diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index b50d6f56..23d9b2ea 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -29,6 +29,7 @@ jobs:
     strategy:
       matrix:
         python-version: ["3.11", "3.12"]
+    timeout-minutes: 30
     steps:
       - uses: actions/checkout@v4
 
diff --git a/.github/workflows/min-deps.yml b/.github/workflows/min-deps.yml
index c236a9ef..c1e13c78 100644
--- a/.github/workflows/min-deps.yml
+++ b/.github/workflows/min-deps.yml
@@ -29,6 +29,7 @@ jobs:
     strategy:
       matrix:
         python-version: ["3.12"]
+    timeout-minutes: 30
     steps:
       - uses: actions/checkout@v4
 
diff --git a/.github/workflows/upstream.yml b/.github/workflows/upstream.yml
index 74867ea5..e07e5163 100644
--- a/.github/workflows/upstream.yml
+++ b/.github/workflows/upstream.yml
@@ -29,6 +29,7 @@ jobs:
     strategy:
       matrix:
         python-version: ["3.12"]
+    timeout-minutes: 30
     steps:
       - uses: actions/checkout@v4
 
diff --git a/conftest.py b/conftest.py
index 0781c37e..2e8fc73a 100644
--- a/conftest.py
+++ b/conftest.py
@@ -103,7 +103,11 @@ def netcdf4_virtual_dataset(netcdf4_file):
 def netcdf4_inlined_ref(netcdf4_file):
     from kerchunk.hdf import SingleHdf5ToZarr
 
-    return SingleHdf5ToZarr(netcdf4_file, inline_threshold=1000).translate()
+    return SingleHdf5ToZarr(
+        netcdf4_file,
+        inline_threshold=1000,
+        storage_options={"use_listings_cache": False},
+    ).translate()
 
 
 @pytest.fixture
diff --git a/virtualizarr/tests/test_readers/conftest.py b/virtualizarr/tests/test_readers/conftest.py
index 4884db4a..9f3e20af 100644
--- a/virtualizarr/tests/test_readers/conftest.py
+++ b/virtualizarr/tests/test_readers/conftest.py
@@ -372,18 +372,22 @@ def scalar_fill_value_hdf5_file(tmpdir):
 compound_fill = (-9999, -9999.0)
 
 fill_values = [
-    {"fill_value": -9999, "data": np.random.randint(0, 10, size=(5))},
-    {"fill_value": -9999.0, "data": np.random.random(5)},
-    {"fill_value": np.nan, "data": np.random.random(5)},
-    {"fill_value": False, "data": np.array([True, False, False, True, True])},
-    {"fill_value": "NaN", "data": np.array(["three"], dtype="S10")},
-    {"fill_value": compound_fill, "data": compound_data},
+    {"label": "int", "fill_value": -9999, "data": np.random.randint(0, 10, size=(5))},
+    {"label": "float", "fill_value": -9999.0, "data": np.random.random(5)},
+    {"label": "npNan", "fill_value": np.nan, "data": np.random.random(5)},
+    {
+        "label": "False",
+        "fill_value": False,
+        "data": np.array([True, False, False, True, True]),
+    },
+    {"label": "NaN", "fill_value": "NaN", "data": np.array(["three"], dtype="S10")},
+    {"label": "compound", "fill_value": compound_fill, "data": compound_data},
 ]
 
 
 @pytest.fixture(params=fill_values)
 def cf_fill_value_hdf5_file(tmpdir, request):
-    filepath = f"{tmpdir}/cf_fill_value.nc"
+    filepath = tmpdir / f"cf_fill_value_{request.param['label']}.nc"
     f = h5py.File(filepath, "w")
     dset = f.create_dataset(name="data", data=request.param["data"], chunks=True)
     dim_scale = f.create_dataset(