@@ -246,7 +246,25 @@ def _normalize_ranking_filter(
 
 def _normalize_attribute_filter(filter_dict: dict, _fields: dict) -> dict:
     raw_state = filter_dict.get("state") or {}
-    state = {k: v for k, v in raw_state.items() if v}
+    # Sort the element lists: `include`/`exclude` name a SET of elements, but the caller
+    # serialises this dict with json.dumps(..., sort_keys=True), which orders the dict
+    # KEYS and leaves the lists alone. Without this, the same filter written in a
+    # different order compares unequal, and an agent has no reason to keep that order
+    # stable between runs -- so a question needing a multi-element filter passed or
+    # failed partly at random, reported as `filters_correct: false` and indistinguishable
+    # from the agent genuinely filtering wrongly.
+    #
+    # The key is the element's own canonical JSON, not a bare sort and not str(): a bare
+    # sort raises TypeError on a mixed-type list (["A", 2]), and a crash inside scoring is
+    # worse than the mismatch this fixes -- while str() collapses 1 and "1" to the same
+    # key, so the stable sort leaves THEIR order as it found it and the ordering bug
+    # survives for exactly that pair. These values are always parsed JSON, so json.dumps
+    # cannot fail on them and it distinguishes types the way the comparison downstream does.
+    state = {
+        k: (sorted(v, key=lambda element: json.dumps(element, sort_keys=True)) if isinstance(v, list) else v)
+        for k, v in raw_state.items()
+        if v
+    }
     return {
         "type": "attribute_filter",
         "field_uri": filter_dict.get("using", ""),
 
@@ -70,6 +70,80 @@ def test_check_filters_exact_attribute_match():
     assert scores.all_ok is True
 
 
+# --- attribute-filter element order must not decide the verdict ---
+#
+# `_normalize_attribute_filter` passes `state` through untouched and the caller serialises
+# it with json.dumps(..., sort_keys=True). sort_keys orders the DICT KEYS (field_uri,
+# state, type) and never the LIST under state["include"], so two filters selecting the
+# same elements in a different order compare unequal.
+#
+# Found from a real eval run (gdc-mic-ai-evaluation, micai_diagnose_master, 2026-09-10):
+# a question filtering cross-border traffic scored metrics_correct=True,
+# dimensions_correct=True, filters_correct=False, because the fixture listed
+# ["Inter-region", "Intra-region"] and the agent emitted ["Intra-region", "Inter-region"].
+# Element order is not something an agent has any reason to keep stable between runs, so
+# every question needing a multi-value attribute filter passes or fails partly at random.
+
+
+def test_attribute_filter_include_order_does_not_change_the_verdict():
+    def viz(values):
+        return _viz(
+            query={
+                "fields": {},
+                "filter_by": {
+                    "f_a": {
+                        "type": "attribute_filter",
+                        "using": "label/cross_border_name",
+                        "state": {"include": values},
+                    }
+                },
+            }
+        )
+
+    expected = viz(["Inter-region", "Intra-region"])
+    actual = viz(["Intra-region", "Inter-region"])
+    assert check_filters(expected, actual).attribute_ok is True
+
+
+def test_attribute_filter_exclude_order_does_not_change_the_verdict():
+    def viz(values):
+        return _viz(
+            query={
+                "fields": {},
+                "filter_by": {
+                    "f_a": {
+                        "type": "attribute_filter",
+                        "using": "label/region",
+                        "state": {"exclude": values},
+                    }
+                },
+            }
+        )
+
+    assert check_filters(viz(["EMEA", "APAC"]), viz(["APAC", "EMEA"])).attribute_ok is True
+
+
+def test_attribute_filter_with_different_elements_still_fails():
+    """The fix must not make the comparison permissive -- a genuinely different set
+    of elements is still a mismatch."""
+
+    def viz(values):
+        return _viz(
+            query={
+                "fields": {},
+                "filter_by": {
+                    "f_a": {
+                        "type": "attribute_filter",
+                        "using": "label/region",
+                        "state": {"include": values},
+                    }
+                },
+            }
+        )
+
+    assert check_filters(viz(["EMEA", "APAC"]), viz(["EMEA", "LATAM"])).attribute_ok is False
+
+
 # --- ranking-filter `attribute` is optional on single-dimension visualizations (QA-28615) ---
 #
 # `attribute` is NotRequired in the AAC schema and AFM ranks over the whole result when it is
@@ -210,6 +284,87 @@ def test_normalized_filters_is_empty_per_category_when_unfiltered():
     assert normalized_filters(viz) == {"date": [], "ranking": [], "attribute": []}
 
 
+def _attr_viz(values, key="include", using="label/cross_border_name"):
+    return _viz(
+        query={
+            "fields": {"m": {"using": "metric/approval_rate"}},
+            "filter_by": {"f": {"type": "attribute_filter", "using": using, "state": {key: values}}},
+        },
+        metrics=["m"],
+    )
+
+
+def test_attribute_filter_elements_compare_as_a_set_not_a_sequence():
+    """`include`/`exclude` name a set of elements, so element order must not decide a verdict.
+
+    json.dumps(sort_keys=True) orders the dict KEYS and leaves the lists alone, so the same
+    filter emitted in a different order compared unequal -- and the agent has no reason to
+    keep that order stable between runs. The failure reported as `filters_correct: false`,
+    indistinguishable from the agent genuinely filtering wrongly.
+    """
+    expected = _attr_viz(["Inter-region", "Intra-region"])
+    assert check_filters(expected, _attr_viz(["Inter-region", "Intra-region"])).attribute_ok is True
+    assert check_filters(expected, _attr_viz(["Intra-region", "Inter-region"])).attribute_ok is True
+
+
+def test_a_three_element_attribute_filter_is_order_insensitive():
+    """Two elements need 2 permutations, three need 6 -- admitting them as extra fixture
+    candidates grows factorially, which is why this belongs in normalisation."""
+    expected = _attr_viz(["A", "B", "C"])
+    for actual in (["C", "A", "B"], ["B", "C", "A"], ["C", "B", "A"]):
+        assert check_filters(expected, _attr_viz(actual)).attribute_ok is True
+
+
+def test_exclude_elements_are_order_insensitive_too():
+    expected = _attr_viz(["Domestic", "Unknown"], key="exclude")
+    assert check_filters(expected, _attr_viz(["Unknown", "Domestic"], key="exclude")).attribute_ok is True
+
+
+def test_ordering_does_not_mask_a_genuinely_different_element_set():
+    """The guard against the fix being "pass everything": different elements still fail."""
+    expected = _attr_viz(["Inter-region", "Intra-region"])
+    assert check_filters(expected, _attr_viz(["Inter-region"])).attribute_ok is False
+    assert check_filters(expected, _attr_viz(["Inter-region", "Domestic"])).attribute_ok is False
+
+
+def test_include_and_exclude_of_the_same_elements_still_differ():
+    """Sorting must not collapse the two state keys into each other."""
+    inc = _attr_viz(["Domestic", "Unknown"], key="include")
+    exc = _attr_viz(["Unknown", "Domestic"], key="exclude")
+    assert check_filters(inc, exc).attribute_ok is False
+
+
+def test_the_same_elements_on_a_different_label_still_differ():
+    expected = _attr_viz(["A", "B"], using="label/cross_border_name")
+    assert check_filters(expected, _attr_viz(["B", "A"], using="label/region_name")).attribute_ok is False
+
+
+def test_a_mixed_type_element_list_does_not_crash_scoring():
+    """A malformed list would raise TypeError from a bare sorted(), and a crash inside
+    scoring is worse than the mismatch this fixes. validate_cross_references reports
+    malformed filter values separately, so this only has to stay comparable."""
+    expected = _attr_viz(["A", 2])
+    assert check_filters(expected, _attr_viz([2, "A"])).attribute_ok is True
+    assert check_filters(expected, _attr_viz(["A", 3])).attribute_ok is False
+
+
+def test_elements_that_stringify_alike_but_differ_in_type_still_sort_stably():
+    """`key=str` collapsed 1 and "1" to the same sort key, so Python's stable sort left
+    their relative order exactly as the agent emitted it and the ordering bug survived for
+    that pair alone. The key is the element's canonical JSON instead, which distinguishes
+    the types the comparison downstream also distinguishes."""
+    assert check_filters(_attr_viz([1, "1"]), _attr_viz(["1", 1])).attribute_ok is True
+    # ...without making the two types interchangeable: one element is not the other set.
+    assert check_filters(_attr_viz([1]), _attr_viz(["1"])).attribute_ok is False
+
+
+def test_heterogeneous_element_lists_sort_without_raising():
+    """Every value here is parsed JSON, so json.dumps cannot fail on it -- which is what
+    makes it usable as a total ordering where a bare sort would raise."""
+    mixed = [None, True, 2, "a", 1.5]
+    assert check_filters(_attr_viz(mixed), _attr_viz(list(reversed(mixed)))).attribute_ok is True
+
+
 # --- relative vs absolute date filters denote the same period ---
 #
 # The agent answers "last month" either relatively (granularity MONTH, from -1, to -1)