diff --git a/docs/60-example-science-world.md b/docs/60-example-science-world.md
index 653e9dbaa..2c7d89587 100644
--- a/docs/60-example-science-world.md
+++ b/docs/60-example-science-world.md
@@ -8,6 +8,10 @@ ScienceWorld trains an agent with `verl` and Agent Lightning >=v1.0 to solve tex
 
 This example uses the local controller in asynchronous trainer mode. Each rollout runs as a local process that interacts with a ScienceWorld environment, calls the model through the AGL Gateway, and reports the final reward. It does not require K8s, Docker, or Minikube.
 
+The model selects an action with `### ACTION: <number> ###`. The agent asks vLLM to retain
+the matched stop string so a newline-terminated reply keeps the closing `###` required by
+the action parser. Invalid or out-of-range replies fall back to action zero.
+
 ## Environment Preparation
 
 Install Java and the example dependencies:
diff --git a/examples/science_world/agents/sw_agent.py b/examples/science_world/agents/sw_agent.py
index 9c5915573..11d5dc841 100644
--- a/examples/science_world/agents/sw_agent.py
+++ b/examples/science_world/agents/sw_agent.py
@@ -219,6 +219,8 @@ async def _call_llm(client: Any, messages: list[dict[str, str]], max_tokens: int
                 messages=messages,
                 max_tokens=max_tokens,
                 stop=["###\n", "###\n\n"],
+                # The strict action parser needs the closing ### in the stop string.
+                extra_body={"include_stop_str_in_output": True},
             )
             return completion.choices[0].message.content or ""
         except Exception as e:
diff --git a/tests/examples/test_science_world_agent.py b/tests/examples/test_science_world_agent.py
new file mode 100644
index 000000000..589ea844b
--- /dev/null
+++ b/tests/examples/test_science_world_agent.py
@@ -0,0 +1,91 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""ScienceWorld action selection through the OpenAI-compatible API boundary."""
+
+from __future__ import annotations
+
+import json
+import sys
+from types import ModuleType
+from typing import Any
+from unittest.mock import Mock
+
+import httpx
+import openai
+import pytest
+
+from examples.science_world.agents.sw_agent import SWAgent, _parse_action_index
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("ending", ["", "\n", "\n\n"])
+async def test_selected_action_survives_stop_filtering(monkeypatch: pytest.MonkeyPatch, ending: str) -> None:
+    generated = "### ACTION: 2 ###" + ending
+    requests: list[dict[str, Any]] = []
+    returned_text: list[str] = []
+
+    def complete(request: httpx.Request) -> httpx.Response:
+        body = json.loads(request.content)
+        requests.append(body)
+        # vLLM excludes a matched stop string unless explicitly asked to retain it.
+        text = generated
+        for stop in body.get("stop", []):
+            if stop in text:
+                end = text.index(stop) + (len(stop) if body.get("include_stop_str_in_output", False) else 0)
+                text = text[:end]
+                break
+        returned_text.append(text)
+        return httpx.Response(
+            200,
+            json={
+                "id": "completion",
+                "object": "chat.completion",
+                "created": 0,
+                "model": "test-model",
+                "choices": [{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": text}}],
+            },
+        )
+
+    env = Mock()
+    env.get_task_description.return_value = "Turn on the furnace."
+    env.reset.return_value = ("A room with a furnace.", {"score": 0})
+    env.inventory.return_value = "Nothing."
+    env.get_valid_action_object_combinations_with_templates.return_value = [
+        {"action": "look around"},
+        {"action": "inventory"},
+        {"action": "turn on furnace"},
+    ]
+    env.step.side_effect = [("Continue.", 0, False, {"score": 50}), ("Done.", 50, True, {"score": 100})]
+    scienceworld = ModuleType("scienceworld")
+    monkeypatch.setattr(scienceworld, "ScienceWorldEnv", Mock(return_value=env), raising=False)
+    monkeypatch.setitem(sys.modules, "scienceworld", scienceworld)
+    for name, value in {
+        "TASK_NAME": "test",
+        "VARIATION_IDX": "0",
+        "SW_MAX_STEPS": "2",
+        "SW_MAX_VALID_ACTIONS_SHOWN": "3",
+        "AGL_KEY": "test-key",
+        "AGL_EVENT_URL": "http://gateway/events",
+        "AGL_OPENAI_BASE_URL": "http://gateway/v1",
+    }.items():
+        monkeypatch.setenv(name, value)
+    reward_post = Mock(return_value=httpx.Response(200, request=httpx.Request("POST", "http://gateway/events")))
+    monkeypatch.setattr(httpx, "post", reward_post)
+
+    async with (
+        httpx.AsyncClient(transport=httpx.MockTransport(complete)) as http_client,
+        openai.AsyncOpenAI(api_key="test-key", base_url="http://gateway/v1", http_client=http_client) as client,
+    ):
+        monkeypatch.setattr(openai, "AsyncOpenAI", lambda **_kwargs: client)
+        await SWAgent().run()
+
+    assert [call.args[0] for call in env.step.call_args_list] == ["turn on furnace", "turn on furnace"]
+    assert len(requests) == 2
+    assert requests[1]["messages"][-2] == {"role": "assistant", "content": returned_text[0]}
+    assert _parse_action_index(returned_text[0], 3) == 2
+    assert reward_post.call_args.kwargs["json"]["data"]["value"] == 1.0
+
+
+@pytest.mark.parametrize("text", ["### ACTION: 2", "### ACTION: invalid ###", "### ACTION: 3 ###", "unrelated"])
+def test_invalid_actions_still_use_the_fallback(text: str) -> None:
+    assert _parse_action_index(text, 3) == 0