diff --git a/python/nx-cugraph/nx_cugraph/algorithms/bipartite/generators.py b/python/nx-cugraph/nx_cugraph/algorithms/bipartite/generators.py
index 25b9b39554b..5a0c970c984 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/bipartite/generators.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/bipartite/generators.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -24,7 +24,7 @@
 ]
 
 
-@networkx_algorithm(nodes_or_number=[0, 1])
+@networkx_algorithm(nodes_or_number=[0, 1], version_added="23.12")
 def complete_bipartite_graph(n1, n2, create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/centrality/betweenness.py b/python/nx-cugraph/nx_cugraph/algorithms/centrality/betweenness.py
index 210e1f0a2b2..ba2b3d9c895 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/centrality/betweenness.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/centrality/betweenness.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -18,11 +18,16 @@
 __all__ = ["betweenness_centrality", "edge_betweenness_centrality"]
 
 
-@networkx_algorithm
+@networkx_algorithm(
+    is_incomplete=True,  # weight not supported
+    is_different=True,  # RNG with seed is different
+    plc="betweenness_centrality",
+    version_added="23.10",
+)
 def betweenness_centrality(
     G, k=None, normalized=True, weight=None, endpoints=False, seed=None
 ):
-    """`weight` parameter is not yet supported."""
+    """`weight` parameter is not yet supported, and RNG with seed may be different."""
     if weight is not None:
         raise NotImplementedError(
             "Weighted implementation of betweenness centrality not currently supported"
@@ -46,9 +51,14 @@ def _(G, k=None, normalized=True, weight=None, endpoints=False, seed=None):
     return weight is None
 
 
-@networkx_algorithm
+@networkx_algorithm(
+    is_incomplete=True,  # weight not supported
+    is_different=True,  # RNG with seed is different
+    plc="edge_betweenness_centrality",
+    version_added="23.10",
+)
 def edge_betweenness_centrality(G, k=None, normalized=True, weight=None, seed=None):
-    """`weight` parameter is not yet supported."""
+    """`weight` parameter is not yet supported, and RNG with seed may be different."""
     if weight is not None:
         raise NotImplementedError(
             "Weighted implementation of betweenness centrality not currently supported"
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/centrality/degree_alg.py b/python/nx-cugraph/nx_cugraph/algorithms/centrality/degree_alg.py
index 0b2fd24af79..a319eb3a12c 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/centrality/degree_alg.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/centrality/degree_alg.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -16,7 +16,7 @@
 __all__ = ["degree_centrality", "in_degree_centrality", "out_degree_centrality"]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def degree_centrality(G):
     G = _to_graph(G)
     if len(G) <= 1:
@@ -27,7 +27,7 @@ def degree_centrality(G):
 
 
 @not_implemented_for("undirected")
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def in_degree_centrality(G):
     G = _to_directed_graph(G)
     if len(G) <= 1:
@@ -38,7 +38,7 @@ def in_degree_centrality(G):
 
 
 @not_implemented_for("undirected")
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def out_degree_centrality(G):
     G = _to_directed_graph(G)
     if len(G) <= 1:
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/centrality/eigenvector.py b/python/nx-cugraph/nx_cugraph/algorithms/centrality/eigenvector.py
index c0f02a6258e..9e615955a8b 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/centrality/eigenvector.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/centrality/eigenvector.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -26,7 +26,12 @@
 
 
 @not_implemented_for("multigraph")
-@networkx_algorithm(extra_params=_dtype_param)
+@networkx_algorithm(
+    extra_params=_dtype_param,
+    is_incomplete=True,  # nstart not supported
+    plc="eigenvector_centrality",
+    version_added="23.12",
+)
 def eigenvector_centrality(
     G, max_iter=100, tol=1.0e-6, nstart=None, weight=None, *, dtype=None
 ):
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/centrality/katz.py b/python/nx-cugraph/nx_cugraph/algorithms/centrality/katz.py
index b61b811b8fa..a2fb950c1aa 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/centrality/katz.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/centrality/katz.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -26,7 +26,12 @@
 
 
 @not_implemented_for("multigraph")
-@networkx_algorithm(extra_params=_dtype_param)
+@networkx_algorithm(
+    extra_params=_dtype_param,
+    is_incomplete=True,  # nstart and normalized=False not supported
+    plc="katz_centrality",
+    version_added="23.12",
+)
 def katz_centrality(
     G,
     alpha=0.1,
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/community/louvain.py b/python/nx-cugraph/nx_cugraph/algorithms/community/louvain.py
index 936d837dacd..d023bab1a47 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/community/louvain.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/community/louvain.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -35,7 +35,11 @@
             "Upper limit of the number of macro-iterations (max: 500)."
         ),
         **_dtype_param,
-    }
+    },
+    is_incomplete=True,  # seed not supported; self-loops not supported
+    is_different=True,  # RNG different
+    plc="louvain",
+    version_added="23.10",
 )
 def louvain_communities(
     G,
@@ -47,7 +51,7 @@ def louvain_communities(
     max_level=None,
     dtype=None,
 ):
-    """`seed` parameter is currently ignored."""
+    """`seed` parameter is currently ignored, and self-loops are not yet supported."""
     # NetworkX allows both directed and undirected, but cugraph only allows undirected.
     seed = _seed_to_int(seed)  # Unused, but ensure it's valid for future compatibility
     G = _to_undirected_graph(G, weight)
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/components/connected.py b/python/nx-cugraph/nx_cugraph/algorithms/components/connected.py
index 41f3457d542..cb12aed1d39 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/components/connected.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/components/connected.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -30,7 +30,7 @@
 
 
 @not_implemented_for("directed")
-@networkx_algorithm
+@networkx_algorithm(plc="weakly_connected_components", version_added="23.12")
 def number_connected_components(G):
     return sum(1 for _ in connected_components(G))
     # PREFERRED IMPLEMENTATION, BUT PLC DOES NOT HANDLE ISOLATED VERTICES WELL
@@ -57,7 +57,7 @@ def _(G):
 
 
 @not_implemented_for("directed")
-@networkx_algorithm
+@networkx_algorithm(plc="weakly_connected_components", version_added="23.12")
 def connected_components(G):
     G = _to_undirected_graph(G)
     if G.src_indices.size == 0:
@@ -86,7 +86,7 @@ def connected_components(G):
 
 
 @not_implemented_for("directed")
-@networkx_algorithm
+@networkx_algorithm(plc="weakly_connected_components", version_added="23.12")
 def is_connected(G):
     G = _to_undirected_graph(G)
     if len(G) == 0:
@@ -110,7 +110,7 @@ def is_connected(G):
 
 
 @not_implemented_for("directed")
-@networkx_algorithm
+@networkx_algorithm(plc="weakly_connected_components", version_added="23.12")
 def node_connected_component(G, n):
     # We could also do plain BFS from n
     G = _to_undirected_graph(G)
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/core.py b/python/nx-cugraph/nx_cugraph/algorithms/core.py
index c00df2d832f..e4520c2713b 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/core.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/core.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -27,7 +27,7 @@
 
 @not_implemented_for("directed")
 @not_implemented_for("multigraph")
-@networkx_algorithm
+@networkx_algorithm(is_incomplete=True, plc="k_truss_subgraph", version_added="23.12")
 def k_truss(G, k):
     """
     Currently raises `NotImplementedError` for graphs with more than one connected
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/dag.py b/python/nx-cugraph/nx_cugraph/algorithms/dag.py
index 067cfed9101..ad5b7594aa1 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/dag.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/dag.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -45,11 +45,11 @@ def _ancestors_and_descendants(G, source, *, is_ancestors):
     return G._nodearray_to_set(node_ids[mask])
 
 
-@networkx_algorithm
+@networkx_algorithm(plc="bfs", version_added="24.02")
 def descendants(G, source):
     return _ancestors_and_descendants(G, source, is_ancestors=False)
 
 
-@networkx_algorithm
+@networkx_algorithm(plc="bfs", version_added="24.02")
 def ancestors(G, source):
     return _ancestors_and_descendants(G, source, is_ancestors=True)
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/isolate.py b/python/nx-cugraph/nx_cugraph/algorithms/isolate.py
index d32223fb3ed..c7e5d7113de 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/isolate.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/isolate.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -25,7 +25,7 @@
 __all__ = ["is_isolate", "isolates", "number_of_isolates"]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.10")
 def is_isolate(G, n):
     G = _to_graph(G)
     index = n if G.key_to_id is None else G.key_to_id[n]
@@ -51,13 +51,13 @@ def _isolates(G) -> cp.ndarray[IndexValue]:
     return cp.nonzero(_mark_isolates(G))[0]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.10")
 def isolates(G):
     G = _to_graph(G)
     return G._nodeiter_to_iter(iter(_isolates(G).tolist()))
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.10")
 def number_of_isolates(G):
     G = _to_graph(G)
     return _mark_isolates(G).sum().tolist()
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/hits_alg.py b/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/hits_alg.py
index 1c8a47c24b1..caa01327a56 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/hits_alg.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/hits_alg.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -32,7 +32,9 @@
             "The edge attribute to use as the edge weight."
         ),
         **_dtype_param,
-    }
+    },
+    plc="hits",
+    version_added="23.12",
 )
 def hits(
     G,
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/pagerank_alg.py b/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/pagerank_alg.py
index 63f6e89c33a..d45d019c1b7 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/pagerank_alg.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/link_analysis/pagerank_alg.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -26,7 +26,12 @@
 __all__ = ["pagerank"]
 
 
-@networkx_algorithm(extra_params=_dtype_param)
+@networkx_algorithm(
+    extra_params=_dtype_param,
+    is_incomplete=True,  # dangling not supported
+    plc={"pagerank", "personalized_pagerank"},
+    version_added="23.12",
+)
 def pagerank(
     G,
     alpha=0.85,
@@ -97,7 +102,7 @@ def pagerank(
 
 
 @pagerank._can_run
-def pagerank(
+def _(
     G,
     alpha=0.85,
     personalization=None,
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/shortest_paths/unweighted.py b/python/nx-cugraph/nx_cugraph/algorithms/shortest_paths/unweighted.py
index 3413a637b32..b1032a8236b 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/shortest_paths/unweighted.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/shortest_paths/unweighted.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -21,12 +21,12 @@
 __all__ = ["single_source_shortest_path_length", "single_target_shortest_path_length"]
 
 
-@networkx_algorithm
+@networkx_algorithm(plc="bfs", version_added="23.12")
 def single_source_shortest_path_length(G, source, cutoff=None):
     return _single_shortest_path_length(G, source, cutoff, "Source")
 
 
-@networkx_algorithm
+@networkx_algorithm(plc="bfs", version_added="23.12")
 def single_target_shortest_path_length(G, target, cutoff=None):
     return _single_shortest_path_length(G, target, cutoff, "Target")
 
diff --git a/python/nx-cugraph/nx_cugraph/algorithms/traversal/breadth_first_search.py b/python/nx-cugraph/nx_cugraph/algorithms/traversal/breadth_first_search.py
index e2a7d46f462..aa671bbb7d4 100644
--- a/python/nx-cugraph/nx_cugraph/algorithms/traversal/breadth_first_search.py
+++ b/python/nx-cugraph/nx_cugraph/algorithms/traversal/breadth_first_search.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -57,7 +57,7 @@ def _bfs(G, source, *, depth_limit=None, reverse=False):
     return distances[mask], predecessors[mask], node_ids[mask]
 
 
-@networkx_algorithm
+@networkx_algorithm(is_incomplete=True, plc="bfs", version_added="24.02")
 def generic_bfs_edges(G, source, neighbors=None, depth_limit=None, sort_neighbors=None):
     """`neighbors` and `sort_neighbors` parameters are not yet supported."""
     return bfs_edges(source, depth_limit=depth_limit)
@@ -68,7 +68,7 @@ def _(G, source, neighbors=None, depth_limit=None, sort_neighbors=None):
     return neighbors is None and sort_neighbors is None
 
 
-@networkx_algorithm
+@networkx_algorithm(is_incomplete=True, plc="bfs", version_added="24.02")
 def bfs_edges(G, source, reverse=False, depth_limit=None, sort_neighbors=None):
     """`sort_neighbors` parameter is not yet supported."""
     G = _check_G_and_source(G, source)
@@ -95,7 +95,7 @@ def _(G, source, reverse=False, depth_limit=None, sort_neighbors=None):
     return sort_neighbors is None
 
 
-@networkx_algorithm
+@networkx_algorithm(is_incomplete=True, plc="bfs", version_added="24.02")
 def bfs_tree(G, source, reverse=False, depth_limit=None, sort_neighbors=None):
     """`sort_neighbors` parameter is not yet supported."""
     G = _check_G_and_source(G, source)
@@ -149,7 +149,7 @@ def _(G, source, reverse=False, depth_limit=None, sort_neighbors=None):
     return sort_neighbors is None
 
 
-@networkx_algorithm
+@networkx_algorithm(is_incomplete=True, plc="bfs", version_added="24.02")
 def bfs_successors(G, source, depth_limit=None, sort_neighbors=None):
     """`sort_neighbors` parameter is not yet supported."""
     G = _check_G_and_source(G, source)
@@ -173,7 +173,7 @@ def _(G, source, depth_limit=None, sort_neighbors=None):
     return sort_neighbors is None
 
 
-@networkx_algorithm
+@networkx_algorithm(plc="bfs", version_added="24.02")
 def bfs_layers(G, sources):
     G = _to_graph(G)
     if sources in G:
@@ -201,7 +201,7 @@ def bfs_layers(G, sources):
     return (G._nodearray_to_list(groups[key]) for key in range(len(groups)))
 
 
-@networkx_algorithm
+@networkx_algorithm(is_incomplete=True, plc="bfs", version_added="24.02")
 def bfs_predecessors(G, source, depth_limit=None, sort_neighbors=None):
     """`sort_neighbors` parameter is not yet supported."""
     G = _check_G_and_source(G, source)
@@ -227,7 +227,7 @@ def _(G, source, depth_limit=None, sort_neighbors=None):
     return sort_neighbors is None
 
 
-@networkx_algorithm
+@networkx_algorithm(plc="bfs", version_added="24.02")
 def descendants_at_distance(G, source, distance):
     G = _check_G_and_source(G, source)
     if distance is None or distance < 0:
diff --git a/python/nx-cugraph/nx_cugraph/classes/function.py b/python/nx-cugraph/nx_cugraph/classes/function.py
index 633e4abd7f4..435dfe37239 100644
--- a/python/nx-cugraph/nx_cugraph/classes/function.py
+++ b/python/nx-cugraph/nx_cugraph/classes/function.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -16,7 +16,7 @@
 __all__ = ["number_of_selfloops"]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def number_of_selfloops(G):
     G = _to_graph(G)
     is_selfloop = G.src_indices == G.dst_indices
diff --git a/python/nx-cugraph/nx_cugraph/convert_matrix.py b/python/nx-cugraph/nx_cugraph/convert_matrix.py
index 80ca0c2fa4b..1a2ecde9b8c 100644
--- a/python/nx-cugraph/nx_cugraph/convert_matrix.py
+++ b/python/nx-cugraph/nx_cugraph/convert_matrix.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -23,7 +23,8 @@
 ]
 
 
-@networkx_algorithm
+# Value columns with string dtype is not supported
+@networkx_algorithm(is_incomplete=True, version_added="23.12")
 def from_pandas_edgelist(
     df,
     source="source",
@@ -32,7 +33,7 @@ def from_pandas_edgelist(
     create_using=None,
     edge_key=None,
 ):
-    """cudf.DataFrame inputs also supported."""
+    """cudf.DataFrame inputs also supported; value columns with str is unsuppported."""
     graph_class, inplace = _create_using_class(create_using)
     src_array = df[source].to_numpy()
     dst_array = df[target].to_numpy()
@@ -120,7 +121,7 @@ def from_pandas_edgelist(
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def from_scipy_sparse_array(
     A, parallel_edges=False, create_using=None, edge_attribute="weight"
 ):
diff --git a/python/nx-cugraph/nx_cugraph/generators/classic.py b/python/nx-cugraph/nx_cugraph/generators/classic.py
index 4213e6dd2a0..a548beea34f 100644
--- a/python/nx-cugraph/nx_cugraph/generators/classic.py
+++ b/python/nx-cugraph/nx_cugraph/generators/classic.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -51,7 +51,7 @@
 concat = itertools.chain.from_iterable
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def barbell_graph(m1, m2, create_using=None):
     # Like two complete graphs and a path_graph
     m1 = _ensure_nonnegative_int(m1)
@@ -81,12 +81,12 @@ def barbell_graph(m1, m2, create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def circular_ladder_graph(n, create_using=None):
     return _ladder_graph(n, create_using, is_circular=True)
 
 
-@networkx_algorithm(nodes_or_number=0)
+@networkx_algorithm(nodes_or_number=0, version_added="23.12")
 def complete_graph(n, create_using=None):
     n, nodes = _number_and_nodes(n)
     if n < 3:
@@ -99,7 +99,7 @@ def complete_graph(n, create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def complete_multipartite_graph(*subset_sizes):
     if not subset_sizes:
         return nxcg.Graph()
@@ -142,7 +142,7 @@ def complete_multipartite_graph(*subset_sizes):
     )
 
 
-@networkx_algorithm(nodes_or_number=0)
+@networkx_algorithm(nodes_or_number=0, version_added="23.12")
 def cycle_graph(n, create_using=None):
     n, nodes = _number_and_nodes(n)
     graph_class, inplace = _create_using_class(create_using)
@@ -172,7 +172,7 @@ def cycle_graph(n, create_using=None):
     return G
 
 
-@networkx_algorithm(nodes_or_number=0)
+@networkx_algorithm(nodes_or_number=0, version_added="23.12")
 def empty_graph(n=0, create_using=None, default=nx.Graph):
     n, nodes = _number_and_nodes(n)
     graph_class, inplace = _create_using_class(create_using, default=default)
@@ -234,12 +234,12 @@ def _ladder_graph(n, create_using, *, is_circular=False):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def ladder_graph(n, create_using=None):
     return _ladder_graph(n, create_using)
 
 
-@networkx_algorithm(nodes_or_number=[0, 1])
+@networkx_algorithm(nodes_or_number=[0, 1], version_added="23.12")
 def lollipop_graph(m, n, create_using=None):
     # Like complete_graph then path_graph
     orig_m, unused_nodes_m = m
@@ -274,12 +274,12 @@ def lollipop_graph(m, n, create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def null_graph(create_using=None):
     return _common_small_graph(0, None, create_using)
 
 
-@networkx_algorithm(nodes_or_number=0)
+@networkx_algorithm(nodes_or_number=0, version_added="23.12")
 def path_graph(n, create_using=None):
     n, nodes = _number_and_nodes(n)
     graph_class, inplace = _create_using_class(create_using)
@@ -299,7 +299,7 @@ def path_graph(n, create_using=None):
     return G
 
 
-@networkx_algorithm(nodes_or_number=0)
+@networkx_algorithm(nodes_or_number=0, version_added="23.12")
 def star_graph(n, create_using=None):
     orig_n, orig_nodes = n
     n, nodes = _number_and_nodes(n)
@@ -323,7 +323,7 @@ def star_graph(n, create_using=None):
     return G
 
 
-@networkx_algorithm(nodes_or_number=[0, 1])
+@networkx_algorithm(nodes_or_number=[0, 1], version_added="23.12")
 def tadpole_graph(m, n, create_using=None):
     orig_m, unused_nodes_m = m
     orig_n, unused_nodes_n = n
@@ -361,12 +361,12 @@ def tadpole_graph(m, n, create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def trivial_graph(create_using=None):
     return _common_small_graph(1, None, create_using)
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def turan_graph(n, r):
     if not 1 <= r <= n:
         raise nx.NetworkXError("Must satisfy 1 <= r <= n")
@@ -375,7 +375,7 @@ def turan_graph(n, r):
     return complete_multipartite_graph(*partitions)
 
 
-@networkx_algorithm(nodes_or_number=0)
+@networkx_algorithm(nodes_or_number=0, version_added="23.12")
 def wheel_graph(n, create_using=None):
     n, nodes = _number_and_nodes(n)
     graph_class, inplace = _create_using_class(create_using)
diff --git a/python/nx-cugraph/nx_cugraph/generators/community.py b/python/nx-cugraph/nx_cugraph/generators/community.py
index e5cb03e8cc0..9b0e0848de9 100644
--- a/python/nx-cugraph/nx_cugraph/generators/community.py
+++ b/python/nx-cugraph/nx_cugraph/generators/community.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -27,7 +27,7 @@
 ]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def caveman_graph(l, k):  # noqa: E741
     l = _ensure_int(l)  # noqa: E741
     k = _ensure_int(k)
diff --git a/python/nx-cugraph/nx_cugraph/generators/small.py b/python/nx-cugraph/nx_cugraph/generators/small.py
index b9a189c31d5..45487571cda 100644
--- a/python/nx-cugraph/nx_cugraph/generators/small.py
+++ b/python/nx-cugraph/nx_cugraph/generators/small.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -43,7 +43,7 @@
 ]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def bull_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -56,7 +56,7 @@ def bull_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def chvatal_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -85,7 +85,7 @@ def chvatal_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def cubical_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -105,7 +105,7 @@ def cubical_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def desargues_graph(create_using=None):
     # This can also be defined w.r.t. LCF_graph
     graph_class, inplace = _create_using_class(create_using)
@@ -146,7 +146,7 @@ def desargues_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def diamond_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -159,7 +159,7 @@ def diamond_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def dodecahedral_graph(create_using=None):
     # This can also be defined w.r.t. LCF_graph
     graph_class, inplace = _create_using_class(create_using)
@@ -200,7 +200,7 @@ def dodecahedral_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def frucht_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -235,7 +235,7 @@ def frucht_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def heawood_graph(create_using=None):
     # This can also be defined w.r.t. LCF_graph
     graph_class, inplace = _create_using_class(create_using)
@@ -274,7 +274,7 @@ def heawood_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def house_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -287,7 +287,7 @@ def house_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def house_x_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -306,7 +306,7 @@ def house_x_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def icosahedral_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -337,7 +337,7 @@ def icosahedral_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def krackhardt_kite_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -366,7 +366,7 @@ def krackhardt_kite_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def moebius_kantor_graph(create_using=None):
     # This can also be defined w.r.t. LCF_graph
     graph_class, inplace = _create_using_class(create_using)
@@ -407,7 +407,7 @@ def moebius_kantor_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def octahedral_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -428,7 +428,7 @@ def octahedral_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def pappus_graph():
     # This can also be defined w.r.t. LCF_graph
     # fmt: off
@@ -452,7 +452,7 @@ def pappus_graph():
     return nxcg.Graph.from_coo(18, src_indices, dst_indices, name="Pappus Graph")
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def petersen_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -479,7 +479,7 @@ def petersen_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def sedgewick_maze_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -500,7 +500,7 @@ def sedgewick_maze_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def tetrahedral_graph(create_using=None):
     # This can also be defined w.r.t. complete_graph
     graph_class, inplace = _create_using_class(create_using)
@@ -517,7 +517,7 @@ def tetrahedral_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def truncated_cube_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -548,7 +548,7 @@ def truncated_cube_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def truncated_tetrahedron_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
@@ -583,7 +583,7 @@ def truncated_tetrahedron_graph(create_using=None):
     return G
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def tutte_graph(create_using=None):
     graph_class, inplace = _create_using_class(create_using)
     if graph_class.is_directed():
diff --git a/python/nx-cugraph/nx_cugraph/generators/social.py b/python/nx-cugraph/nx_cugraph/generators/social.py
index 3c936d07af3..07e82c63fbf 100644
--- a/python/nx-cugraph/nx_cugraph/generators/social.py
+++ b/python/nx-cugraph/nx_cugraph/generators/social.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -25,7 +25,7 @@
 ]
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def davis_southern_women_graph():
     # fmt: off
     src_indices = cp.array(
@@ -88,7 +88,7 @@ def davis_southern_women_graph():
     )
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def florentine_families_graph():
     # fmt: off
     src_indices = cp.array(
@@ -114,7 +114,7 @@ def florentine_families_graph():
     return nxcg.Graph.from_coo(15, src_indices, dst_indices, id_to_key=nodes)
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def karate_club_graph():
     # fmt: off
     src_indices = cp.array(
@@ -175,7 +175,7 @@ def karate_club_graph():
     )
 
 
-@networkx_algorithm
+@networkx_algorithm(version_added="23.12")
 def les_miserables_graph():
     # fmt: off
     src_indices = cp.array(
diff --git a/python/nx-cugraph/nx_cugraph/scripts/__init__.py b/python/nx-cugraph/nx_cugraph/scripts/__init__.py
new file mode 100644
index 00000000000..aeae6078111
--- /dev/null
+++ b/python/nx-cugraph/nx_cugraph/scripts/__init__.py
@@ -0,0 +1,12 @@
+# Copyright (c) 2024, NVIDIA CORPORATION.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/python/nx-cugraph/nx_cugraph/scripts/__main__.py b/python/nx-cugraph/nx_cugraph/scripts/__main__.py
new file mode 100755
index 00000000000..c0963e64cc5
--- /dev/null
+++ b/python/nx-cugraph/nx_cugraph/scripts/__main__.py
@@ -0,0 +1,38 @@
+#!/usr/bin/env python
+# Copyright (c) 2024, NVIDIA CORPORATION.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+if __name__ == "__main__":
+    import argparse
+
+    from nx_cugraph.scripts import print_table, print_tree
+
+    parser = argparse.ArgumentParser(
+        parents=[
+            print_table.get_argumentparser(add_help=False),
+            print_tree.get_argumentparser(add_help=False),
+        ],
+        description="Print info about functions implemented by nx-cugraph",
+    )
+    parser.add_argument("action", choices=["print_table", "print_tree"])
+    args = parser.parse_args()
+    if args.action == "print_table":
+        print_table.main()
+    else:
+        print_tree.main(
+            by=args.by,
+            networkx_path=args.networkx_path,
+            dispatch_name=args.dispatch_name or args.dispatch_name_always,
+            version_added=args.version_added,
+            plc=args.plc,
+            dispatch_name_if_different=not args.dispatch_name_always,
+        )
diff --git a/python/nx-cugraph/nx_cugraph/scripts/print_table.py b/python/nx-cugraph/nx_cugraph/scripts/print_table.py
new file mode 100755
index 00000000000..7e69de63dc1
--- /dev/null
+++ b/python/nx-cugraph/nx_cugraph/scripts/print_table.py
@@ -0,0 +1,78 @@
+#!/usr/bin/env python
+# Copyright (c) 2024, NVIDIA CORPORATION.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import argparse
+import sys
+from collections import namedtuple
+
+from networkx.utils.backends import _registered_algorithms as algos
+
+from _nx_cugraph import get_info
+from nx_cugraph.interface import BackendInterface
+
+
+def get_funcpath(func):
+    return f"{func.__module__}.{func.__name__}"
+
+
+def get_path_to_name():
+    return {
+        get_funcpath(algos[funcname]): funcname
+        for funcname in get_info()["functions"].keys() & algos.keys()
+    }
+
+
+Info = namedtuple(
+    "Info",
+    "networkx_path, dispatch_name, version_added, plc, is_incomplete, is_different",
+)
+
+
+def get_path_to_info(path_to_name=None, version_added_sep=".", plc_sep="/"):
+    if path_to_name is None:
+        path_to_name = get_path_to_name()
+    rv = {}
+    for funcpath in sorted(path_to_name):
+        funcname = path_to_name[funcpath]
+        cufunc = getattr(BackendInterface, funcname)
+        plc = plc_sep.join(sorted(cufunc._plc_names)) if cufunc._plc_names else ""
+        version_added = cufunc.version_added.replace(".", version_added_sep)
+        is_incomplete = cufunc.is_incomplete
+        is_different = cufunc.is_different
+        rv[funcpath] = Info(
+            funcpath, funcname, version_added, plc, is_incomplete, is_different
+        )
+    return rv
+
+
+def main(path_to_info=None, *, file=sys.stdout):
+    if path_to_info is None:
+        path_to_info = get_path_to_info(version_added_sep=".")
+    lines = ["networkx_path,dispatch_name,version_added,plc,is_incomplete,is_different"]
+    lines.extend(",".join(info) for info in path_to_info.values())
+    text = "\n".join(lines)
+    print(text, file=file)
+    return text
+
+
+def get_argumentparser(add_help=True):
+    return argparse.ArgumentParser(
+        description="Print info about functions implemented by nx-cugraph as CSV",
+        add_help=add_help,
+    )
+
+
+if __name__ == "__main__":
+    parser = get_argumentparser()
+    args = parser.parse_args()
+    main()
diff --git a/python/nx-cugraph/nx_cugraph/scripts/print_tree.py b/python/nx-cugraph/nx_cugraph/scripts/print_tree.py
new file mode 100755
index 00000000000..bb75d735c31
--- /dev/null
+++ b/python/nx-cugraph/nx_cugraph/scripts/print_tree.py
@@ -0,0 +1,241 @@
+#!/usr/bin/env python
+# Copyright (c) 2024, NVIDIA CORPORATION.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import argparse
+import re
+import sys
+
+import networkx as nx
+
+from nx_cugraph.scripts.print_table import get_path_to_info
+
+
+def add_branch(G, path, extra="", *, skip=0):
+    branch = path.split(".")
+    prev = ".".join(branch[: skip + 1])
+    for i in range(skip + 2, len(branch)):
+        cur = ".".join(branch[:i])
+        G.add_edge(prev, cur)
+        prev = cur
+    if extra:
+        if not isinstance(extra, str):
+            extra = ", ".join(extra)
+        path += f" ({extra})"
+    G.add_edge(prev, path)
+
+
+def get_extra(
+    info,
+    *,
+    networkx_path=False,
+    dispatch_name=False,
+    version_added=False,
+    plc=False,
+    dispatch_name_if_different=False,
+    incomplete=False,
+    different=False,
+):
+    extra = []
+    if networkx_path:
+        extra.append(info.networkx_path)
+    if dispatch_name and (
+        not dispatch_name_if_different
+        or info.dispatch_name != info.networkx_path.rsplit(".", 1)[-1]
+    ):
+        extra.append(info.dispatch_name)
+    if version_added:
+        v = info.version_added
+        if len(v) != 5:
+            raise ValueError(f"Is there something wrong with version: {v!r}?")
+        extra.append(v[:2] + "." + v[-2:])
+    if plc and info.plc:
+        extra.append(info.plc)
+    if incomplete and info.is_incomplete:
+        extra.append("is-incomplete")
+    if different and info.is_different:
+        extra.append("is-different")
+    return extra
+
+
+def create_tree(
+    path_to_info=None,
+    *,
+    by="networkx_path",
+    skip=0,
+    networkx_path=False,
+    dispatch_name=False,
+    version_added=False,
+    plc=False,
+    dispatch_name_if_different=False,
+    incomplete=False,
+    different=False,
+    prefix="",
+):
+    if path_to_info is None:
+        path_to_info = get_path_to_info()
+    if isinstance(by, str):
+        by = [by]
+    G = nx.DiGraph()
+    for info in sorted(
+        path_to_info.values(),
+        key=lambda x: (*(getattr(x, b) for b in by), x.networkx_path),
+    ):
+        if not all(getattr(info, b) for b in by):
+            continue
+        path = prefix + ".".join(getattr(info, b) for b in by)
+        extra = get_extra(
+            info,
+            networkx_path=networkx_path,
+            dispatch_name=dispatch_name,
+            version_added=version_added,
+            plc=plc,
+            dispatch_name_if_different=dispatch_name_if_different,
+            incomplete=incomplete,
+            different=different,
+        )
+        add_branch(G, path, extra=extra, skip=skip)
+    return G
+
+
+def main(
+    path_to_info=None,
+    *,
+    by="networkx_path",
+    networkx_path=False,
+    dispatch_name=False,
+    version_added=False,
+    plc=False,
+    dispatch_name_if_different=True,
+    incomplete=False,
+    different=False,
+    file=sys.stdout,
+):
+    if path_to_info is None:
+        path_to_info = get_path_to_info(version_added_sep="-")
+    kwargs = {
+        "networkx_path": networkx_path,
+        "dispatch_name": dispatch_name,
+        "version_added": version_added,
+        "plc": plc,
+        "dispatch_name_if_different": dispatch_name_if_different,
+        "incomplete": incomplete,
+        "different": different,
+    }
+    if by == "networkx_path":
+        G = create_tree(path_to_info, by="networkx_path", **kwargs)
+        text = re.sub(r"[A-Za-z_\./]+\.", "", ("\n".join(nx.generate_network_text(G))))
+    elif by == "plc":
+        G = create_tree(
+            path_to_info, by=["plc", "networkx_path"], prefix="plc-", **kwargs
+        )
+        text = re.sub(
+            "plc-",
+            "plc.",
+            re.sub(
+                r" plc-[A-Za-z_\./]*\.",
+                " ",
+                "\n".join(nx.generate_network_text(G)),
+            ),
+        )
+    elif by == "version_added":
+        G = create_tree(
+            path_to_info,
+            by=["version_added", "networkx_path"],
+            prefix="version_added-",
+            **kwargs,
+        )
+        text = re.sub(
+            "version_added-",
+            "version: ",
+            re.sub(
+                r" version_added-[-0-9A-Za-z_\./]*\.",
+                " ",
+                "\n".join(nx.generate_network_text(G)),
+            ),
+        ).replace("-", ".")
+    else:
+        raise ValueError(
+            "`by` argument should be one of {'networkx_path', 'plc', 'version_added' "
+            f"got: {by}"
+        )
+    print(text, file=file)
+    return text
+
+
+def get_argumentparser(add_help=True):
+    parser = argparse.ArgumentParser(
+        "Print a tree showing NetworkX functions implemented by nx-cugraph",
+        add_help=add_help,
+    )
+    parser.add_argument(
+        "--by",
+        choices=["networkx_path", "plc", "version_added"],
+        default="networkx_path",
+        help="How to group functions",
+    )
+    parser.add_argument(
+        "--dispatch-name",
+        "--dispatch_name",
+        action="store_true",
+        help="Show the dispatch name in parentheses if different from NetworkX name",
+    )
+    parser.add_argument(
+        "--dispatch-name-always",
+        "--dispatch_name_always",
+        action="store_true",
+        help="Always show the dispatch name in parentheses",
+    )
+    parser.add_argument(
+        "--plc",
+        "--pylibcugraph",
+        action="store_true",
+        help="Show the used pylibcugraph function in parentheses",
+    )
+    parser.add_argument(
+        "--version-added",
+        "--version_added",
+        action="store_true",
+        help="Show the version added in parentheses",
+    )
+    parser.add_argument(
+        "--networkx-path",
+        "--networkx_path",
+        action="store_true",
+        help="Show the full networkx path in parentheses",
+    )
+    parser.add_argument(
+        "--incomplete",
+        action="store_true",
+        help="Show which functions are incomplete",
+    )
+    parser.add_argument(
+        "--different",
+        action="store_true",
+        help="Show which functions are different",
+    )
+    return parser
+
+
+if __name__ == "__main__":
+    parser = get_argumentparser()
+    args = parser.parse_args()
+    main(
+        by=args.by,
+        networkx_path=args.networkx_path,
+        dispatch_name=args.dispatch_name or args.dispatch_name_always,
+        version_added=args.version_added,
+        plc=args.plc,
+        dispatch_name_if_different=not args.dispatch_name_always,
+        incomplete=args.incomplete,
+        different=args.different,
+    )
diff --git a/python/nx-cugraph/nx_cugraph/utils/decorators.py b/python/nx-cugraph/nx_cugraph/utils/decorators.py
index a0dbfcec890..d09a9e9617a 100644
--- a/python/nx-cugraph/nx_cugraph/utils/decorators.py
+++ b/python/nx-cugraph/nx_cugraph/utils/decorators.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2023, NVIDIA CORPORATION.
+# Copyright (c) 2023-2024, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -41,14 +41,25 @@ class networkx_algorithm:
     name: str
     extra_doc: str | None
     extra_params: dict[str, str] | None
+    version_added: str
+    is_incomplete: bool
+    is_different: bool
+    _plc_names: set[str] | None
 
     def __new__(
         cls,
         func=None,
         *,
         name: str | None = None,
+        # Extra parameter info that is added to NetworkX docstring
         extra_params: dict[str, str] | str | None = None,
+        # Applies `nodes_or_number` decorator compatibly across versions (3.3 changed)
         nodes_or_number: list[int] | int | None = None,
+        # Metadata (for introspection only)
+        version_added: str,  # Required
+        is_incomplete: bool = False,  # See self.extra_doc for details if True
+        is_different: bool = False,  # See self.extra_doc for details if True
+        plc: str | set[str] | None = None,  # Hidden from user, may be removed someday
     ):
         if func is None:
             return partial(
@@ -56,6 +67,10 @@ def __new__(
                 name=name,
                 extra_params=extra_params,
                 nodes_or_number=nodes_or_number,
+                plc=plc,
+                version_added=version_added,
+                is_incomplete=is_incomplete,
+                is_different=is_different,
             )
         instance = object.__new__(cls)
         if nodes_or_number is not None and nx.__version__[:3] > "3.2":
@@ -74,6 +89,15 @@ def __new__(
                 f"extra_params must be dict, str, or None; got {type(extra_params)}"
             )
         instance.extra_params = extra_params
+        if plc is None or isinstance(plc, set):
+            instance._plc_names = plc
+        elif isinstance(plc, str):
+            instance._plc_names = {plc}
+        else:
+            raise TypeError(f"plc argument must be str, set, or None; got {type(plc)}")
+        instance.version_added = version_added
+        instance.is_incomplete = is_incomplete
+        instance.is_different = is_different
         # The docstring on our function is added to the NetworkX docstring.
         instance.extra_doc = (
             dedent(func.__doc__.lstrip("\n").rstrip()) if func.__doc__ else None
@@ -91,6 +115,11 @@ def __new__(
 
     def _can_run(self, func):
         """Set the `can_run` attribute to the decorated function."""
+        if not func.__name__.startswith("_"):
+            raise ValueError(
+                "The name of the function used by `_can_run` must begin with '_'; "
+                f"got: {func.__name__!r}"
+            )
         self.can_run = func
 
     def __call__(self, /, *args, **kwargs):
diff --git a/python/nx-cugraph/pyproject.toml b/python/nx-cugraph/pyproject.toml
index b29578b036f..63ac115918f 100644
--- a/python/nx-cugraph/pyproject.toml
+++ b/python/nx-cugraph/pyproject.toml
@@ -52,12 +52,20 @@ test = [
 Homepage = "https://github.com/rapidsai/cugraph"
 Documentation = "https://docs.rapids.ai/api/cugraph/stable/"
 
+# "plugin" used in nx version < 3.2
 [project.entry-points."networkx.plugins"]
 cugraph = "nx_cugraph.interface:BackendInterface"
 
 [project.entry-points."networkx.plugin_info"]
 cugraph = "_nx_cugraph:get_info"
 
+# "backend" used in nx version >= 3.2
+[project.entry-points."networkx.backends"]
+cugraph = "nx_cugraph.interface:BackendInterface"
+
+[project.entry-points."networkx.backend_info"]
+cugraph = "_nx_cugraph:get_info"
+
 [tool.setuptools]
 license-files = ["LICENSE"]