diff --git a/bigframes/core/validations.py b/bigframes/core/validations.py
index 9c03ddb930..daa1252824 100644
--- a/bigframes/core/validations.py
+++ b/bigframes/core/validations.py
@@ -17,7 +17,7 @@
 from __future__ import annotations
 
 import functools
-from typing import Optional, Protocol, TYPE_CHECKING
+from typing import Optional, Protocol, TYPE_CHECKING, Union
 
 import bigframes.constants
 import bigframes.exceptions
@@ -25,6 +25,8 @@
 if TYPE_CHECKING:
     from bigframes import Session
     from bigframes.core.blocks import Block
+    from bigframes.dataframe import DataFrame
+    from bigframes.operations.base import SeriesMethods
 
 
 class HasSession(Protocol):
@@ -37,6 +39,16 @@ def _block(self) -> Block:
         ...
 
 
+def requires_index(meth):
+    @functools.wraps(meth)
+    def guarded_meth(df: Union[DataFrame, SeriesMethods], *args, **kwargs):
+        df._throw_if_null_index(meth.__name__)
+        return meth(df, *args, **kwargs)
+
+    guarded_meth._validations_requires_index = True  # type: ignore
+    return guarded_meth
+
+
 def requires_ordering(suggestion: Optional[str] = None):
     def decorator(meth):
         @functools.wraps(meth)
@@ -44,6 +56,7 @@ def guarded_meth(object: HasSession, *args, **kwargs):
             enforce_ordered(object, meth.__name__, suggestion)
             return meth(object, *args, **kwargs)
 
+        guarded_meth._validations_requires_ordering = True  # type: ignore
         return guarded_meth
 
     return decorator
diff --git a/bigframes/dataframe.py b/bigframes/dataframe.py
index dabe85c923..a174ef0b0f 100644
--- a/bigframes/dataframe.py
+++ b/bigframes/dataframe.py
@@ -17,7 +17,6 @@
 from __future__ import annotations
 
 import datetime
-import functools
 import inspect
 import re
 import sys
@@ -92,15 +91,6 @@
 )
 
 
-def requires_index(meth):
-    @functools.wraps(meth)
-    def guarded_meth(df: DataFrame, *args, **kwargs):
-        df._throw_if_null_index(meth.__name__)
-        return meth(df, *args, **kwargs)
-
-    return guarded_meth
-
-
 # Inherits from pandas DataFrame so that we can use the same docstrings.
 @log_adapter.class_logger
 class DataFrame(vendored_pandas_frame.DataFrame):
@@ -261,7 +251,7 @@ def _sql_names(
         return results
 
     @property
-    @requires_index
+    @validations.requires_index
     def index(
         self,
     ) -> indexes.Index:
@@ -277,7 +267,7 @@ def index(self, value):
         self.index.name = value.name if hasattr(value, "name") else None
 
     @property
-    @requires_index
+    @validations.requires_index
     def loc(self) -> indexers.LocDataFrameIndexer:
         return indexers.LocDataFrameIndexer(self)
 
@@ -292,7 +282,7 @@ def iat(self) -> indexers.IatDataFrameIndexer:
         return indexers.IatDataFrameIndexer(self)
 
     @property
-    @requires_index
+    @validations.requires_index
     def at(self) -> indexers.AtDataFrameIndexer:
         return indexers.AtDataFrameIndexer(self)
 
@@ -348,7 +338,7 @@ def _has_index(self) -> bool:
     def T(self) -> DataFrame:
         return DataFrame(self._get_block().transpose())
 
-    @requires_index
+    @validations.requires_index
     @validations.requires_ordering()
     def transpose(self) -> DataFrame:
         return self.T
@@ -417,7 +407,7 @@ def memory_usage(self, index: bool = True):
             column_sizes = pandas.concat([index_size, column_sizes])
         return column_sizes
 
-    @requires_index
+    @validations.requires_index
     def info(
         self,
         verbose: Optional[bool] = None,
@@ -1682,7 +1672,7 @@ def set_index(
         col_ids_strs: List[str] = [col_id for col_id in col_ids if col_id is not None]
         return DataFrame(self._block.set_index(col_ids_strs, append=append, drop=drop))
 
-    @requires_index
+    @validations.requires_index
     def sort_index(
         self, ascending: bool = True, na_position: Literal["first", "last"] = "last"
     ) -> DataFrame:
@@ -1884,7 +1874,7 @@ def reindex(
         if columns is not None:
             return self._reindex_columns(columns)
 
-    @requires_index
+    @validations.requires_index
     def _reindex_rows(
         self,
         index,
@@ -1931,12 +1921,12 @@ def _reindex_columns(self, columns):
         result_df.columns = new_column_index
         return result_df
 
-    @requires_index
+    @validations.requires_index
     def reindex_like(self, other: DataFrame, *, validate: typing.Optional[bool] = None):
         return self.reindex(index=other.index, columns=other.columns, validate=validate)
 
     @validations.requires_ordering()
-    @requires_index
+    @validations.requires_index
     def interpolate(self, method: str = "linear") -> DataFrame:
         if method == "pad":
             return self.ffill()
@@ -2231,12 +2221,12 @@ def agg(
     aggregate = agg
     aggregate.__doc__ = inspect.getdoc(vendored_pandas_frame.DataFrame.agg)
 
-    @requires_index
+    @validations.requires_index
     @validations.requires_ordering()
     def idxmin(self) -> bigframes.series.Series:
         return bigframes.series.Series(block_ops.idxmin(self._block))
 
-    @requires_index
+    @validations.requires_index
     @validations.requires_ordering()
     def idxmax(self) -> bigframes.series.Series:
         return bigframes.series.Series(block_ops.idxmax(self._block))
@@ -2345,7 +2335,7 @@ def _pivot(
         )
         return DataFrame(pivot_block)
 
-    @requires_index
+    @validations.requires_index
     @validations.requires_ordering()
     def pivot(
         self,
@@ -2360,7 +2350,7 @@ def pivot(
     ) -> DataFrame:
         return self._pivot(columns=columns, index=index, values=values)
 
-    @requires_index
+    @validations.requires_index
     @validations.requires_ordering()
     def pivot_table(
         self,
@@ -2460,7 +2450,7 @@ def _stack_multi(self, level: LevelsType = -1):
         block = block.stack(levels=len(level))
         return DataFrame(block)
 
-    @requires_index
+    @validations.requires_index
     @validations.requires_ordering()
     def unstack(self, level: LevelsType = -1):
         if not utils.is_list_like(level):
@@ -2711,7 +2701,7 @@ def groupby(
         else:
             raise TypeError("You have to supply one of 'by' and 'level'")
 
-    @requires_index
+    @validations.requires_index
     def _groupby_level(
         self,
         level: LevelsType,
diff --git a/bigframes/operations/base.py b/bigframes/operations/base.py
index f339345971..1daa1ea5ae 100644
--- a/bigframes/operations/base.py
+++ b/bigframes/operations/base.py
@@ -14,7 +14,6 @@
 
 from __future__ import annotations
 
-import functools
 import typing
 from typing import List, Sequence
 
@@ -35,15 +34,6 @@
 import bigframes.session
 
 
-def requires_index(meth):
-    @functools.wraps(meth)
-    def guarded_meth(df: SeriesMethods, *args, **kwargs):
-        df._throw_if_null_index(meth.__name__)
-        return meth(df, *args, **kwargs)
-
-    return guarded_meth
-
-
 class SeriesMethods:
     def __init__(
         self,
diff --git a/bigframes/series.py b/bigframes/series.py
index 7ba4858b5e..c2137bca35 100644
--- a/bigframes/series.py
+++ b/bigframes/series.py
@@ -52,7 +52,6 @@
 import bigframes.operations as ops
 import bigframes.operations.aggregations as agg_ops
 import bigframes.operations.base
-from bigframes.operations.base import requires_index
 import bigframes.operations.datetimes as dt
 import bigframes.operations.plotting as plotting
 import bigframes.operations.strings as strings
@@ -88,7 +87,7 @@ def dtypes(self):
         return self._dtype
 
     @property
-    @requires_index
+    @validations.requires_index
     def loc(self) -> bigframes.core.indexers.LocSeriesIndexer:
         return bigframes.core.indexers.LocSeriesIndexer(self)
 
@@ -103,7 +102,7 @@ def iat(self) -> bigframes.core.indexers.IatSeriesIndexer:
         return bigframes.core.indexers.IatSeriesIndexer(self)
 
     @property
-    @requires_index
+    @validations.requires_index
     def at(self) -> bigframes.core.indexers.AtSeriesIndexer:
         return bigframes.core.indexers.AtSeriesIndexer(self)
 
@@ -142,7 +141,7 @@ def values(self) -> numpy.ndarray:
         return self.to_numpy()
 
     @property
-    @requires_index
+    @validations.requires_index
     def index(self) -> indexes.Index:
         return indexes.Index.from_frame(self)
 
@@ -245,7 +244,7 @@ def rename(
 
         raise ValueError(f"Unsupported type of parameter index: {type(index)}")
 
-    @requires_index
+    @validations.requires_index
     def rename_axis(
         self,
         mapper: typing.Union[blocks.Label, typing.Sequence[blocks.Label]],
@@ -404,12 +403,12 @@ def drop(
         block = block.drop_columns([condition_id])
         return Series(block.select_column(self._value_column))
 
-    @requires_index
+    @validations.requires_index
     def droplevel(self, level: LevelsType, axis: int | str = 0):
         resolved_level_ids = self._resolve_levels(level)
         return Series(self._block.drop_levels(resolved_level_ids))
 
-    @requires_index
+    @validations.requires_index
     def swaplevel(self, i: int = -2, j: int = -1):
         level_i = self._block.index_columns[i]
         level_j = self._block.index_columns[j]
@@ -419,7 +418,7 @@ def swaplevel(self, i: int = -2, j: int = -1):
         ]
         return Series(self._block.reorder_levels(reordering))
 
-    @requires_index
+    @validations.requires_index
     def reorder_levels(self, order: LevelsType, axis: int | str = 0):
         resolved_level_ids = self._resolve_levels(order)
         return Series(self._block.reorder_levels(resolved_level_ids))
@@ -609,7 +608,7 @@ def _mapping_replace(self, mapping: dict[typing.Hashable, typing.Hashable]):
         return Series(block.select_column(result))
 
     @validations.requires_ordering()
-    @requires_index
+    @validations.requires_index
     def interpolate(self, method: str = "linear") -> Series:
         if method == "pad":
             return self.ffill()
@@ -1162,7 +1161,7 @@ def argmin(self) -> int:
             scalars.Scalar, Series(block.select_column(row_nums)).iloc[0]
         )
 
-    @requires_index
+    @validations.requires_index
     def unstack(self, level: LevelsType = -1):
         if isinstance(level, int) or isinstance(level, str):
             level = [level]
@@ -1186,7 +1185,7 @@ def unstack(self, level: LevelsType = -1):
         )
         return bigframes.dataframe.DataFrame(pivot_block)
 
-    @requires_index
+    @validations.requires_index
     def idxmax(self) -> blocks.Label:
         block = self._block.order_by(
             [
@@ -1200,7 +1199,7 @@ def idxmax(self) -> blocks.Label:
         block = block.slice(0, 1)
         return indexes.Index(block).to_pandas()[0]
 
-    @requires_index
+    @validations.requires_index
     def idxmin(self) -> blocks.Label:
         block = self._block.order_by(
             [
@@ -1314,7 +1313,7 @@ def sort_values(
         )
         return Series(block)
 
-    @requires_index
+    @validations.requires_index
     def sort_index(self, *, axis=0, ascending=True, na_position="last") -> Series:
         # TODO(tbergeron): Support level parameter once multi-index introduced.
         if na_position not in ["first", "last"]:
@@ -1377,7 +1376,7 @@ def groupby(
         else:
             raise TypeError("You have to supply one of 'by' and 'level'")
 
-    @requires_index
+    @validations.requires_index
     def _groupby_level(
         self,
         level: int | str | typing.Sequence[int] | typing.Sequence[str],
@@ -1518,11 +1517,11 @@ def combine(
         materialized_series = result_series._cached()
         return materialized_series
 
-    @requires_index
+    @validations.requires_index
     def add_prefix(self, prefix: str, axis: int | str | None = None) -> Series:
         return Series(self._get_block().add_prefix(prefix))
 
-    @requires_index
+    @validations.requires_index
     def add_suffix(self, suffix: str, axis: int | str | None = None) -> Series:
         return Series(self._get_block().add_suffix(suffix))
 
@@ -1574,7 +1573,7 @@ def filter(
         else:
             raise ValueError("Need to provide 'items', 'like', or 'regex'")
 
-    @requires_index
+    @validations.requires_index
     def reindex(self, index=None, *, validate: typing.Optional[bool] = None):
         if validate and not self.index.is_unique:
             raise ValueError("Original index must be unique to reindex")
@@ -1603,7 +1602,7 @@ def reindex(self, index=None, *, validate: typing.Optional[bool] = None):
         )._block
         return Series(result_block)
 
-    @requires_index
+    @validations.requires_index
     def reindex_like(self, other: Series, *, validate: typing.Optional[bool] = None):
         return self.reindex(other.index, validate=validate)
 
diff --git a/scripts/publish_api_coverage.py b/scripts/publish_api_coverage.py
index 25fbfbf988..0292d4880d 100644
--- a/scripts/publish_api_coverage.py
+++ b/scripts/publish_api_coverage.py
@@ -116,7 +116,15 @@ def generate_pandas_api_coverage():
     """Inspect all our pandas objects, and compare with the real pandas objects, to see
     which methods we implement. For each, generate a regex that can be used to check if
     its present in a notebook"""
-    header = ["api", "pattern", "kind", "is_in_bigframes", "missing_parameters"]
+    header = [
+        "api",
+        "pattern",
+        "kind",
+        "is_in_bigframes",
+        "missing_parameters",
+        "requires_index",
+        "requires_ordering",
+    ]
     api_patterns = []
     indexers = ["loc", "iloc", "iat", "ix", "at"]
     for name, pandas_obj, bigframes_obj in PANDAS_TARGETS:
@@ -156,6 +164,13 @@ def generate_pandas_api_coverage():
                 token_type = "property"
 
             is_in_bigframes = hasattr(bigframes_obj, member)
+            requires_index = False
+            requires_ordering = False
+
+            if is_in_bigframes:
+                attr = getattr(bigframes_obj, member)
+                requires_index = hasattr(attr, "_validations_requires_index")
+                requires_ordering = hasattr(attr, "_validations_requires_ordering")
 
             api_patterns.append(
                 [
@@ -164,6 +179,8 @@ def generate_pandas_api_coverage():
                     token_type,
                     is_in_bigframes,
                     missing_parameters,
+                    requires_index,
+                    requires_ordering,
                 ]
             )
 
@@ -287,6 +304,7 @@ def generate_api_coverage(df, api_prefix):
         dataframe_apis["missing_parameters"].str.len() != 0
     ) & dataframe_apis["is_in_bigframes"]
     not_implemented = ~dataframe_apis["is_in_bigframes"]
+
     dataframe_table = pd.DataFrame(
         {
             "API": format_api(
@@ -295,12 +313,16 @@ def generate_api_coverage(df, api_prefix):
                 api_prefix,
             ),
             "Implemented": "",
+            "Requires index": "",
+            "Requires ordering": "",
             "Missing parameters": dataframe_apis["missing_parameters"],
         }
     )
     dataframe_table.loc[fully_implemented, "Implemented"] = "Y"
     dataframe_table.loc[partial_implemented, "Implemented"] = "P"
     dataframe_table.loc[not_implemented, "Implemented"] = "N"
+    dataframe_table.loc[dataframe_apis["requires_index"], "Requires index"] = "Y"
+    dataframe_table.loc[dataframe_apis["requires_ordering"], "Requires ordering"] = "Y"
     return dataframe_table