diff --git a/iohub/ngff/utils.py b/iohub/ngff/utils.py
index 11621fc5..e1f50d85 100644
--- a/iohub/ngff/utils.py
+++ b/iohub/ngff/utils.py
@@ -4,7 +4,15 @@
 from collections import defaultdict
 from functools import partial
 from pathlib import Path
-from typing import Any, Callable, Literal, Sequence, Union
+from typing import (
+    Any,
+    Callable,
+    Literal,
+    Protocol,
+    Sequence,
+    Union,
+    runtime_checkable,
+)
 from warnings import warn
 
 import click
@@ -147,9 +155,48 @@ def create_empty_plate(
             if channel_name not in metadata_channel_names:
                 position.append_channel(channel_name, resize_arrays=True)
 
+@runtime_checkable
+class TransformFunction(Protocol):
+    def __call__(
+        self, 
+        data: NDArray, 
+        input_time_index: int | None = None,
+        **kwargs: Any
+    ) -> NDArray:
+        """Transform image data. 
+        
+        The function must take the CZYX or TCZYX NDArray as the first argument and return a CZYX or TCZYX NDArray. 
+        Additional arguments are passed through **kwargs.
+        
+        Parameters
+        ----------
+        data : NDArray
+            CZYX or TCZYX image data to transform
+        input_time_index : int, optional
+            Time index for time-dependent transformations. Defaults to None.
+        **kwargs
+            Additional transformation parameters
+            
+        Returns
+        -------
+        NDArray
+            Transformed data with same shape as input.
+        
+		Examples
+		--------
+        Double the Array
+		>>> def double(data: NDArray, **kwargs) -> NDArray:
+		...     return data * 2
+        Apply Gaussian blur on the Array
+        >>> def gaussian_blur(data: NDArray, **kwargs) -> NDArray:
+        ...     from skimage.filters import gaussian
+        ...     return gaussian(data, **kwargs)
+        """
+        ...
+
 
 def _apply_transform_to_czyx(
-    func: Callable[[NDArray, Any], NDArray],
+    func: TransformFunction,
     input_position_path: Path,
     input_channel_indices: Union[list[int], slice],
     input_time_index: int,
@@ -208,7 +255,7 @@ def _save_transformed(
 
 
 def apply_transform_to_czyx_and_save(
-    func: Callable[[NDArray, Any], NDArray],
+    func: TransformFunction,
     input_position_path: Path,
     output_position_path: Path,
     input_channel_indices: Union[list[int], slice],
@@ -225,7 +272,7 @@ def apply_transform_to_czyx_and_save(
 
     Parameters
     ----------
-    func : Callable[[NDArray, Any], NDArray]
+    func : TransformFunction
         The function to be applied to the data.
         func must take the CZYX NDArray as the first argument and return
         a CZXY NDArray. Additional arguments are passed through **kwargs.
@@ -282,6 +329,7 @@ def apply_transform_to_czyx_and_save(
         input_time_index=input_time_index,
         **kwargs,
     )
+    skipped: bool = True
     if transformed is not None:
         _save_transformed(
             transformed,
@@ -289,17 +337,12 @@ def apply_transform_to_czyx_and_save(
             output_channel_indices=output_channel_indices,
             output_position_path=output_position_path,
         )
-        _echo_finished(
-            time_index=input_time_index,
-            channel_index=input_channel_indices,
-            skipped=False,
-        )
-    else:
-        _echo_finished(
-            time_index=input_time_index,
-            channel_index=input_channel_indices,
-            skipped=True,
-        )
+        skipped = False
+    _echo_finished(
+        time_index=input_time_index,
+        channel_index=input_channel_indices,
+        skipped=skipped,
+    )
 
 
 def _indices_to_shard_aligned_batches(
@@ -367,7 +410,7 @@ def _slice_to_list(indices: list[int] | slice) -> list[int]:
 
 
 def apply_transform_to_tczyx_and_save(
-    func: Callable[[NDArray, Any], NDArray],
+    func: TransformFunction,
     input_position_path: Path,
     output_position_path: Path,
     input_channel_indices: list[int] | slice,
@@ -382,7 +425,7 @@ def apply_transform_to_tczyx_and_save(
 
     Parameters
     ----------
-    func : Callable[[NDArray, Any], NDArray]
+    func : TransformFunction
         The function to be applied to the data.
         func must take the TCZYX NDArray as the first argument and return
         a TCZXY NDArray. Additional arguments are passed through **kwargs.
@@ -442,7 +485,7 @@ def apply_transform_to_tczyx_and_save(
 
 
 def process_single_position(
-    func: Callable[[NDArray, Any], NDArray],
+    func: TransformFunction,
     input_position_path: Path,
     output_position_path: Path,
     input_channel_indices: list[slice] | list[list[int]] | None = None,
@@ -459,7 +502,7 @@ def process_single_position(
 
     Parameters
     ----------
-    func : Callable[[NDArray, Any], NDArray]
+    func : TransformFunction
         The function to be applied to the data.
         func must take the CZYX NDArray as the first argument and return
         a CZXY NDArray. Additional arguments are passed through **kwargs.