diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index 53edd056a6802..173ff99912f05 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -1084,6 +1084,7 @@ def blk_func(bvalues: ArrayLike) -> ArrayLike:
                     assert how == "ohlc"
                     raise
 
+                # We get here with a) EADtypes and b) object dtype
                 obj: Union[Series, DataFrame]
                 # call our grouper again with only this block
                 if isinstance(bvalues, ExtensionArray):
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 651af2d314251..6ef2e67030881 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1012,6 +1012,8 @@ def _agg_general(
                     # raised in _get_cython_function, in some cases can
                     #  be trimmed by implementing cython funcs for more dtypes
                     pass
+                else:
+                    raise
 
             # apply a non-cython aggregation
             result = self.aggregate(lambda x: npfunc(x, axis=self.axis))
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index c076b6e2e181b..e9525f03368fa 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -601,7 +601,7 @@ def _transform(
 
         return result
 
-    def agg_series(self, obj: Series, func: F, *args, **kwargs):
+    def agg_series(self, obj: Series, func: F):
         # Caller is responsible for checking ngroups != 0
         assert self.ngroups != 0
 
@@ -649,7 +649,7 @@ def _aggregate_series_fast(self, obj: Series, func: F):
         result, counts = grouper.get_result()
         return result, counts
 
-    def _aggregate_series_pure_python(self, obj: Series, func: F, *args, **kwargs):
+    def _aggregate_series_pure_python(self, obj: Series, func: F):
         group_index, _, ngroups = self.group_info
 
         counts = np.zeros(ngroups, dtype=int)
@@ -658,7 +658,7 @@ def _aggregate_series_pure_python(self, obj: Series, func: F, *args, **kwargs):
         splitter = get_splitter(obj, group_index, ngroups, axis=0)
 
         for label, group in splitter:
-            res = func(group, *args, **kwargs)
+            res = func(group)
 
             if result is None:
                 if isinstance(res, (Series, Index, np.ndarray)):
@@ -835,7 +835,7 @@ def groupings(self) -> "List[grouper.Grouping]":
             for lvl, name in zip(self.levels, self.names)
         ]
 
-    def agg_series(self, obj: Series, func: F, *args, **kwargs):
+    def agg_series(self, obj: Series, func: F):
         # Caller is responsible for checking ngroups != 0
         assert self.ngroups != 0
         assert len(self.bins) > 0  # otherwise we'd get IndexError in get_result