diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
index 17efced74..b2a69e549 100644
--- a/.github/workflows/R-CMD-check.yaml
+++ b/.github/workflows/R-CMD-check.yaml
@@ -1,7 +1,10 @@
 on:
   push:
+    branches:
+      - master
   pull_request:
-    types: [opened, synchronize, reopened]
+    branches:
+      - master
 
 name: R-CMD-check
 
@@ -18,7 +21,7 @@ jobs:
           - {os: macOS-latest,   r: 'release'}
           - {os: windows-latest, r: 'release'}
           - {os: windows-latest, r: '3.6'}
-          - {os: ubuntu-16.04,   r: 'devel', rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
+          - {os: ubuntu-16.04,   r: 'devel', rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest", http-user-agent: "R/4.0.0 (ubuntu-16.04) R (4.0.0 x86_64-pc-linux-gnu x86_64 linux-gnu) on GitHub Actions" }
           - {os: ubuntu-16.04,   r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: 'oldrel',  rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
           - {os: ubuntu-16.04,   r: '3.5',     rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"}
@@ -34,6 +37,7 @@ jobs:
       - uses: r-lib/actions/setup-r@master
         with:
           r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
 
       - uses: r-lib/actions/setup-pandoc@master
 
@@ -79,7 +83,7 @@ jobs:
         run: |
           reticulate::conda_create('r-reticulate', packages = c('python==3.6.9'))
           tensorflow::install_tensorflow(version='1.14.0')
-        shell: Rscript {0}
+        shell: Rscript {0}        
 
       - name: Session info
         run: |
diff --git a/NAMESPACE b/NAMESPACE
index d238df397..87169f197 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -168,6 +168,7 @@ export(set_model_mode)
 export(set_new_model)
 export(set_pred)
 export(show_call)
+export(show_engines)
 export(show_fit)
 export(show_model_info)
 export(surv_reg)
diff --git a/NEWS.md b/NEWS.md
index 8a5fc3ef0..adb9b6db8 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,7 @@
 # parsnip (development version)
 
+* `show_engines()` will provide information on the current set for a model. 
+
 # parsnip 0.1.3
 
  * A `glance()` method for `model_fit` objects was added (#325)
diff --git a/R/boost_tree.R b/R/boost_tree.R
index d3f1cc31d..a005dbb64 100644
--- a/R/boost_tree.R
+++ b/R/boost_tree.R
@@ -62,6 +62,8 @@
 #' \item \pkg{Spark}: `"spark"`
 #' }
 #'
+#' For this model, other packages may add additional engines. Use
+#' [show_engines()] to see the current set of engines.
 #'
 #' @includeRmd man/rmd/boost-tree.Rmd details
 #'
@@ -81,6 +83,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()], [set_engine()]
 #' @examples
+#' show_engines("boost_tree")
+#'
 #' boost_tree(mode = "classification", trees = 20)
 #' # Parameters can be represented by a placeholder:
 #' boost_tree(mode = "regression", mtry = varying())
diff --git a/R/decision_tree.R b/R/decision_tree.R
index 5c518771f..015501971 100644
--- a/R/decision_tree.R
+++ b/R/decision_tree.R
@@ -62,6 +62,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()]
 #' @examples
+#' show_engines("decision_tree")
+#'
 #' decision_tree(mode = "classification", tree_depth = 5)
 #' # Parameters can be represented by a placeholder:
 #' decision_tree(mode = "regression", cost_complexity = varying())
diff --git a/R/engines.R b/R/engines.R
index f1ad8a3ec..20593dc9e 100644
--- a/R/engines.R
+++ b/R/engines.R
@@ -106,3 +106,24 @@ set_engine <- function(object, engine, ...) {
     engine = object$engine
   )
 }
+
+#' Display available engines for a model
+#'
+#' The possible engines for a model may depend on what packages are loaded. There
+#' are some `parsnip`-adjacent packages that only add engines to existing models.
+#' @param x The name of a `parsnip` model (e.g., "linear_reg", "mars", etc.)
+#' @return A tibble.
+#' show_engines("linear_reg")
+#' @export
+show_engines <- function(x) {
+  if (!is.character(x) || length(x) > 1) {
+    rlang::abort("`show_engines()` takes a single character string as input.")
+  }
+  res <- try(get_from_env(x), silent = TRUE)
+  if (inherits(res, "try-error")) {
+    rlang::abort(
+      paste0("No results found for model function '", x, "'.")
+    )
+  }
+  res
+}
diff --git a/R/linear_reg.R b/R/linear_reg.R
index 619a3c761..0839f4132 100644
--- a/R/linear_reg.R
+++ b/R/linear_reg.R
@@ -42,6 +42,9 @@
 #' \item \pkg{keras}: `"keras"`
 #' }
 #'
+#' For this model, other packages may add additional engines. Use
+#' [show_engines()] to see the current set of engines.
+#'
 #' @includeRmd man/rmd/linear-reg.Rmd details
 #'
 #' @note For models created using the spark engine, there are
@@ -59,6 +62,8 @@
 #'
 #' @seealso [fit()], [set_engine()]
 #' @examples
+#' show_engines("linear_reg")
+#'
 #' linear_reg()
 #' # Parameters can be represented by a placeholder:
 #' linear_reg(penalty = varying())
diff --git a/R/logistic_reg.R b/R/logistic_reg.R
index 049a19685..c8bf93c6e 100644
--- a/R/logistic_reg.R
+++ b/R/logistic_reg.R
@@ -40,6 +40,9 @@
 #' \item \pkg{keras}: `"keras"`
 #' }
 #'
+#' For this model, other packages may add additional engines. Use
+#' [show_engines()] to see the current set of engines.
+#'
 #' @includeRmd man/rmd/logistic-reg.Rmd details
 #'
 #' @note For models created using the spark engine, there are
@@ -57,6 +60,8 @@
 #'
 #' @seealso [fit()]
 #' @examples
+#' show_engines("logistic_reg")
+#'
 #' logistic_reg()
 #' # Parameters can be represented by a placeholder:
 #' logistic_reg(penalty = varying())
diff --git a/R/mars.R b/R/mars.R
index 1e68efb95..276ff82f7 100644
--- a/R/mars.R
+++ b/R/mars.R
@@ -41,6 +41,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()]
 #' @examples
+#' show_engines("mars")
+#'
 #' mars(mode = "regression", num_terms = 5)
 #' @export
 mars <-
diff --git a/R/mlp.R b/R/mlp.R
index 422e1fcd3..bee75a322 100644
--- a/R/mlp.R
+++ b/R/mlp.R
@@ -56,6 +56,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()]
 #' @examples
+#' show_engines("mlp")
+#'
 #' mlp(mode = "classification", penalty = 0.01)
 #' # Parameters can be represented by a placeholder:
 #' mlp(mode = "regression", hidden_units = varying())
diff --git a/R/multinom_reg.R b/R/multinom_reg.R
index 48310ca48..1bcd4525b 100644
--- a/R/multinom_reg.R
+++ b/R/multinom_reg.R
@@ -56,6 +56,8 @@
 #'
 #' @seealso [fit()]
 #' @examples
+#' show_engines("multinom_reg")
+#'
 #' multinom_reg()
 #' # Parameters can be represented by a placeholder:
 #' multinom_reg(penalty = varying())
diff --git a/R/nearest_neighbor.R b/R/nearest_neighbor.R
index 6988697a6..37b953596 100644
--- a/R/nearest_neighbor.R
+++ b/R/nearest_neighbor.R
@@ -51,6 +51,8 @@
 #' @seealso [fit()]
 #'
 #' @examples
+#' show_engines("nearest_neighbor")
+#'
 #' nearest_neighbor(neighbors = 11)
 #'
 #' @export
diff --git a/R/rand_forest.R b/R/rand_forest.R
index 98177eae5..1f018ec19 100644
--- a/R/rand_forest.R
+++ b/R/rand_forest.R
@@ -56,6 +56,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()]
 #' @examples
+#' show_engines("rand_forest")
+#'
 #' rand_forest(mode = "classification", trees = 2000)
 #' # Parameters can be represented by a placeholder:
 #' rand_forest(mode = "regression", mtry = varying())
diff --git a/R/surv_reg.R b/R/surv_reg.R
index cced97abf..d775ff399 100644
--- a/R/surv_reg.R
+++ b/R/surv_reg.R
@@ -45,6 +45,8 @@
 #' @references Jackson, C. (2016). `flexsurv`: A Platform for Parametric Survival
 #'  Modeling in R. _Journal of Statistical Software_, 70(8), 1 - 33.
 #' @examples
+#' show_engines("surv_reg")
+#'
 #' surv_reg()
 #' # Parameters can be represented by a placeholder:
 #' surv_reg(dist = varying())
diff --git a/R/svm_poly.R b/R/svm_poly.R
index 5edc8c631..087af9b79 100644
--- a/R/svm_poly.R
+++ b/R/svm_poly.R
@@ -41,6 +41,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()]
 #' @examples
+#' show_engines("svm_poly")
+#'
 #' svm_poly(mode = "classification", degree = 1.2)
 #' # Parameters can be represented by a placeholder:
 #' svm_poly(mode = "regression", cost = varying())
diff --git a/R/svm_rbf.R b/R/svm_rbf.R
index 52503f72a..e64abee70 100644
--- a/R/svm_rbf.R
+++ b/R/svm_rbf.R
@@ -42,6 +42,8 @@
 #' @importFrom purrr map_lgl
 #' @seealso [fit()]
 #' @examples
+#' show_engines("svm_rbf")
+#'
 #' svm_rbf(mode = "classification", rbf_sigma = 0.2)
 #' # Parameters can be represented by a placeholder:
 #' svm_rbf(mode = "regression", cost = varying())
diff --git a/man/boost_tree.Rd b/man/boost_tree.Rd
index af7fbf2ff..d3904ca93 100644
--- a/man/boost_tree.Rd
+++ b/man/boost_tree.Rd
@@ -117,6 +117,9 @@ following \emph{engines}:
 \item \pkg{R}:  \code{"xgboost"} (the default), \code{"C5.0"}
 \item \pkg{Spark}: \code{"spark"}
 }
+
+For this model, other packages may add additional engines. Use
+\code{\link[=show_engines]{show_engines()}} to see the current set of engines.
 }
 \note{
 For models created using the spark engine, there are
@@ -178,6 +181,10 @@ mod_param <-
   update(sample_size = sample_prop(c(0.4, 0.9)))
 }\if{html}{\out{</div>}}
 
+For this engine, tuning over \code{trees} is very efficient since the same
+model object can be used to make predictions over multiple values of
+\code{trees}.
+
 Finally, note that \code{xgboost} models require that non-numeric predictors
 (e.g., factors) must be converted to dummy variables or some other
 numeric representation. By default, when using \code{fit()} with \code{xgboost}, a
@@ -201,6 +208,10 @@ Note that \code{\link[C50:C5.0]{C50::C5.0()}} does not require factor
 predictors to be converted to indicator variables. \code{fit()} does not
 affect the encoding of the predictor values (i.e. factors stay factors)
 for this model.
+
+For this engine, tuning over \code{trees} is very efficient since the same
+model object can be used to make predictions over multiple values of
+\code{trees}.
 }
 
 \subsection{spark}{\if{html}{\out{<div class="r">}}\preformatted{boost_tree() \%>\% 
@@ -256,6 +267,8 @@ regression.
 }
 
 \examples{
+show_engines("boost_tree")
+
 boost_tree(mode = "classification", trees = 20)
 # Parameters can be represented by a placeholder:
 boost_tree(mode = "regression", mtry = varying())
diff --git a/man/decision_tree.Rd b/man/decision_tree.Rd
index f18144657..88c495752 100644
--- a/man/decision_tree.Rd
+++ b/man/decision_tree.Rd
@@ -189,6 +189,8 @@ parameter.\tabular{llll}{
 }
 
 \examples{
+show_engines("decision_tree")
+
 decision_tree(mode = "classification", tree_depth = 5)
 # Parameters can be represented by a placeholder:
 decision_tree(mode = "regression", cost_complexity = varying())
diff --git a/man/linear_reg.Rd b/man/linear_reg.Rd
index a11abb402..5eb262d0f 100644
--- a/man/linear_reg.Rd
+++ b/man/linear_reg.Rd
@@ -74,6 +74,9 @@ following \emph{engines}:
 \item \pkg{Spark}: \code{"spark"}
 \item \pkg{keras}: \code{"keras"}
 }
+
+For this model, other packages may add additional engines. Use
+\code{\link[=show_engines]{show_engines()}} to see the current set of engines.
 }
 \note{
 For models created using the spark engine, there are
@@ -195,6 +198,8 @@ parameter.\tabular{llll}{
 }
 
 \examples{
+show_engines("linear_reg")
+
 linear_reg()
 # Parameters can be represented by a placeholder:
 linear_reg(penalty = varying())
diff --git a/man/logistic_reg.Rd b/man/logistic_reg.Rd
index fcee139bd..4bba6a7ac 100644
--- a/man/logistic_reg.Rd
+++ b/man/logistic_reg.Rd
@@ -72,6 +72,9 @@ following \emph{engines}:
 \item \pkg{Spark}: \code{"spark"}
 \item \pkg{keras}: \code{"keras"}
 }
+
+For this model, other packages may add additional engines. Use
+\code{\link[=show_engines]{show_engines()}} to see the current set of engines.
 }
 \note{
 For models created using the spark engine, there are
@@ -194,6 +197,8 @@ parameter.\tabular{llll}{
 }
 
 \examples{
+show_engines("logistic_reg")
+
 logistic_reg()
 # Parameters can be represented by a placeholder:
 logistic_reg(penalty = varying())
diff --git a/man/mars.Rd b/man/mars.Rd
index e8cb16234..b8534ce28 100644
--- a/man/mars.Rd
+++ b/man/mars.Rd
@@ -110,6 +110,10 @@ attached.
 
 Also, \code{fit()} passes the data directly to \code{earth::earth()} so that its
 formula method can create dummy variables as-needed.
+
+For this engine, tuning over \code{num_terms} is very efficient since the
+same model object can be used to make predictions over multiple values
+of \code{num_terms}.
 }
 
 \subsection{Parameter translations}{
@@ -128,6 +132,8 @@ parameter.\tabular{ll}{
 }
 
 \examples{
+show_engines("mars")
+
 mars(mode = "regression", num_terms = 5)
 model <- mars(num_terms = 10, prune_method = "none")
 model
diff --git a/man/mlp.Rd b/man/mlp.Rd
index ed6b1087a..6b5e00a01 100644
--- a/man/mlp.Rd
+++ b/man/mlp.Rd
@@ -176,6 +176,8 @@ parameter.\tabular{lll}{
 }
 
 \examples{
+show_engines("mlp")
+
 mlp(mode = "classification", penalty = 0.01)
 # Parameters can be represented by a placeholder:
 mlp(mode = "regression", hidden_units = varying())
diff --git a/man/multinom_reg.Rd b/man/multinom_reg.Rd
index 895a9d51a..954dd3089 100644
--- a/man/multinom_reg.Rd
+++ b/man/multinom_reg.Rd
@@ -170,6 +170,8 @@ parameter.\tabular{lllll}{
 }
 
 \examples{
+show_engines("multinom_reg")
+
 multinom_reg()
 # Parameters can be represented by a placeholder:
 multinom_reg(penalty = varying())
diff --git a/man/nearest_neighbor.Rd b/man/nearest_neighbor.Rd
index d4dd84df1..86513d55a 100644
--- a/man/nearest_neighbor.Rd
+++ b/man/nearest_neighbor.Rd
@@ -88,6 +88,10 @@ version of \code{train.kknn()} and not \code{kknn()}. It is set up in this way s
 that \code{parsnip} can utilize the underlying \code{predict.train.kknn} method to
 predict on new data. This also means that a single value of that
 function’s \code{kernel} argument (a.k.a \code{weight_func} here) can be supplied
+
+For this engine, tuning over \code{neighbors} is very efficient since the
+same model object can be used to make predictions over multiple values
+of \code{neighbors}.
 }
 
 \subsection{Parameter translations}{
@@ -106,6 +110,8 @@ parameter.\tabular{ll}{
 }
 
 \examples{
+show_engines("nearest_neighbor")
+
 nearest_neighbor(neighbors = 11)
 
 }
diff --git a/man/rand_forest.Rd b/man/rand_forest.Rd
index 03380a213..a42e01664 100644
--- a/man/rand_forest.Rd
+++ b/man/rand_forest.Rd
@@ -206,6 +206,8 @@ classification and 5 for regression.
 }
 
 \examples{
+show_engines("rand_forest")
+
 rand_forest(mode = "classification", trees = 2000)
 # Parameters can be represented by a placeholder:
 rand_forest(mode = "regression", mtry = varying())
diff --git a/man/rmd/boost-tree.Rmd b/man/rmd/boost-tree.Rmd
index dae9e5156..b99b8ada5 100644
--- a/man/rmd/boost-tree.Rmd
+++ b/man/rmd/boost-tree.Rmd
@@ -38,6 +38,9 @@ mod_param <-
   update(sample_size = sample_prop(c(0.4, 0.9)))
 ```
 
+For this engine, tuning over `trees` is very efficient since the same model 
+object can be used to make predictions over multiple values of `trees`.  
+
 Finally, note that `xgboost` models require that non-numeric predictors (e.g., factors) must be converted to dummy variables or some other numeric representation. By default, when using `fit()` with `xgboost`, a one-hot encoding is used to convert factor predictors to indicator variables. 
 
 
@@ -52,6 +55,9 @@ boost_tree() %>%
 
 Note that [C50::C5.0()] does not require factor predictors to be converted  to indicator variables. `fit()` does not affect the encoding of the predictor values (i.e. factors stay factors) for this model.
 
+For this engine, tuning over `trees` is very efficient since the same model 
+object can be used to make predictions over multiple values of `trees`.  
+
 ## spark
 
 ```{r spark-reg}
diff --git a/man/rmd/mars.Rmd b/man/rmd/mars.Rmd
index d0976f697..88ab12440 100644
--- a/man/rmd/mars.Rmd
+++ b/man/rmd/mars.Rmd
@@ -26,6 +26,8 @@ Note that, when the model is fit, the `earth` package only has its  namespace lo
 
 Also, `fit()` passes the data directly to `earth::earth()` so that its formula method can create dummy variables as-needed. 
 
+For this engine, tuning over `num_terms` is very efficient since the same model 
+object can be used to make predictions over multiple values of `num_terms`.  
 
 ## Parameter translations
 
diff --git a/man/rmd/nearest-neighbor.Rmd b/man/rmd/nearest-neighbor.Rmd
index 002b9c8d6..14d0dd352 100644
--- a/man/rmd/nearest-neighbor.Rmd
+++ b/man/rmd/nearest-neighbor.Rmd
@@ -27,6 +27,9 @@ utilize the underlying `predict.train.kknn` method to predict on new data. This
 also means that a single value of that function's `kernel` argument (a.k.a
 `weight_func` here) can be supplied
 
+For this engine, tuning over `neighbors` is very efficient since the same model 
+object can be used to make predictions over multiple values of `neighbors`. 
+
 ## Parameter translations
 
 The standardized parameter names in parsnip can be mapped to their original 
diff --git a/man/show_engines.Rd b/man/show_engines.Rd
new file mode 100644
index 000000000..69d0a52db
--- /dev/null
+++ b/man/show_engines.Rd
@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/engines.R
+\name{show_engines}
+\alias{show_engines}
+\title{Display available engines for a model}
+\usage{
+show_engines(x)
+}
+\arguments{
+\item{x}{The name of a \code{parsnip} model (e.g., "linear_reg", "mars", etc.)}
+}
+\value{
+A tibble.
+show_engines("linear_reg")
+}
+\description{
+The possible engines for a model may depend on what packages are loaded. There
+are some \code{parsnip}-adjacent packages that only add engines to existing models.
+}
diff --git a/man/surv_reg.Rd b/man/surv_reg.Rd
index f65dcd705..a087ef1c2 100644
--- a/man/surv_reg.Rd
+++ b/man/surv_reg.Rd
@@ -117,6 +117,8 @@ parameter.\tabular{lll}{
 }
 
 \examples{
+show_engines("surv_reg")
+
 surv_reg()
 # Parameters can be represented by a placeholder:
 surv_reg(dist = varying())
diff --git a/man/svm_poly.Rd b/man/svm_poly.Rd
index 147ebdf99..489fb477b 100644
--- a/man/svm_poly.Rd
+++ b/man/svm_poly.Rd
@@ -125,6 +125,8 @@ parameter.\tabular{ll}{
 }
 
 \examples{
+show_engines("svm_poly")
+
 svm_poly(mode = "classification", degree = 1.2)
 # Parameters can be represented by a placeholder:
 svm_poly(mode = "regression", cost = varying())
diff --git a/man/svm_rbf.Rd b/man/svm_rbf.Rd
index 7b93e64ba..53827252d 100644
--- a/man/svm_rbf.Rd
+++ b/man/svm_rbf.Rd
@@ -156,6 +156,8 @@ parameter.\tabular{lll}{
 }
 
 \examples{
+show_engines("svm_rbf")
+
 svm_rbf(mode = "classification", rbf_sigma = 0.2)
 # Parameters can be represented by a placeholder:
 svm_rbf(mode = "regression", cost = varying())
diff --git a/tests/testthat/test_linear_reg.R b/tests/testthat/test_linear_reg.R
index ca304d0ea..312e73b78 100644
--- a/tests/testthat/test_linear_reg.R
+++ b/tests/testthat/test_linear_reg.R
@@ -371,3 +371,10 @@ test_that('default engine', {
   expect_true(inherits(fit$fit, "lm"))
 })
 
+test_that('show engine', {
+  res <- show_engines("linear_reg")
+  expt <- get_from_env("linear_reg")
+  expect_equal(res, expt)
+  expect_error(show_engines("linear_re"), "No results found for model function")
+})
+