diff --git a/algorithm_catalog/max_ndvi_composite_files/max_ndvi_composite_description.md b/algorithm_catalog/max_ndvi_composite_files/max_ndvi_composite_description.md
index a64ece7..33c3f05 100644
--- a/algorithm_catalog/max_ndvi_composite_files/max_ndvi_composite_description.md
+++ b/algorithm_catalog/max_ndvi_composite_files/max_ndvi_composite_description.md
@@ -10,7 +10,7 @@ which leads to visual discontinuities in the result.
 
 # Performance characteristics
 
-The method is computationally efficient, as it only requires the B04, B08 and SCL bands to determine the rank score. Loading 
+The method is computationally efficient, as it only requires the B04, B08 and SCL bands to determine the rank score. Loading
 of other bands can be minimized to read only selected observations.
 
 
@@ -33,7 +33,7 @@ https://radiantearth.github.io/stac-browser/#/external/s3.waw3-1.cloudferro.com/
 The processing platform reported these usage statistics for the example:
 
 ```
-Credits: 63 
+Credits: 63
 CPU usage: 47.743,722 cpu-seconds
 Wall time: 1.948 seconds
 Input Pixel 10.997,635 mega-pixel
@@ -75,8 +75,8 @@ https://www.nature.com/articles/s43016-021-00429-z
 
 # Known limitations
 
-The method uses a vegetation index as scoring metric to determine the best pixel, making it only suitable for land applications. 
-Bare or urban areas may not be well represented in the composite. 
+The method uses a vegetation index as scoring metric to determine the best pixel, making it only suitable for land applications.
+Bare or urban areas may not be well represented in the composite.
 
 It favours the observation which is least contaminated by atmospheric effects, but does not guarantee a fully uncontaminated composite.
 
@@ -92,4 +92,4 @@ Artifacts are expected over water and urban areas.
 Residual cloud artifacts may be present in the composite, especially for smaller time windows or during cloudy seasons.
 The cloud artifacts are caused by the limited capabilities of the default Sentinel-2 cloud detection mechanism to correctly identify all clouds.
 
-![max_ndvi_cloud_artifacts.png](max_ndvi_composite_files/max_ndvi_cloud_artifacts.png)
\ No newline at end of file
+![max_ndvi_cloud_artifacts.png](max_ndvi_composite_files/max_ndvi_cloud_artifacts.png)
diff --git a/openeo_udp/examples/max_ndvi_composite/generate.py b/openeo_udp/examples/max_ndvi_composite/generate.py
index 5a34e5c..79b3ad8 100644
--- a/openeo_udp/examples/max_ndvi_composite/generate.py
+++ b/openeo_udp/examples/max_ndvi_composite/generate.py
@@ -31,9 +31,9 @@ def generate() -> dict:
     )
 
     max_cloud_description = """The maximum cloud cover percentage to filter Sentinel-2 inputs at full product level.
-    By reducing the percentage, fewer input products are considered, which also potentially increases the risk of missing valid data.  
+    By reducing the percentage, fewer input products are considered, which also potentially increases the risk of missing valid data.
     We do not recommend setting it higher than 95%, as this decreases performance by reading very cloudy areas with little chance of finding good pixels.
-    
+
     For composites over large time ranges, a reduced value can help to consider only good quality input products, with few undetected clouds.
     """
     max_cloud_cover_param = Parameter.number(