diff --git a/hamilton/function_modifiers/recursive.py b/hamilton/function_modifiers/recursive.py
index f0b283955..0dd41b09e 100644
--- a/hamilton/function_modifiers/recursive.py
+++ b/hamilton/function_modifiers/recursive.py
@@ -803,12 +803,11 @@ def __init__(
         # We can decouple it so that on_input selects the target dataframe parameter that will inject into the next node
         # pass_dataframe_as selects the original dataframe we want to extract columns from
         # columns_to_pass is optinal helper that can be toggled on/off so no need to raise this error.
-        if (
-            int(pass_dataframe_as is None) + int(columns_to_pass is None) + int(on_input is None)
-            == 1
-        ):
+        n_set = sum(arg is not None for arg in (pass_dataframe_as, columns_to_pass, on_input))
+        if n_set != 1:
             raise ValueError(
-                "You must specify only one of ``columns_to_pass``, ``pass_dataframe_as``, and ``on_input``. "
+                "You must specify exactly one of ``columns_to_pass``, ``pass_dataframe_as``, "
+                "and ``on_input``. "
                 "This is because specifying ``pass_dataframe_as`` or ``on_input`` injects into "
                 "the set of columns, allowing you to perform your own extraction"
                 "from the dataframe. We then execute all columns in the subdag"
diff --git a/tests/function_modifiers/test_recursive.py b/tests/function_modifiers/test_recursive.py
index 282b37607..a40b38a4d 100644
--- a/tests/function_modifiers/test_recursive.py
+++ b/tests/function_modifiers/test_recursive.py
@@ -687,3 +687,54 @@ def test_columns_and_subdag_nodes_do_not_clash():
 
     assert not with_columns_base.contains_duplicates([node_a, node_c])
     assert with_columns_base.contains_duplicates([node_a, node_b, node_c])
+
+
+class _BaseValidationSub(with_columns_base):
+    """Minimal concrete subclass used to exercise `with_columns_base.__init__`-time
+    validation. The abstract methods are trivially stubbed because no test in this
+    block invokes them.
+    """
+
+    def get_initial_nodes(self, fn, params):
+        return "", []
+
+    def get_subdag_nodes(self, fn, config):
+        return []
+
+    def chain_subdag_nodes(self, fn, inject_parameter, generated_nodes):
+        return None
+
+    def validate(self, fn):
+        pass
+
+
+def _dummy_subdag_fn() -> int:
+    return 0
+
+
+def test_with_columns_base_raises_when_no_mutex_arg_set():
+    with pytest.raises(ValueError, match="exactly one of"):
+        _BaseValidationSub(_dummy_subdag_fn, select=["x"])
+
+
+def test_with_columns_base_raises_when_two_mutex_args_set():
+    with pytest.raises(ValueError, match="exactly one of"):
+        _BaseValidationSub(_dummy_subdag_fn, columns_to_pass=["a"], on_input="b", select=["x"])
+
+
+def test_with_columns_base_raises_when_all_three_mutex_args_set():
+    with pytest.raises(ValueError, match="exactly one of"):
+        _BaseValidationSub(
+            _dummy_subdag_fn,
+            columns_to_pass=["a"],
+            pass_dataframe_as="b",
+            on_input="c",
+            select=["x"],
+        )
+
+
+def test_with_columns_base_accepts_exactly_one_mutex_arg():
+    # Each of the three single-set cases must instantiate cleanly.
+    _BaseValidationSub(_dummy_subdag_fn, columns_to_pass=["a"], select=["x"], dataframe_type=object)
+    _BaseValidationSub(_dummy_subdag_fn, pass_dataframe_as="b", select=["x"], dataframe_type=object)
+    _BaseValidationSub(_dummy_subdag_fn, on_input="c", select=["x"], dataframe_type=object)