diff --git a/docs/source/examples/best-practices.rst b/docs/source/examples/best-practices.rst
index 84cc78b88..2de3809c8 100644
--- a/docs/source/examples/best-practices.rst
+++ b/docs/source/examples/best-practices.rst
@@ -9,9 +9,7 @@ When choosing between two multi-GPU setups, it is best to pick the one where mos
 `DGX <https://www.nvidia.com/en-us/data-center/dgx-systems/>`_, a cloud instance with `multi-gpu options <https://rapids.ai/cloud>`_ , a high-density GPU HPC instance, etc.  This is done for two reasons:
 
 - Moving data between GPUs is costly and performance decreases when computation stops due to communication overheads, Host-to-Device/Device-to-Host transfers, etc
-- Multi-GPU instances often come with accelerated networking like `NVLink <https://www.nvidia.com/en-us/data-center/nvlink/>`_.  These accelerated
-networking paths usually have much higher throughput/bandwidth compared with traditional networking *and* don't force and Host-to-Device/Device-to-Host transfers.  See
-`Accelerated Networking`_ for more discussion
+- Multi-GPU instances often come with accelerated networking like `NVLink <https://www.nvidia.com/en-us/data-center/nvlink/>`_.  These accelerated networking paths usually have much higher throughput/bandwidth compared with traditional networking *and* don't force and Host-to-Device/Device-to-Host transfers.  See `Accelerated Networking`_ for more discussion.
 
 .. code-block:: python
 
diff --git a/docs/source/examples/ucx.rst b/docs/source/examples/ucx.rst
index 6230caf67..18c569ff1 100644
--- a/docs/source/examples/ucx.rst
+++ b/docs/source/examples/ucx.rst
@@ -69,7 +69,7 @@ To start a Dask scheduler using UCX with automatic configuration and one GB of R
 .. note::
     The ``interface="ib0"`` is intentionally specified above to ensure RDMACM is used in systems that support InfiniBand. On systems that don't support InfiniBand or where RDMACM isn't required, the ``interface`` argument may be omitted or specified to listen on a different interface.
 
-    We specify ``UCX_MEMTYPE_REG_WHOLE_ALLOC_TYPES=cuda`` above for optimal performance with InfiniBand, see details `here <https://ucx-py.readthedocs.io/en/latest/configuration.html#ucx-memtype-reg-whole-alloc-types>`_. If not using InfiniBand, that option may be omitted. In UCX 1.12 and newer, that option is default and may be omitted as well even when using InfiniBand.
+    We specify ``UCX_MEMTYPE_REG_WHOLE_ALLOC_TYPES=cuda`` above for optimal performance with InfiniBand, see details `here <https://ucx-py.readthedocs.io/en/latest/configuration.html#ucx-memtype-reg-whole-alloc-types>`__. If not using InfiniBand, that option may be omitted. In UCX 1.12 and newer, that option is default and may be omitted as well even when using InfiniBand.
 
 Workers
 ^^^^^^^
@@ -86,7 +86,7 @@ To start workers with automatic UCX configuration and an RMM pool of 14GB per GP
 .. note::
     Analogous to the scheduler setup, the ``interface="ib0"`` is intentionally specified above to ensure RDMACM is used in systems that support InfiniBand. On systems that don't support InfiniBand or where RDMACM isn't required, the ``interface`` argument may be omitted or specified to listen on a different interface.
 
-    We specify ``UCX_MEMTYPE_REG_WHOLE_ALLOC_TYPES=cuda`` above for optimal performance with InfiniBand, see details `here <https://ucx-py.readthedocs.io/en/latest/configuration.html#ucx-memtype-reg-whole-alloc-types>`_. If not using InfiniBand, that option may be omitted. In UCX 1.12 and newer, that option is default and may be omitted as well even when using InfiniBand.
+    We specify ``UCX_MEMTYPE_REG_WHOLE_ALLOC_TYPES=cuda`` above for optimal performance with InfiniBand, see details `here <https://ucx-py.readthedocs.io/en/latest/configuration.html#ucx-memtype-reg-whole-alloc-types>`__. If not using InfiniBand, that option may be omitted. In UCX 1.12 and newer, that option is default and may be omitted as well even when using InfiniBand.
 
 Client
 ^^^^^^
@@ -122,7 +122,7 @@ Alternatively, the ``with dask.config.set`` statement from the example above may
     We specify ``UCX_MEMTYPE_REG_WHOLE_ALLOC_TYPES=cuda`` above for optimal performance with InfiniBand, see details `here <https://ucx-py.readthedocs.io/en/latest/configuration.html#ucx-memtype-reg-whole-alloc-types>`_. If not using InfiniBand, that option may be omitted. In UCX 1.12 and newer, that option is default and may be omitted as well even when using InfiniBand.
 
 ``dask cuda worker`` with Manual Configuration
-------------------------------------------
+----------------------------------------------
 
 When using ``dask cuda worker`` with UCX communication and manual configuration, the scheduler, workers, and client must all be started manually, each using the same UCX configuration.
 
diff --git a/docs/source/quickstart.rst b/docs/source/quickstart.rst
index c5592b439..c42bd4837 100644
--- a/docs/source/quickstart.rst
+++ b/docs/source/quickstart.rst
@@ -16,6 +16,10 @@ To create a Dask-CUDA cluster using all available GPUs and connect a Dask.distri
     cluster = LocalCUDACluster()
     client = Client(cluster)
 
+.. tip::
+
+   Be sure to include an ``if __name__ == "__main__":`` block when using :py:class:`dask_cuda.LocalCUDACluster` in a standalone Python script. See `standalone Python scripts <https://docs.dask.org/en/stable/scheduling.html#standalone-python-scripts>`_ for more details.
+
 ``dask cuda worker``
 --------------------