diff --git a/rdagent/components/coder/data_science/share/eval.py b/rdagent/components/coder/data_science/share/eval.py
index d3b95f5f42..af6ec425b1 100644
--- a/rdagent/components/coder/data_science/share/eval.py
+++ b/rdagent/components/coder/data_science/share/eval.py
@@ -166,11 +166,16 @@ def evaluate(
             # Read the content of files submission.csv and scores.csv after execution
             # Check if the content has changed
             # excactly same checking. But it will take more user's time
+            change_messages = []
             if scores_content_before != scores_content_after:
-                return_msg = "\n[Error] The content of scores.csv has changed. Please check the code to ensure that the model is dumped correctly, and rerun the code to use the model directly without retraining it."
-                return_msg += f"\nBefore:\n{scores_content_before}\nAfter:\n{scores_content_after}"
-                if submission_content_before != submission_content_after:
-                    # If the scores file changes, display the two contents and append it into the return_checking
-                    return_msg = "[Error] The content of submission.csv has changed. Please check the code to ensure that the model is dumped correctly, and rerun the code to use the model directly without retraining it."
-                csfb.return_checking = (csfb.return_checking or "") + return_msg
+                change_messages.append(
+                    "\n[Error] The content of scores.csv has changed. Please check the code to ensure that the model is dumped correctly, and rerun the code to use the model directly without retraining it."
+                    f"\nBefore:\n{scores_content_before}\nAfter:\n{scores_content_after}",
+                )
+            if submission_content_before != submission_content_after:
+                change_messages.append(
+                    "\n[Error] The content of submission.csv has changed. Please check the code to ensure that the model is dumped correctly, and rerun the code to use the model directly without retraining it.",
+                )
+            if change_messages:
+                csfb.return_checking = (csfb.return_checking or "") + "".join(change_messages)
         return csfb
diff --git a/test/scenarios/data_science/test_model_dump_high_diagnostics.py b/test/scenarios/data_science/test_model_dump_high_diagnostics.py
new file mode 100644
index 0000000000..e8d0a5d2ac
--- /dev/null
+++ b/test/scenarios/data_science/test_model_dump_high_diagnostics.py
@@ -0,0 +1,95 @@
+from types import SimpleNamespace
+
+import pytest
+
+import rdagent.components.coder.data_science.share.eval as share_eval
+from rdagent.components.coder.CoSTEER.evaluators import CoSTEERSingleFeedback
+from rdagent.components.coder.data_science.share.eval import ModelDumpEvaluator
+
+
+class FakeTemplate:
+    def r(self, *args, **kwargs):
+        return "/input"
+
+
+@pytest.mark.parametrize(
+    ("change_scores", "change_submission", "expected_messages"),
+    [
+        (True, False, ("scores.csv",)),
+        (False, True, ("submission.csv",)),
+        (True, True, ("scores.csv", "submission.csv")),
+        (False, False, ()),
+    ],
+)
+def test_model_dump_high_check_reports_each_changed_artifact(
+    tmp_path,
+    monkeypatch,
+    change_scores,
+    change_submission,
+    expected_messages,
+):
+    monkeypatch.setattr(share_eval, "T", lambda *args, **kwargs: FakeTemplate())
+    monkeypatch.setattr(share_eval, "get_ds_env", lambda *args, **kwargs: object())
+    monkeypatch.setattr(share_eval, "get_clear_ws_cmd", lambda *args, **kwargs: "clear")
+    monkeypatch.setattr(share_eval, "remove_eda_part", lambda stdout: stdout)
+    monkeypatch.setattr(share_eval.DS_RD_SETTING, "model_dump_check_level", "high")
+    monkeypatch.setattr(
+        share_eval,
+        "build_cls_from_json_with_retry",
+        lambda *args, **kwargs: CoSTEERSingleFeedback(
+            execution="ok",
+            return_checking="existing diagnostics",
+            code="ok",
+            final_decision=True,
+        ),
+    )
+
+    (tmp_path / "models").mkdir()
+    (tmp_path / "models" / "model.bin").write_text("model", encoding="utf-8")
+
+    scores_before = "model,score\nensemble,0.1\n"
+    scores_after = "model,score\nensemble,0.2\n"
+    submission_before = "id,pred\n1,0.1\n"
+    submission_after = "id,pred\n1,0.2\n"
+    (tmp_path / "scores.csv").write_text(scores_before, encoding="utf-8")
+    (tmp_path / "submission.csv").write_text(submission_before, encoding="utf-8")
+
+    class FakeImplementation:
+        workspace_path = tmp_path
+        all_codes = {"main.py": "pass"}
+
+        def execute(self, env=None, entry=None):
+            if entry == "clear":
+                (tmp_path / "scores.csv").unlink(missing_ok=True)
+                (tmp_path / "submission.csv").unlink(missing_ok=True)
+                return "cleared"
+
+            assert "--inference" in entry
+            (tmp_path / "scores.csv").write_text(
+                scores_after if change_scores else scores_before,
+                encoding="utf-8",
+            )
+            (tmp_path / "submission.csv").write_text(
+                submission_after if change_submission else submission_before,
+                encoding="utf-8",
+            )
+            return "inference finished"
+
+    scen = SimpleNamespace(
+        competition="demo-competition",
+        debug_path="/tmp/demo-input",
+        real_debug_timeout=lambda: 1,
+        real_full_timeout=lambda: 1,
+    )
+    feedback = ModelDumpEvaluator(scen, data_type="sample").evaluate(
+        None,
+        FakeImplementation(),
+        None,
+    )
+
+    diagnostics = feedback.return_checking or ""
+    assert "existing diagnostics" in diagnostics
+    for filename in expected_messages:
+        assert f"content of {filename} has changed" in diagnostics
+    for filename in {"scores.csv", "submission.csv"} - set(expected_messages):
+        assert f"content of {filename} has changed" not in diagnostics