base.py
+++ b/src/agentunit/datasets/base.py
@@ -79,7 +79,25 @@ def _loader() -> Iterable[DatasetCase]:
     return DatasetSource(name=str(file_path.stem), loader=_loader)
 
 
-def load_local_csv(path: str | Path) -> DatasetSource:
+def _parse_list_field(value: str | None, delimiter: str) -> list[str] | None:
+    """Safely parse a delimited list field from CSV."""
+    if not value or not isinstance(value, str):
+        return None
+
+    if not delimiter:
+        # Empty delimiter is invalid for str.split
+        return [value.strip()] if value.strip() else None
+
+    parts = [item.strip() for item in value.split(delimiter)]
+    cleaned = [p for p in parts if p]
+    return cleaned or None
+
+
+def load_local_csv(
+    path: str | Path,
+    tools_delimiter: str = ";",
+    context_delimiter: str = "||",
+) -> DatasetSource:
     file_path = Path(path)
     if not file_path.exists():
         msg = f"Dataset file not found: {file_path}"
@@ -88,18 +106,29 @@ def load_local_csv(path: str | Path) -> DatasetSource:
     def _loader() -> Iterable[DatasetCase]:
         with file_path.open(newline="", encoding="utf-8") as fh:
             reader = csv.DictReader(fh)
+
             for idx, row in enumerate(reader):
-                yield DatasetCase(
-                    id=row.get("id") or f"case-{idx}",
-                    query=row["query"],
-                    expected_output=row.get("expected_output"),
-                    tools=row.get("tools", "").split(";") if row.get("tools") else None,
-                    context=row.get("context", "").split("||") if row.get("context") else None,
-                    metadata={
-                        k: v
-                        for k, v in row.items()
-                        if k not in {"id", "query", "expected_output", "tools", "context"}
-                    },
-                )
+                try:
+                    yield DatasetCase(
+                        id=row.get("id") or f"case-{idx}",
+                        query=row["query"],
+                        expected_output=row.get("expected_output"),
+                        tools=_parse_list_field(row.get("tools"), tools_delimiter),
+                        context=_parse_list_field(row.get("context"), context_delimiter),
+                        metadata={
+                            k: v
+                            for k, v in row.items()
+                            if k
+                            not in {
+                                "id",
+                                "query",
+                                "expected_output",
+                                "tools",
+                                "context",
+                            }
+                        },
+                    )
+                except Exception as exc:
+                    raise AgentUnitError(f"Malformed CSV row at index {idx}: {row}") from exc
 
     return DatasetSource(name=str(file_path.stem), loader=_loader)