diff --git a/NAMESPACE b/NAMESPACE
index 26588286f..26f77abd9 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,5 +1,8 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(build_longer_spec,data.frame)
+S3method(build_wider_spec,data.frame)
+S3method(chop,data.frame)
 S3method(complete,data.frame)
 S3method(complete_,data.frame)
 S3method(drop_na,data.frame)
@@ -16,13 +19,17 @@ S3method(full_seq,POSIXct)
 S3method(full_seq,numeric)
 S3method(gather,data.frame)
 S3method(gather_,data.frame)
+S3method(hoist,data.frame)
 S3method(nest,data.frame)
 S3method(nest,grouped_df)
 S3method(nest,tbl_df)
 S3method(nest_legacy,data.frame)
 S3method(nest_legacy,tbl_df)
+S3method(pack,data.frame)
 S3method(pivot_longer,data.frame)
+S3method(pivot_longer_spec,data.frame)
 S3method(pivot_wider,data.frame)
+S3method(pivot_wider_spec,data.frame)
 S3method(replace_na,data.frame)
 S3method(replace_na,default)
 S3method(separate,data.frame)
@@ -31,11 +38,16 @@ S3method(separate_rows,data.frame)
 S3method(separate_rows_,data.frame)
 S3method(spread,data.frame)
 S3method(spread_,data.frame)
+S3method(unchop,data.frame)
+S3method(uncount,data.frame)
 S3method(unite,data.frame)
 S3method(unite_,data.frame)
 S3method(unnest,data.frame)
 S3method(unnest,rowwise_df)
 S3method(unnest_legacy,data.frame)
+S3method(unnest_longer,data.frame)
+S3method(unnest_wider,data.frame)
+S3method(unpack,data.frame)
 export("%>%")
 export(as_tibble)
 export(build_longer_spec)
diff --git a/R/chop.R b/R/chop.R
index ed235f12b..e47084ebf 100644
--- a/R/chop.R
+++ b/R/chop.R
@@ -40,6 +40,7 @@
 #' @param ptype Optionally, supply a data frame prototype for the output `cols`,
 #'   overriding the default that will be guessed from the combination of
 #'   individual values.
+#' @param ... Additional arguments passed on to methods.
 #' @export
 #' @examples
 #' # Chop ==============================================================
@@ -66,7 +67,13 @@
 #' df <- tibble(x = 1:3, y = list(NULL, tibble(x = 1), tibble(y = 1:2)))
 #' df %>% unchop(y)
 #' df %>% unchop(y, keep_empty = TRUE)
-chop <- function(data, cols) {
+chop <- function(data, cols, ...) {
+  ellipsis::check_dots_used()
+  UseMethod("chop")
+}
+
+#' @export
+chop.data.frame <- function(data, cols, ...) {
   if (missing(cols)) {
     return(data)
   }
@@ -89,7 +96,13 @@ chop <- function(data, cols) {
 
 #' @export
 #' @rdname chop
-unchop <- function(data, cols, keep_empty = FALSE, ptype = NULL) {
+unchop <- function(data, cols, ..., keep_empty = FALSE, ptype = NULL) {
+  ellipsis::check_dots_used()
+  UseMethod("unchop")
+}
+
+#' @export
+unchop.data.frame <- function(data, cols, ..., keep_empty = FALSE, ptype = NULL) {
   cols <- tidyselect::eval_select(enquo(cols), data)
   if (length(cols) == 0) {
     return(data)
diff --git a/R/pack.R b/R/pack.R
index 3dab13b7d..418b27625 100644
--- a/R/pack.R
+++ b/R/pack.R
@@ -60,6 +60,11 @@
 #' df %>% unpack(c(y, z))
 #' df %>% unpack(c(y, z), names_sep = "_")
 pack <- function(.data, ..., .names_sep = NULL) {
+  UseMethod("pack")
+}
+
+#' @export
+pack.data.frame <- function(.data, ..., .names_sep = NULL) {
   cols <- enquos(...)
   if (any(names2(cols) == "")) {
     abort("All elements of `...` must be named")
@@ -94,7 +99,13 @@ pack <- function(.data, ..., .names_sep = NULL) {
 #'
 #'   See [vctrs::vec_as_names()] for more details on these terms and the
 #'   strategies used to enforce them.
-unpack <- function(data, cols, names_sep = NULL, names_repair = "check_unique") {
+unpack <- function(data, cols, ..., names_sep = NULL, names_repair = "check_unique") {
+  ellipsis::check_dots_used()
+  UseMethod("unpack")
+}
+
+#' @export
+unpack.data.frame <- function(data, cols, ..., names_sep = NULL, names_repair = "check_unique") {
   check_present(cols)
   cols <- tidyselect::eval_select(enquo(cols), data)
 
diff --git a/R/pivot-long.R b/R/pivot-long.R
index 62fafbc1f..fd31dee62 100644
--- a/R/pivot-long.R
+++ b/R/pivot-long.R
@@ -207,8 +207,22 @@ pivot_longer_spec <- function(data,
                               names_repair = "check_unique",
                               values_drop_na = FALSE,
                               values_ptypes = list(),
-                              values_transform = list()
+                              values_transform = list(),
+                              ...
                               ) {
+  ellipsis::check_dots_used()
+  UseMethod("pivot_longer_spec")
+}
+
+#' @export
+pivot_longer_spec.data.frame <- function(data,
+                                         spec,
+                                         ...,
+                                         names_repair = "check_unique",
+                                         values_drop_na = FALSE,
+                                         values_ptypes = list(),
+                                         values_transform = list()
+                                         ) {
   spec <- check_spec(spec)
   spec <- deduplicate_spec(spec, data)
 
@@ -265,6 +279,7 @@ pivot_longer_spec <- function(data,
 #' @rdname pivot_longer_spec
 #' @export
 build_longer_spec <- function(data, cols,
+                              ...,
                               names_to = "name",
                               values_to = "value",
                               names_prefix = NULL,
@@ -272,6 +287,20 @@ build_longer_spec <- function(data, cols,
                               names_pattern = NULL,
                               names_ptypes = NULL,
                               names_transform = NULL) {
+  ellipsis::check_dots_used()
+  UseMethod("build_longer_spec")
+}
+
+#' @export
+build_longer_spec.data.frame <- function(data, cols,
+                                         ...,
+                                         names_to = "name",
+                                         values_to = "value",
+                                         names_prefix = NULL,
+                                         names_sep = NULL,
+                                         names_pattern = NULL,
+                                         names_ptypes = NULL,
+                                         names_transform = NULL) {
   cols <- tidyselect::eval_select(enquo(cols), data[unique(names(data))])
 
   if (length(cols) == 0) {
diff --git a/R/pivot-wide.R b/R/pivot-wide.R
index 421f5dc88..38e86f785 100644
--- a/R/pivot-wide.R
+++ b/R/pivot-wide.R
@@ -109,6 +109,7 @@ pivot_wider <- function(data,
 
 #' @export
 pivot_wider.data.frame <- function(data,
+                                   ...,
                                    id_cols = NULL,
                                    names_from = name,
                                    names_prefix = "",
@@ -118,8 +119,7 @@ pivot_wider.data.frame <- function(data,
                                    names_repair = "check_unique",
                                    values_from = value,
                                    values_fill = NULL,
-                                   values_fn = NULL,
-                                   ...
+                                   values_fn = NULL
                                    ) {
   names_from <- enquo(names_from)
   values_from <- enquo(values_from)
@@ -133,7 +133,8 @@ pivot_wider.data.frame <- function(data,
   )
 
   id_cols <- enquo(id_cols)
-  pivot_wider_spec(data, spec, !!id_cols,
+  pivot_wider_spec(data, spec,
+    id_cols = !!id_cols,
     names_repair = names_repair,
     values_fill = values_fill,
     values_fn = values_fn
@@ -186,11 +187,24 @@ pivot_wider.data.frame <- function(data,
 #' us_rent_income %>%
 #'   pivot_wider_spec(spec2)
 pivot_wider_spec <- function(data,
-                                  spec,
-                                  names_repair = "check_unique",
-                                  id_cols = NULL,
-                                  values_fill = NULL,
-                                  values_fn = NULL) {
+                             spec,
+                             ...,
+                             names_repair = "check_unique",
+                             id_cols = NULL,
+                             values_fill = NULL,
+                             values_fn = NULL) {
+  ellipsis::check_dots_used()
+  UseMethod("pivot_wider_spec")
+}
+
+#' @export
+pivot_wider_spec.data.frame <- function(data,
+                                        spec,
+                                        ...,
+                                        names_repair = "check_unique",
+                                        id_cols = NULL,
+                                        values_fill = NULL,
+                                        values_fn = NULL) {
   spec <- check_spec(spec)
 
   if (is.function(values_fn)) {
@@ -286,11 +300,26 @@ pivot_wider_spec <- function(data,
 build_wider_spec <- function(data,
                              names_from = name,
                              values_from = value,
+                             ...,
                              names_prefix = "",
                              names_sep = "_",
                              names_glue = NULL,
                              names_sort = FALSE
                              ) {
+  ellipsis::check_dots_used()
+  UseMethod("build_wider_spec")
+}
+
+#' @export
+build_wider_spec.data.frame <- function(data,
+                                        names_from = name,
+                                        values_from = value,
+                                        ...,
+                                        names_prefix = "",
+                                        names_sep = "_",
+                                        names_glue = NULL,
+                                        names_sort = FALSE
+                                        ) {
   names_from <- tidyselect::eval_select(enquo(names_from), data)
   values_from <- tidyselect::eval_select(enquo(values_from), data)
 
diff --git a/R/rectangle.R b/R/rectangle.R
index 2f450c367..8fa10a92d 100644
--- a/R/rectangle.R
+++ b/R/rectangle.R
@@ -115,6 +115,11 @@
 #'
 #' @export hoist
 hoist <- function(.data, .col, ..., .remove = TRUE, .simplify = TRUE, .ptype = list(), .transform = list()) {
+  UseMethod("hoist")
+}
+
+#' @export
+hoist.data.frame <- function(.data, .col, ..., .remove = TRUE, .simplify = TRUE, .ptype = list(), .transform = list()) {
   check_present(.col)
   .col <- tidyselect::vars_pull(names(.data), !!enquo(.col))
   x <- .data[[.col]]
@@ -195,6 +200,7 @@ check_pluckers <- function(...) {
 #'   has inner names.
 #' @inheritParams unnest
 unnest_longer <- function(data, col,
+                          ...,
                           values_to = NULL,
                           indices_to = NULL,
                           indices_include = NULL,
@@ -203,6 +209,21 @@ unnest_longer <- function(data, col,
                           ptype = list(),
                           transform = list()
                           ) {
+  ellipsis::check_dots_used()
+  UseMethod("unnest_longer")
+}
+
+#' @export
+unnest_longer.data.frame <- function(data, col,
+                                     ...,
+                                     values_to = NULL,
+                                     indices_to = NULL,
+                                     indices_include = NULL,
+                                     names_repair = "check_unique",
+                                     simplify = TRUE,
+                                     ptype = list(),
+                                     transform = list()
+                                     ) {
 
   check_present(col)
   col <- tidyselect::vars_pull(names(data), !!enquo(col))
@@ -243,12 +264,26 @@ unnest_longer <- function(data, col,
 #'   as is. If a string, the inner and outer names will be paste together using
 #'   `names_sep` as a separator.
 unnest_wider <- function(data, col,
+                         ...,
                          names_sep = NULL,
                          simplify = TRUE,
                          names_repair = "check_unique",
                          ptype = list(),
                          transform = list()
                          ) {
+  ellipsis::check_dots_used()
+  UseMethod("unnest_wider")
+}
+
+#' @export
+unnest_wider.data.frame <- function(data, col,
+                                    ...,
+                                    names_sep = NULL,
+                                    simplify = TRUE,
+                                    names_repair = "check_unique",
+                                    ptype = list(),
+                                    transform = list()
+                                    ) {
   check_present(col)
   col <- tidyselect::vars_pull(tbl_vars(data), !!enquo(col))
 
diff --git a/R/uncount.R b/R/uncount.R
index 29ab067a3..f34e112bd 100644
--- a/R/uncount.R
+++ b/R/uncount.R
@@ -10,6 +10,7 @@
 #'   identifier for each created row.
 #' @param .remove If `TRUE`, and `weights` is the name of a column in `data`,
 #'   then this column is removed.
+#' @param ... Additional arguments passed on to methods.
 #' @export
 #' @examples
 #' df <- tibble(x = c("a", "b"), n = c(1, 2))
@@ -21,7 +22,13 @@
 #'
 #' # Or expressions
 #' uncount(df, 2 / n)
-uncount <- function(data, weights, .remove = TRUE, .id = NULL) {
+uncount <- function(data, weights, ..., .remove = TRUE, .id = NULL) {
+  ellipsis::check_dots_used()
+  UseMethod("uncount")
+}
+
+#' @export
+uncount.data.frame <- function(data, weights, ..., .remove = TRUE, .id = NULL) {
   weights_quo <- enquo(weights)
   w <- dplyr::pull(dplyr::mutate(data, `_weight` = !! weights_quo))
   # NOTE `vec_cast()` and check for positive weights can be removed
diff --git a/man/chop.Rd b/man/chop.Rd
index 9ebf59861..798dc53e5 100644
--- a/man/chop.Rd
+++ b/man/chop.Rd
@@ -5,9 +5,9 @@
 \alias{unchop}
 \title{Chop and unchop}
 \usage{
-chop(data, cols)
+chop(data, cols, ...)
 
-unchop(data, cols, keep_empty = FALSE, ptype = NULL)
+unchop(data, cols, ..., keep_empty = FALSE, ptype = NULL)
 }
 \arguments{
 \item{data}{A data frame.}
@@ -19,6 +19,8 @@ For \code{unchop()}, each column should be a list-column containing generalised
 vectors (e.g. any mix of \code{NULL}s, atomic vector, S3 vectors, a lists,
 or data frames).}
 
+\item{...}{Additional arguments passed on to methods.}
+
 \item{keep_empty}{By default, you get one row of output for each element
 of the list your unchopping/unnesting. This means that if there's a
 size-0 element (like \code{NULL} or an empty data frame), that entire row
diff --git a/man/hoist.Rd b/man/hoist.Rd
index deb35059f..013fa5e74 100644
--- a/man/hoist.Rd
+++ b/man/hoist.Rd
@@ -20,6 +20,7 @@ hoist(
 unnest_longer(
   data,
   col,
+  ...,
   values_to = NULL,
   indices_to = NULL,
   indices_include = NULL,
@@ -32,6 +33,7 @@ unnest_longer(
 unnest_wider(
   data,
   col,
+  ...,
   names_sep = NULL,
   simplify = TRUE,
   names_repair = "check_unique",
diff --git a/man/pack.Rd b/man/pack.Rd
index 6950f12d4..a5fce8b8e 100644
--- a/man/pack.Rd
+++ b/man/pack.Rd
@@ -7,7 +7,7 @@
 \usage{
 pack(.data, ..., .names_sep = NULL)
 
-unpack(data, cols, names_sep = NULL, names_repair = "check_unique")
+unpack(data, cols, ..., names_sep = NULL, names_repair = "check_unique")
 }
 \arguments{
 \item{...}{<\code{\link[=tidyr_tidy_select]{tidy-select}}> Columns to pack, specified
diff --git a/man/pivot_longer_spec.Rd b/man/pivot_longer_spec.Rd
index 6a3f53bde..84647374f 100644
--- a/man/pivot_longer_spec.Rd
+++ b/man/pivot_longer_spec.Rd
@@ -11,12 +11,14 @@ pivot_longer_spec(
   names_repair = "check_unique",
   values_drop_na = FALSE,
   values_ptypes = list(),
-  values_transform = list()
+  values_transform = list(),
+  ...
 )
 
 build_longer_spec(
   data,
   cols,
+  ...,
   names_to = "name",
   values_to = "value",
   names_prefix = NULL,
@@ -68,6 +70,8 @@ If not specified, the type of the columns generated from \code{names_to} will
 be character, and the type of the variables generated from \code{values_to}
 will be the common type of the input columns used to generate them.}
 
+\item{...}{Additional arguments passed on to methods.}
+
 \item{cols}{<\code{\link[=tidyr_tidy_select]{tidy-select}}> Columns to pivot into
 longer format.}
 
diff --git a/man/pivot_wider_spec.Rd b/man/pivot_wider_spec.Rd
index b7f2cfd02..991a35d67 100644
--- a/man/pivot_wider_spec.Rd
+++ b/man/pivot_wider_spec.Rd
@@ -8,6 +8,7 @@
 pivot_wider_spec(
   data,
   spec,
+  ...,
   names_repair = "check_unique",
   id_cols = NULL,
   values_fill = NULL,
@@ -18,6 +19,7 @@ build_wider_spec(
   data,
   names_from = name,
   values_from = value,
+  ...,
   names_prefix = "",
   names_sep = "_",
   names_glue = NULL,
@@ -38,6 +40,8 @@ pivoted from the wide format.
 The special \code{.seq} variable is used to disambiguate rows internally;
 it is automatically removed after pivotting.}
 
+\item{...}{Additional arguments passed on to methods.}
+
 \item{names_repair}{What happens if the output has invalid column names?
 The default, \code{"check_unique"} is to error if the columns are duplicated.
 Use \code{"minimal"} to allow duplicates in the output, or \code{"unique"} to
diff --git a/man/uncount.Rd b/man/uncount.Rd
index 4ea97eb93..459d9f1bf 100644
--- a/man/uncount.Rd
+++ b/man/uncount.Rd
@@ -4,7 +4,7 @@
 \alias{uncount}
 \title{"Uncount" a data frame}
 \usage{
-uncount(data, weights, .remove = TRUE, .id = NULL)
+uncount(data, weights, ..., .remove = TRUE, .id = NULL)
 }
 \arguments{
 \item{data}{A data frame, tibble, or grouped tibble.}
@@ -12,6 +12,8 @@ uncount(data, weights, .remove = TRUE, .id = NULL)
 \item{weights}{A vector of weights. Evaluated in the context of \code{data};
 supports quasiquotation.}
 
+\item{...}{Additional arguments passed on to methods.}
+
 \item{.remove}{If \code{TRUE}, and \code{weights} is the name of a column in \code{data},
 then this column is removed.}