diff --git a/browsergym/webarena_verified/src/browsergym/webarena_verified/evaluators.py b/browsergym/webarena_verified/src/browsergym/webarena_verified/evaluators.py
index bd30bcb3..3f34662b 100644
--- a/browsergym/webarena_verified/src/browsergym/webarena_verified/evaluators.py
+++ b/browsergym/webarena_verified/src/browsergym/webarena_verified/evaluators.py
@@ -121,10 +121,7 @@ def __call__(
             logger.info(
                 f"- {result.evaluator_name}: status: {result.status}, score: {result.score}, error_msg: {result.error_msg}"
             )
-        # return average score if multiple evaluators are present, otherwise return the aggregated score
-        return (
-            sum(result.score for result in results.evaluators_results)
-            / len(results.evaluators_results)
-            if results.evaluators_results
-            else results.score
-        )
+        # webarena_verified scores a task 1.0 only when every evaluator passes, and 0.0 when any
+        # evaluator fails or errors. Return that task score instead of averaging the evaluators,
+        # which would give partial credit to tasks the benchmark counts as failed.
+        return results.score
diff --git a/tests/webarena/test_webarena_verified_evaluator.py b/tests/webarena/test_webarena_verified_evaluator.py
new file mode 100644
index 00000000..8e0bd12a
--- /dev/null
+++ b/tests/webarena/test_webarena_verified_evaluator.py
@@ -0,0 +1,86 @@
+import importlib.resources
+import importlib.util
+import json
+from unittest.mock import MagicMock, patch
+
+import playwright.sync_api
+import pytest
+
+# Skip test if webarena_verified is not installed or importable in this environment
+webarena_verified_installed = importlib.util.find_spec("browsergym.webarena_verified") is not None
+if webarena_verified_installed:
+    from browsergym.webarena_verified.evaluators import WebArenaVerifiedEvaluator
+    from webarena.browser_env.actions import ActionTypes
+    from webarena_verified.types.eval import (
+        EvalAssertion,
+        EvalStatus,
+        EvaluatorResult,
+        TaskEvalResult,
+    )
+
+
+def two_evaluator_task():
+    dataset = json.loads(
+        importlib.resources.files("webarena_verified")
+        .joinpath("assets/dataset/webarena-verified.json")
+        .read_text()
+    )
+    return next(task for task in dataset if len(task["eval"]) == 2)
+
+
+def evaluator_result(name, status):
+    if status == "error":
+        return EvaluatorResult.create(
+            evaluator_name=name, is_error=True, error_msg="evaluator failed"
+        )
+    assertion = EvalAssertion.create(assertion_name="check", status=EvalStatus(status))
+    return EvaluatorResult.create(evaluator_name=name, assertions=[assertion])
+
+
+@pytest.mark.skipif(
+    not webarena_verified_installed, reason="browsergym.webarena_verified not installed"
+)
+@pytest.mark.parametrize(
+    "statuses,expected_reward",
+    [
+        (("success", "success"), 1.0),
+        (("success", "failure"), 0.0),
+        (("failure", "success"), 0.0),
+        (("success", "error"), 0.0),
+    ],
+)
+def test_reward_is_the_webarena_verified_task_score(statuses, expected_reward, tmp_path):
+    """A task only counts as solved when every one of its evaluators passes."""
+    task = two_evaluator_task()
+    results = TaskEvalResult.create(
+        task_id=task["task_id"],
+        intent_template_id=task["intent_template_id"],
+        sites=tuple(task["sites"]),
+        task_revision=task["revision"],
+        data_checksum="test",
+        evaluators_results=[
+            evaluator_result(spec["evaluator"], status)
+            for spec, status in zip(task["eval"], statuses)
+        ],
+    )
+    assert results.score == expected_reward
+
+    config_file = tmp_path / "task.json"
+    config_file.write_text(json.dumps(task))
+
+    # Skip __init__, which builds the evaluation harness from a live WebArena instance.
+    evaluator = WebArenaVerifiedEvaluator.__new__(WebArenaVerifiedEvaluator)
+    evaluator.evaluator = MagicMock()
+    evaluator.evaluator.evaluate_task.return_value = results
+    page = MagicMock(spec=playwright.sync_api.Page)
+
+    with patch("browsergym.webarena_verified.evaluators.NetworkTrace"), patch(
+        "browsergym.webarena_verified.evaluators.TaskEvalContext"
+    ):
+        reward = evaluator(
+            trajectory=[{}, {"action_type": ActionTypes.STOP, "answer": "{}"}],
+            config_file=str(config_file),
+            page=page,
+        )
+
+    assert reward == expected_reward