def test_agent_action_registries_keep_l2_and_l3_boundaries():
    import services.agent_actions as actions

    assert set(actions.SAFE_ACTIONS) == {
        "retry_task",
        "query_km",
        "silence_alert",
        "flag_for_human_review",
        "route_to_km",
        "mark_for_relearn",
    }
    assert set(actions.OPS_ACTIONS) == {
        "pause_task",
        "resume_task",
        "force_retry_now",
    }
    assert set(actions.SAFE_ACTIONS).isdisjoint(actions.OPS_ACTIONS)

    for action_name, func in actions.SAFE_ACTIONS.items():
        assert getattr(actions, action_name) is func
    for action_name, func in actions.OPS_ACTIONS.items():
        assert getattr(actions, action_name) is func


def test_flag_for_human_review_writes_pending_memory(monkeypatch):
    import services.agent_actions as actions
    import services.openclaw_learning_service as learning

    calls = []
    monkeypatch.setattr(actions, "_audit", lambda *args, **kwargs: 999)
    monkeypatch.setattr(
        learning,
        "store_insight",
        lambda **kwargs: calls.append(kwargs) or 123,
    )

    result = actions.flag_for_human_review("SKU-1", "銷量斷崖，請人工確認")

    assert result["status"] == "pending_review"
    assert result["insight_id"] == 123
    assert calls[0]["insight_type"] == "human_review"
    assert calls[0]["status"] == "pending"
    assert calls[0]["product_sku"] == "SKU-1"


def test_route_to_km_writes_archived_memory(monkeypatch):
    import services.agent_actions as actions
    import services.openclaw_learning_service as learning

    calls = []
    monkeypatch.setattr(actions, "_audit", lambda *args, **kwargs: 999)
    monkeypatch.setattr(learning, "store_insight", lambda **kwargs: calls.append(kwargs) or 456)

    result = actions.route_to_km("SKU-2", "pricing", "競品價差擴大")

    assert result == {"status": "archived", "sku": "SKU-2", "domain": "pricing", "insight_id": 456}
    assert calls[0]["insight_type"] == "km_entry"
    assert calls[0]["metadata"]["domain"] == "pricing"


def test_mark_for_relearn_writes_pending_marker(monkeypatch):
    import services.agent_actions as actions
    import services.openclaw_learning_service as learning

    calls = []
    monkeypatch.setattr(actions, "_audit", lambda *args, **kwargs: 999)
    monkeypatch.setattr(learning, "store_insight", lambda **kwargs: calls.append(kwargs) or 789)

    result = actions.mark_for_relearn("SKU-3", "NemoTron 信心不足")

    assert result["status"] == "marked"
    assert result["insight_id"] == 789
    assert calls[0]["insight_type"] == "relearn_marker"
    assert calls[0]["status"] == "pending"