diff --git a/DESCRIPTION b/DESCRIPTION
index 1c1a08492..bfa80fed1 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 1.2.1.9000
+Version: 1.2.1.9001
 Authors@R: c(
     person("Max", "Kuhn", , "max@posit.co", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "davis@posit.co", role = "aut"),
diff --git a/R/bag_tree.R b/R/bag_tree.R
index d36997083..e80fc200a 100644
--- a/R/bag_tree.R
+++ b/R/bag_tree.R
@@ -85,9 +85,7 @@ update.bag_tree <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.bag_tree <- function(object) {
-  if (object$engine == "C5.0" && object$mode == "regression")
-    stop("C5.0 is classification only.", call. = FALSE)
+check_args.bag_tree <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
 
diff --git a/R/boost_tree.R b/R/boost_tree.R
index c7227eadc..799afee1e 100644
--- a/R/boost_tree.R
+++ b/R/boost_tree.R
@@ -164,23 +164,15 @@ translate.boost_tree <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.boost_tree <- function(object) {
+check_args.boost_tree <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$trees) && args$trees < 0) {
-    rlang::abort("`trees` should be >= 1.")
-  }
-  if (is.numeric(args$sample_size) && (args$sample_size < 0 | args$sample_size > 1)) {
-    rlang::abort("`sample_size` should be within [0,1].")
-  }
-  if (is.numeric(args$tree_depth) && args$tree_depth < 0) {
-    rlang::abort("`tree_depth` should be >= 1.")
-  }
-  if (is.numeric(args$min_n) && args$min_n < 0) {
-    rlang::abort("`min_n` should be >= 1.")
-  }
-
+  check_number_whole(args$trees, min = 0, allow_null = TRUE, call = call, arg = "trees")
+  check_number_decimal(args$sample_size, min = 0, max = 1, allow_null = TRUE, call = call, arg = "sample_size")
+  check_number_whole(args$tree_depth, min = 0, allow_null = TRUE, call = call, arg = "tree_depth")
+  check_number_whole(args$min_n, min = 0, allow_null = TRUE, call = call, arg = "min_n")
+  
   invisible(object)
 }
 
diff --git a/R/c5_rules.R b/R/c5_rules.R
index 7e5040f5d..904e2cb56 100644
--- a/R/c5_rules.R
+++ b/R/c5_rules.R
@@ -111,32 +111,23 @@ update.C5_rules <-
 # make work in different places
 
 #' @export
-check_args.C5_rules <- function(object) {
+check_args.C5_rules <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$trees)) {
-    if (length(args$trees) > 1) {
-      rlang::abort("Only a single value of `trees` is used.")
-    }
-    msg <- "The number of trees should be >= 1 and <= 100. Truncating the value."
-    if (args$trees > 100) {
-      object$args$trees <-
-        rlang::new_quosure(100L, env = rlang::empty_env())
-      rlang::warn(msg)
-    }
-    if (args$trees < 1) {
-      object$args$trees <-
-        rlang::new_quosure(1L, env = rlang::empty_env())
-      rlang::warn(msg)
-    }
+  check_number_whole(args$min_n, allow_null = TRUE, call = call, arg = "min_n")
+  check_number_whole(args$tree, allow_null = TRUE, call = call, arg = "tree")
 
+  msg <- "The number of trees should be {.code >= 1} and {.code <= 100}"
+  if (!(is.null(args$trees)) && args$trees > 100) {
+    object$args$trees <- rlang::new_quosure(100L, env = rlang::empty_env())
+    cli::cli_warn(c(msg, "Truncating to 100."))
   }
-  if (is.numeric(args$min_n)) {
-    if (length(args$min_n) > 1) {
-      rlang::abort("Only a single `min_n`` value is used.")
-    }
+  if (!(is.null(args$trees)) && args$trees < 1) {
+    object$args$trees <- rlang::new_quosure(1L, env = rlang::empty_env())
+    cli::cli_warn(c(msg, "Truncating to 1."))
   }
+
   invisible(object)
 }
 
diff --git a/R/cubist_rules.R b/R/cubist_rules.R
index 5273a2665..a8cc5407c 100644
--- a/R/cubist_rules.R
+++ b/R/cubist_rules.R
@@ -135,44 +135,36 @@ update.cubist_rules <-
 # make work in different places
 
 #' @export
-check_args.cubist_rules <- function(object) {
+check_args.cubist_rules <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$committees)) {
-    if (length(args$committees) > 1) {
-      rlang::abort("Only a single committee member is used.")
-    }
-    msg <- "The number of committees should be >= 1 and <= 100. Truncating the value."
-    if (args$committees > 100) {
-      object$args$committees <-
-        rlang::new_quosure(100L, env = rlang::empty_env())
-      rlang::warn(msg)
-    }
-    if (args$committees < 1) {
-      object$args$committees <-
-        rlang::new_quosure(1L, env = rlang::empty_env())
-      rlang::warn(msg)
-    }
+  check_number_whole(args$committees, allow_null = TRUE, call = call, arg = "committees")
 
-  }
-  if (is.numeric(args$neighbors)) {
-    if (length(args$neighbors) > 1) {
-      rlang::abort("Only a single neighbors value is used.")
-    }
-    msg <- "The number of neighbors should be >= 0 and <= 9. Truncating the value."
-    if (args$neighbors > 9) {
-      object$args$neighbors <-
-        rlang::new_quosure(9L, env = rlang::empty_env())
-      rlang::warn(msg)
-    }
-    if (args$neighbors < 0) {
-      object$args$neighbors <-
-        rlang::new_quosure(0L, env = rlang::empty_env())
-      rlang::warn(msg)
+  msg <- "The number of committees should be {.code >= 1} and {.code <= 100}."
+  if (!(is.null(args$committees)) && args$committees > 100) {
+    object$args$committees <-
+      rlang::new_quosure(100L, env = rlang::empty_env())
+      cli::cli_warn(c(msg, "Truncating to 100."))
     }
+  if (!(is.null(args$committees)) && args$committees < 1) {
+    object$args$committees <-
+      rlang::new_quosure(1L, env = rlang::empty_env())
+      cli::cli_warn(c(msg, "Truncating to 1."))
+  }
+
+  check_number_whole(args$neighbors, allow_null = TRUE, call = call, arg = "neighbors")
 
+  msg <- "The number of neighbors should be {.code >= 0} and {.code <= 9}."
+  if (!(is.null(args$neighbors)) && args$neighbors > 9) {
+    object$args$neighbors <- rlang::new_quosure(9L, env = rlang::empty_env())
+    cli::cli_warn(c(msg, "Truncating to 9."))
   }
+  if (!(is.null(args$neighbors)) && args$neighbors < 0) {
+    object$args$neighbors <- rlang::new_quosure(0L, env = rlang::empty_env())
+    cli::cli_warn(c(msg, "Truncating to 0."))
+  }
+
   invisible(object)
 }
 
diff --git a/R/decision_tree.R b/R/decision_tree.R
index 98c13d26a..8266fe806 100644
--- a/R/decision_tree.R
+++ b/R/decision_tree.R
@@ -128,9 +128,7 @@ translate.decision_tree <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.decision_tree <- function(object) {
-  if (object$engine == "C5.0" && object$mode == "regression")
-    rlang::abort("C5.0 is classification only.")
+check_args.decision_tree <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
 
diff --git a/R/discrim_flexible.R b/R/discrim_flexible.R
index 0f5c0162c..8b2826b1a 100644
--- a/R/discrim_flexible.R
+++ b/R/discrim_flexible.R
@@ -85,21 +85,14 @@ update.discrim_flexible <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.discrim_flexible <- function(object) {
+check_args.discrim_flexible <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$prod_degree) && args$prod_degree < 0)
-    stop("`prod_degree` should be >= 1", call. = FALSE)
-
-  if (is.numeric(args$num_terms) && args$num_terms < 0)
-    stop("`num_terms` should be >= 1", call. = FALSE)
-
-  if (!is.character(args$prune_method) &&
-      !is.null(args$prune_method) &&
-      !is.character(args$prune_method))
-    stop("`prune_method` should be a single string value", call. = FALSE)
-
+  check_number_whole(args$prod_degree, min = 1, allow_null = TRUE, call = call, arg = "prod_degree")
+  check_number_whole(args$num_terms, min = 1, allow_null = TRUE, call = call, arg = "num_terms")
+  check_string(args$prune_method, allow_empty = FALSE, allow_null = TRUE, call = call, arg = "prune_method")
+  
   invisible(object)
 }
 
diff --git a/R/discrim_linear.R b/R/discrim_linear.R
index 54d618a9c..22eff4ea5 100644
--- a/R/discrim_linear.R
+++ b/R/discrim_linear.R
@@ -80,13 +80,11 @@ update.discrim_linear <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.discrim_linear <- function(object) {
+check_args.discrim_linear <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (all(is.numeric(args$penalty)) && any(args$penalty < 0)) {
-    stop("The amount of regularization should be >= 0", call. = FALSE)
-  }
+  check_number_decimal(args$penalty, min = 0, allow_null = TRUE, call = call, arg = "penalty")
 
   invisible(object)
 }
diff --git a/R/discrim_regularized.R b/R/discrim_regularized.R
index ddf327d22..e6f209c4c 100644
--- a/R/discrim_regularized.R
+++ b/R/discrim_regularized.R
@@ -95,18 +95,13 @@ update.discrim_regularized <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.discrim_regularized <- function(object) {
+check_args.discrim_regularized <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$frac_common_cov) &&
-      (args$frac_common_cov < 0 | args$frac_common_cov > 1)) {
-    stop("The common covariance fraction should be between zero and one", call. = FALSE)
-  }
-  if (is.numeric(args$frac_identity) &&
-      (args$frac_identity < 0 | args$frac_identity > 1)) {
-    stop("The identity matrix fraction should be between zero and one", call. = FALSE)
-  }
+  check_number_decimal(args$frac_common_cov, min = 0, max = 1, allow_null = TRUE, call = call, arg = "frac_common_cov")
+  check_number_decimal(args$frac_identity, min = 0, max = 1, allow_null = TRUE, call = call, arg = "frac_identity")
+  
   invisible(object)
 }
 
diff --git a/R/fit_helpers.R b/R/fit_helpers.R
index 29002a41d..7e2437434 100644
--- a/R/fit_helpers.R
+++ b/R/fit_helpers.R
@@ -4,7 +4,7 @@
 # data to formula/data objects and so on.
 
 form_form <-
-  function(object, control, env, ...) {
+  function(object, control, env, ..., call = rlang::caller_env()) {
 
     if (inherits(env$data, "data.frame")) {
       check_outcome(eval_tidy(rlang::f_lhs(env$formula), env$data), object)
@@ -32,7 +32,7 @@ form_form <-
     }
 
     # evaluate quoted args once here to check them
-    object <- check_args(object)
+    object <- check_args(object, call = call)
 
     # sub in arguments to actual syntax for corresponding engine
     object <- translate(object, engine = object$engine)
@@ -60,7 +60,12 @@ form_form <-
     res
   }
 
-xy_xy <- function(object, env, control, target = "none", ...) {
+xy_xy <- function(object, 
+                  env, 
+                  control, 
+                  target = "none", 
+                  ..., 
+                  call = rlang::caller_env()) {
 
   if (inherits(env$x, "tbl_spark") | inherits(env$y, "tbl_spark"))
     rlang::abort("spark objects can only be used with the formula interface to `fit()`")
@@ -83,7 +88,7 @@ xy_xy <- function(object, env, control, target = "none", ...) {
   }
 
   # evaluate quoted args once here to check them
-  object <- check_args(object)
+  object <- check_args(object, call = call)
 
   # sub in arguments to actual syntax for corresponding engine
   object <- translate(object, engine = object$engine)
@@ -114,7 +119,7 @@ xy_xy <- function(object, env, control, target = "none", ...) {
 }
 
 form_xy <- function(object, control, env,
-                    target = "none", ...) {
+                    target = "none", ..., call = rlang::caller_env()) {
 
   encoding_info <-
     get_encoding(class(object)[1]) %>%
@@ -138,7 +143,8 @@ form_xy <- function(object, control, env,
     object = object,
     env = env, #weights!
     control = control,
-    target = target
+    target = target,
+    call = call
   )
   data_obj$y_var <- all.vars(rlang::f_lhs(env$formula))
   data_obj$x <- NULL
diff --git a/R/linear_reg.R b/R/linear_reg.R
index 0d4625223..0b7b636b4 100644
--- a/R/linear_reg.R
+++ b/R/linear_reg.R
@@ -106,16 +106,12 @@ update.linear_reg <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.linear_reg <- function(object) {
+check_args.linear_reg <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (all(is.numeric(args$penalty)) && any(args$penalty < 0))
-    rlang::abort("The amount of regularization should be >= 0.")
-  if (is.numeric(args$mixture) && (args$mixture < 0 | args$mixture > 1))
-    rlang::abort("The mixture proportion should be within [0,1].")
-  if (is.numeric(args$mixture) && length(args$mixture) > 1)
-    rlang::abort("Only one value of `mixture` is allowed.")
+  check_number_decimal(args$mixture, min = 0, max = 1, allow_null = TRUE, call = call, arg = "mixture")
+  check_number_decimal(args$penalty, min = 0, allow_null = TRUE, call = call, arg = "penalty")
 
   invisible(object)
 }
diff --git a/R/logistic_reg.R b/R/logistic_reg.R
index 58b5de93e..40ccf5dc5 100644
--- a/R/logistic_reg.R
+++ b/R/logistic_reg.R
@@ -135,25 +135,32 @@ update.logistic_reg <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.logistic_reg <- function(object) {
+check_args.logistic_reg <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (all(is.numeric(args$penalty)) && any(args$penalty < 0))
-    rlang::abort("The amount of regularization should be >= 0.")
-  if (is.numeric(args$mixture) && (args$mixture < 0 | args$mixture > 1))
-    rlang::abort("The mixture proportion should be within [0,1].")
-  if (is.numeric(args$mixture) && length(args$mixture) > 1)
-    rlang::abort("Only one value of `mixture` is allowed.")
+  check_number_decimal(args$mixture, min = 0, max = 1, allow_null = TRUE, call = call, arg = "mixture")
+  check_number_decimal(args$penalty, min = 0, allow_null = TRUE, call = call, arg = "penalty")
 
   if (object$engine == "LiblineaR") {
-    if(is.numeric(args$mixture) && !args$mixture %in% 0:1)
-      rlang::abort(c("For the LiblineaR engine, mixture must be 0 or 1.",
-                     "Choose a pure ridge model with `mixture = 0`.",
-                     "Choose a pure lasso model with `mixture = 1`.",
-                     "The Liblinear engine does not support other values."))
-    if(all(is.numeric(args$penalty)) && !all(args$penalty > 0))
-      rlang::abort("For the LiblineaR engine, penalty must be > 0.")
+    if (is.numeric(args$mixture) && !args$mixture %in% 0:1) {
+      cli::cli_abort(
+        c("x" = "For the {.pkg LiblineaR} engine, mixture must be 0 or 1, \\
+                not {args$mixture}.",
+          "i" = "Choose a pure ridge model with {.code mixture = 0} or \\
+                a pure lasso model with {.code mixture = 1}.",
+          "!" = "The {.pkg Liblinear} engine does not support other values."),
+        call = call
+      )
+    }
+    
+    if ((!is.null(args$penalty)) && args$penalty == 0) {
+      cli::cli_abort(
+        "For the {.pkg LiblineaR} engine, {.arg penalty} must be {.code > 0}, \\
+         not 0.",
+        call = call
+      )
+    }
   }
 
   invisible(object)
diff --git a/R/mars.R b/R/mars.R
index 59e4f0f63..f4ad10ae7 100644
--- a/R/mars.R
+++ b/R/mars.R
@@ -105,20 +105,13 @@ translate.mars <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.mars <- function(object) {
+check_args.mars <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$prod_degree) && args$prod_degree < 0)
-    rlang::abort("`prod_degree` should be >= 1.")
-
-  if (is.numeric(args$num_terms) && args$num_terms < 0)
-    rlang::abort("`num_terms` should be >= 1.")
-
-  if (!is_varying(args$prune_method) &&
-      !is.null(args$prune_method) &&
-      !is.character(args$prune_method))
-    rlang::abort("`prune_method` should be a single string value.")
+  check_number_whole(args$prod_degree, min = 1, allow_null = TRUE, call = call, arg = "prod_degree")
+  check_number_whole(args$num_terms, min = 1, allow_null = TRUE, call = call, arg = "num_terms")
+  check_string(args$prune_method, allow_empty = FALSE, allow_null = TRUE, call = call, arg = "prune_method")
 
   invisible(object)
 }
diff --git a/R/misc.R b/R/misc.R
index fa591aecc..b564870fd 100644
--- a/R/misc.R
+++ b/R/misc.R
@@ -285,12 +285,12 @@ show_fit <- function(model, eng) {
 #' @export
 #' @keywords internal
 #' @rdname add_on_exports
-check_args <- function(object) {
+check_args <- function(object, call = rlang::caller_env()) {
   UseMethod("check_args")
 }
 
 #' @export
-check_args.default <- function(object) {
+check_args.default <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
 
diff --git a/R/mlp.R b/R/mlp.R
index 8b5ba1b59..fa3cf097c 100644
--- a/R/mlp.R
+++ b/R/mlp.R
@@ -126,21 +126,20 @@ translate.mlp <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.mlp <- function(object) {
+check_args.mlp <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$penalty))
-    if (args$penalty < 0)
-      rlang::abort("The amount of weight decay must be >= 0.")
+  check_number_decimal(args$penalty, min = 0, allow_null = TRUE, call = call, arg = "penalty")
+  check_number_decimal(args$dropout, min = 0, max = 1, allow_null = TRUE, call = call, arg = "dropout")
 
-  if (is.numeric(args$dropout))
-    if (args$dropout < 0 | args$dropout >= 1)
-      rlang::abort("The dropout proportion must be on [0, 1).")
-
-  if (is.numeric(args$penalty) & is.numeric(args$dropout))
-    if (args$dropout > 0 & args$penalty > 0)
-      rlang::abort("Both weight decay and dropout should not be specified.")
+  if (is.numeric(args$penalty) && is.numeric(args$dropout) &&
+      args$dropout > 0 && args$penalty > 0) {
+    cli::cli_abort(
+      "Both weight decay and dropout should not be specified.",
+      call = call
+    )
+  }
 
   invisible(object)
 }
diff --git a/R/multinom_reg.R b/R/multinom_reg.R
index 8b0d887e0..1a8f0e8a1 100644
--- a/R/multinom_reg.R
+++ b/R/multinom_reg.R
@@ -100,14 +100,12 @@ update.multinom_reg <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.multinom_reg <- function(object) {
+check_args.multinom_reg <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (all(is.numeric(args$penalty)) && any(args$penalty < 0))
-    rlang::abort("The amount of regularization should be >= 0.")
-  if (is.numeric(args$mixture) && (args$mixture < 0 | args$mixture > 1))
-    rlang::abort("The mixture proportion should be within [0,1].")
+  check_number_decimal(args$mixture, min = 0, max = 1, allow_null = TRUE, call = call, arg = "mixture")
+  check_number_decimal(args$penalty, min = 0, allow_null = TRUE, call = call, arg = "penalty")
 
   invisible(object)
 }
diff --git a/R/nearest_neighbor.R b/R/nearest_neighbor.R
index 0976d2907..37daaea4c 100644
--- a/R/nearest_neighbor.R
+++ b/R/nearest_neighbor.R
@@ -90,26 +90,16 @@ update.nearest_neighbor <- function(object,
   )
 }
 
-
-positive_int_scalar <- function(x) {
-  (length(x) == 1) && (x > 0) && (x %% 1 == 0)
-}
-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.nearest_neighbor <- function(object) {
+check_args.nearest_neighbor <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$neighbors) && !positive_int_scalar(args$neighbors)) {
-    rlang::abort("`neighbors` must be a length 1 positive integer.")
-  }
-
-  if (is.character(args$weight_func) && length(args$weight_func) > 1) {
-    rlang::abort("The length of `weight_func` must be 1.")
-  }
-
+  check_number_whole(args$neighbors, min = 0, allow_null = TRUE, call = call, arg = "neighbors")
+  check_string(args$weight_func, allow_null = TRUE, call = call, arg = "weight_func")
+  
   invisible(object)
 }
 
diff --git a/R/pls.R b/R/pls.R
index c9eea560f..3a2bc13d7 100644
--- a/R/pls.R
+++ b/R/pls.R
@@ -87,13 +87,11 @@ update.pls <-
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.pls <- function(object) {
+check_args.pls <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (is.numeric(args$num_comp) && args$num_comp < 1) {
-    rlang::abort("`num_comp` should be >= 0.")
-  }
+  check_number_whole(args$num_comp, min = 0, allow_null = TRUE, call = call, arg = "num_comp")
 
   invisible(object)
 }
diff --git a/R/poisson_reg.R b/R/poisson_reg.R
index e538f29ee..e3201aca1 100644
--- a/R/poisson_reg.R
+++ b/R/poisson_reg.R
@@ -101,16 +101,12 @@ translate.poisson_reg <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.poisson_reg <- function(object) {
+check_args.poisson_reg <- function(object, call = rlang::caller_env()) {
 
   args <- lapply(object$args, rlang::eval_tidy)
 
-  if (all(is.numeric(args$penalty)) && any(args$penalty < 0))
-    rlang::abort("The amount of regularization should be >= 0.")
-  if (is.numeric(args$mixture) && (args$mixture < 0 | args$mixture > 1))
-    rlang::abort("The mixture proportion should be within [0,1].")
-  if (is.numeric(args$mixture) && length(args$mixture) > 1)
-    rlang::abort("Only one value of `mixture` is allowed.")
+  check_number_decimal(args$mixture, min = 0, max = 1, allow_null = TRUE, call = call, arg = "mixture")
+  check_number_decimal(args$penalty, min = 0, allow_null = TRUE, call = call, arg = "penalty")
 
   invisible(object)
 }
diff --git a/R/rand_forest.R b/R/rand_forest.R
index 425b9d9fb..2a6aed042 100644
--- a/R/rand_forest.R
+++ b/R/rand_forest.R
@@ -161,7 +161,7 @@ translate.rand_forest <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.rand_forest <- function(object) {
+check_args.rand_forest <- function(object, call = rlang::caller_env()) {
   # move translate checks here?
   invisible(object)
 }
diff --git a/R/surv_reg.R b/R/surv_reg.R
index e0d321536..85638840d 100644
--- a/R/surv_reg.R
+++ b/R/surv_reg.R
@@ -83,7 +83,7 @@ translate.surv_reg <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.surv_reg <- function(object) {
+check_args.surv_reg <- function(object, call = rlang::caller_env()) {
 
   if (object$engine == "flexsurv") {
 
diff --git a/R/survival_reg.R b/R/survival_reg.R
index 6b270d825..d34781ee9 100644
--- a/R/survival_reg.R
+++ b/R/survival_reg.R
@@ -82,7 +82,7 @@ translate.survival_reg <- function(x, engine = x$engine, ...) {
 }
 
 #' @export
-check_args.survival_reg <- function(object) {
+check_args.survival_reg <- function(object, call = rlang::caller_env()) {
 
   if (object$engine == "flexsurv") {
 
diff --git a/R/svm_linear.R b/R/svm_linear.R
index b888758f3..2548cd499 100644
--- a/R/svm_linear.R
+++ b/R/svm_linear.R
@@ -140,7 +140,7 @@ translate.svm_linear <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.svm_linear <- function(object) {
+check_args.svm_linear <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
 
diff --git a/R/svm_poly.R b/R/svm_poly.R
index 028a09294..4acd1afe8 100644
--- a/R/svm_poly.R
+++ b/R/svm_poly.R
@@ -134,7 +134,7 @@ translate.svm_poly <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.svm_poly <- function(object) {
+check_args.svm_poly <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
 
diff --git a/R/svm_rbf.R b/R/svm_rbf.R
index af6bde862..ba8abf272 100644
--- a/R/svm_rbf.R
+++ b/R/svm_rbf.R
@@ -139,7 +139,7 @@ translate.svm_rbf <- function(x, engine = x$engine, ...) {
 # ------------------------------------------------------------------------------
 
 #' @export
-check_args.svm_rbf <- function(object) {
+check_args.svm_rbf <- function(object, call = rlang::caller_env()) {
   invisible(object)
 }
 
diff --git a/man/add_on_exports.Rd b/man/add_on_exports.Rd
index 8ecfcdad4..69760d481 100644
--- a/man/add_on_exports.Rd
+++ b/man/add_on_exports.Rd
@@ -19,7 +19,7 @@ null_value(x)
 
 show_fit(model, eng)
 
-check_args(object)
+check_args(object, call = rlang::caller_env())
 
 update_dot_check(...)
 
diff --git a/tests/testthat/_snaps/boost_tree.md b/tests/testthat/_snaps/boost_tree.md
index 890681236..f84c5d509 100644
--- a/tests/testthat/_snaps/boost_tree.md
+++ b/tests/testthat/_snaps/boost_tree.md
@@ -15,3 +15,51 @@
       Computational engine: C5.0 
       
 
+# bad input
+
+    Code
+      boost_tree(mode = "bogus")
+    Condition
+      Error in `boost_tree()`:
+      ! "bogus" is not a known mode for model `boost_tree()`.
+
+# check_args() works
+
+    Code
+      spec <- boost_tree(trees = -1) %>% set_engine("xgboost") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `trees` must be a whole number larger than or equal to 0 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- boost_tree(sample_size = -10) %>% set_engine("xgboost") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `sample_size` must be a number between 0 and 1 or `NULL`, not the number -10.
+
+---
+
+    Code
+      spec <- boost_tree(tree_depth = -10) %>% set_engine("xgboost") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `tree_depth` must be a whole number larger than or equal to 0 or `NULL`, not the number -10.
+
+---
+
+    Code
+      spec <- boost_tree(min_n = -10) %>% set_engine("xgboost") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `min_n` must be a whole number larger than or equal to 0 or `NULL`, not the number -10.
+
diff --git a/tests/testthat/_snaps/linear_reg.md b/tests/testthat/_snaps/linear_reg.md
index 4626c9656..cce6764c5 100644
--- a/tests/testthat/_snaps/linear_reg.md
+++ b/tests/testthat/_snaps/linear_reg.md
@@ -23,3 +23,21 @@
       Error in `predict()`:
       ! Please use `new_data` instead of `newdata`.
 
+# check_args() works
+
+    Code
+      spec <- linear_reg(mixture = -1) %>% set_engine("lm") %>% set_mode("regression")
+      fit(spec, compounds ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `mixture` must be a number between 0 and 1 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- linear_reg(penalty = -1) %>% set_engine("lm") %>% set_mode("regression")
+      fit(spec, compounds ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `penalty` must be a number larger than or equal to 0 or `NULL`, not the number -1.
+
diff --git a/tests/testthat/_snaps/logistic_reg.md b/tests/testthat/_snaps/logistic_reg.md
index ed336d9e3..9bb671332 100644
--- a/tests/testthat/_snaps/logistic_reg.md
+++ b/tests/testthat/_snaps/logistic_reg.md
@@ -29,3 +29,45 @@
       Warning:
       glm.fit: fitted probabilities numerically 0 or 1 occurred
 
+# check_args() works
+
+    Code
+      spec <- logistic_reg(mixture = -1) %>% set_engine("glm") %>% set_mode(
+        "classification")
+      fit(spec, Class ~ ., lending_club)
+    Condition
+      Error in `fit()`:
+      ! `mixture` must be a number between 0 and 1 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- logistic_reg(penalty = -1) %>% set_engine("glm") %>% set_mode(
+        "classification")
+      fit(spec, Class ~ ., lending_club)
+    Condition
+      Error in `fit()`:
+      ! `penalty` must be a number larger than or equal to 0 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- logistic_reg(mixture = 0.5) %>% set_engine("LiblineaR") %>% set_mode(
+        "classification")
+      fit(spec, Class ~ ., lending_club)
+    Condition
+      Error in `fit()`:
+      x For the LiblineaR engine, mixture must be 0 or 1, not 0.5.
+      i Choose a pure ridge model with `mixture = 0` or a pure lasso model with `mixture = 1`.
+      ! The Liblinear engine does not support other values.
+
+---
+
+    Code
+      spec <- logistic_reg(penalty = 0) %>% set_engine("LiblineaR") %>% set_mode(
+        "classification")
+      fit(spec, Class ~ ., lending_club)
+    Condition
+      Error in `fit()`:
+      ! For the LiblineaR engine, `penalty` must be `> 0`, not 0.
+
diff --git a/tests/testthat/_snaps/mars.md b/tests/testthat/_snaps/mars.md
index a1596440e..64cc504a1 100644
--- a/tests/testthat/_snaps/mars.md
+++ b/tests/testthat/_snaps/mars.md
@@ -22,3 +22,33 @@
       Error in `multi_predict()`:
       ! Please use `new_data` instead of `newdata`.
 
+# check_args() works
+
+    Code
+      spec <- mars(prod_degree = 0) %>% set_engine("earth") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `prod_degree` must be a whole number larger than or equal to 1 or `NULL`, not the number 0.
+
+---
+
+    Code
+      spec <- mars(num_terms = 0) %>% set_engine("earth") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `num_terms` must be a whole number larger than or equal to 1 or `NULL`, not the number 0.
+
+---
+
+    Code
+      spec <- mars(prune_method = 2) %>% set_engine("earth") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `prune_method` must be a single string or `NULL`, not the number 2.
+
diff --git a/tests/testthat/_snaps/mlp.md b/tests/testthat/_snaps/mlp.md
index bfdd3bfb2..03b192b7a 100644
--- a/tests/testthat/_snaps/mlp.md
+++ b/tests/testthat/_snaps/mlp.md
@@ -15,3 +15,31 @@
       Computational engine: nnet 
       
 
+# check_args() works
+
+    Code
+      spec <- mlp(penalty = -1) %>% set_engine("keras") %>% set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `penalty` must be a number larger than or equal to 0 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- mlp(dropout = -1) %>% set_engine("keras") %>% set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `dropout` must be a number between 0 and 1 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- mlp(dropout = 1, penalty = 3) %>% set_engine("keras") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! Both weight decay and dropout should not be specified.
+
diff --git a/tests/testthat/_snaps/multinom_reg.md b/tests/testthat/_snaps/multinom_reg.md
index da29212d1..0f01bb547 100644
--- a/tests/testthat/_snaps/multinom_reg.md
+++ b/tests/testthat/_snaps/multinom_reg.md
@@ -15,3 +15,23 @@
       Computational engine: glmnet 
       
 
+# check_args() works
+
+    Code
+      spec <- multinom_reg(mixture = -1) %>% set_engine("keras") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `mixture` must be a number between 0 and 1 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- multinom_reg(penalty = -1) %>% set_engine("keras") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `penalty` must be a number larger than or equal to 0 or `NULL`, not the number -1.
+
diff --git a/tests/testthat/_snaps/nearest_neighbor.md b/tests/testthat/_snaps/nearest_neighbor.md
index c4d6d63f3..401c06c51 100644
--- a/tests/testthat/_snaps/nearest_neighbor.md
+++ b/tests/testthat/_snaps/nearest_neighbor.md
@@ -15,3 +15,23 @@
       Computational engine: kknn 
       
 
+# check_args() works
+
+    Code
+      spec <- nearest_neighbor(neighbors = -1) %>% set_engine("kknn") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `neighbors` must be a whole number larger than or equal to 0 or `NULL`, not the number -1.
+
+---
+
+    Code
+      spec <- nearest_neighbor(weight_func = 2) %>% set_engine("kknn") %>% set_mode(
+        "classification")
+      fit(spec, class ~ ., hpc)
+    Condition
+      Error in `fit()`:
+      ! `weight_func` must be a single string or `NULL`, not the number 2.
+
diff --git a/tests/testthat/test-bart.R b/tests/testthat/test-bart.R
new file mode 100644
index 000000000..162cb0d5c
--- /dev/null
+++ b/tests/testthat/test-bart.R
@@ -0,0 +1,4 @@
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})
diff --git a/tests/testthat/test_boost_tree.R b/tests/testthat/test_boost_tree.R
index f92216870..a099d64bf 100644
--- a/tests/testthat/test_boost_tree.R
+++ b/tests/testthat/test_boost_tree.R
@@ -11,15 +11,7 @@ test_that('updating', {
 })
 
 test_that('bad input', {
-  expect_error(boost_tree(mode = "bogus"))
-  expect_error({
-    bt <- boost_tree(trees = -1) %>% set_engine("xgboost")
-    fit(bt, class ~ ., hpc)
-  })
-  expect_error({
-    bt <- boost_tree(min_n = -10)  %>% set_engine("xgboost")
-    fit(bt, class ~ ., hpc)
-  })
+  expect_snapshot(error = TRUE, boost_tree(mode = "bogus"))
   expect_message(translate(boost_tree(mode = "classification"), engine = NULL))
   expect_error(translate(boost_tree(formula = y ~ x)))
 })
@@ -54,3 +46,44 @@ test_that('boost_tree can be fit with 1 predictor if validation is used', {
     fit(spec, mpg ~ disp, data = mtcars)
   )
 })
+
+test_that("check_args() works", {
+  skip_if_not_installed("xgboost")
+  
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- boost_tree(trees = -1) %>% 
+        set_engine("xgboost") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- boost_tree(sample_size = -10) %>% 
+        set_engine("xgboost") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- boost_tree(tree_depth = -10) %>% 
+        set_engine("xgboost") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- boost_tree(min_n = -10) %>% 
+        set_engine("xgboost") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+})
diff --git a/tests/testthat/test_decision_tree.R b/tests/testthat/test_decision_tree.R
index bb1391299..85dd3ac1f 100644
--- a/tests/testthat/test_decision_tree.R
+++ b/tests/testthat/test_decision_tree.R
@@ -69,3 +69,8 @@ test_that('argument checks for data dimensions', {
   expect_equal(args$min_instances_per_node,  rlang::expr(min_rows(1000, x)))
 
 })
+
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})
diff --git a/tests/testthat/test_gen_additive_model.R b/tests/testthat/test_gen_additive_model.R
index 3e58605a2..0b6a76ea8 100644
--- a/tests/testthat/test_gen_additive_model.R
+++ b/tests/testthat/test_gen_additive_model.R
@@ -98,3 +98,8 @@ test_that('classification', {
   expect_equal(f_ci[[".pred_lower_Class2"]], lower)
 
 })
+
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})
diff --git a/tests/testthat/test_linear_reg.R b/tests/testthat/test_linear_reg.R
index 21a93bae3..637ec8075 100644
--- a/tests/testthat/test_linear_reg.R
+++ b/tests/testthat/test_linear_reg.R
@@ -12,8 +12,6 @@ test_that('updating', {
 
 test_that('bad input', {
   expect_error(linear_reg(mode = "classification"))
-  # expect_error(linear_reg(penalty = -1))
-  # expect_error(linear_reg(mixture = -1))
   expect_error(translate(linear_reg(), engine = "wat?"))
   expect_error(translate(linear_reg(), engine = NULL))
   expect_error(translate(linear_reg(formula = y ~ x)))
@@ -342,3 +340,23 @@ test_that('lm can handle rankdeficient predictions', {
   expect_identical(names(preds), ".pred")
 })
 
+test_that("check_args() works", {
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- linear_reg(mixture = -1) %>% 
+        set_engine("lm") %>% 
+        set_mode("regression")
+      fit(spec, compounds ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- linear_reg(penalty = -1) %>% 
+        set_engine("lm") %>% 
+        set_mode("regression")
+      fit(spec, compounds ~ ., hpc)
+    }
+  )
+})
diff --git a/tests/testthat/test_logistic_reg.R b/tests/testthat/test_logistic_reg.R
index 8a6434747..3b46e023f 100644
--- a/tests/testthat/test_logistic_reg.R
+++ b/tests/testthat/test_logistic_reg.R
@@ -249,3 +249,41 @@ test_that('liblinear probabilities', {
 
 })
 
+test_that("check_args() works", {
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- logistic_reg(mixture = -1) %>% 
+        set_engine("glm") %>% 
+        set_mode("classification")
+      fit(spec, Class ~ ., lending_club)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- logistic_reg(penalty = -1) %>% 
+        set_engine("glm") %>% 
+        set_mode("classification")
+      fit(spec, Class ~ ., lending_club)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- logistic_reg(mixture = 0.5) %>% 
+        set_engine("LiblineaR") %>% 
+        set_mode("classification")
+      fit(spec, Class ~ ., lending_club)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- logistic_reg(penalty = 0) %>% 
+        set_engine("LiblineaR") %>% 
+        set_mode("classification")
+      fit(spec, Class ~ ., lending_club)
+    }
+  )
+})
diff --git a/tests/testthat/test_mars.R b/tests/testthat/test_mars.R
index dbd5a04fb..2a9d419cd 100644
--- a/tests/testthat/test_mars.R
+++ b/tests/testthat/test_mars.R
@@ -216,3 +216,35 @@ test_that('classification', {
 
   expect_equal(parsnip_pred$.pred_good, earth_pred)
 })
+
+test_that("check_args() works", {
+  skip_if_not_installed("earth")
+  
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- mars(prod_degree = 0) %>% 
+        set_engine("earth") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- mars(num_terms = 0) %>% 
+        set_engine("earth") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- mars(prune_method = 2) %>% 
+        set_engine("earth") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+})
diff --git a/tests/testthat/test_mlp.R b/tests/testthat/test_mlp.R
index ec9dafad9..4e9a52b4e 100644
--- a/tests/testthat/test_mlp.R
+++ b/tests/testthat/test_mlp.R
@@ -1,3 +1,4 @@
+hpc <- hpc_data[1:150, c(2:5, 8)]
 
 test_that('updating', {
   expect_snapshot(
@@ -48,3 +49,34 @@ test_that("more activations for brulee", {
   expect_true(inherits(fit$fit, "brulee_mlp"))
 })
 
+test_that("check_args() works", {
+  skip_if_not_installed("keras")
+
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- mlp(penalty = -1) %>% 
+        set_engine("keras") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- mlp(dropout = -1) %>% 
+        set_engine("keras") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- mlp(dropout = 1, penalty = 3) %>% 
+        set_engine("keras") %>% 
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+})
diff --git a/tests/testthat/test_multinom_reg.R b/tests/testthat/test_multinom_reg.R
index 18b25be9a..0cec39200 100644
--- a/tests/testthat/test_multinom_reg.R
+++ b/tests/testthat/test_multinom_reg.R
@@ -15,3 +15,26 @@ test_that('bad input', {
   expect_error(multinom_reg(penalty = 0.1) %>% set_engine())
   expect_warning(translate(multinom_reg(penalty = 0.1) %>% set_engine("glmnet", x = hpc[,1:3], y = hpc$class)))
 })
+
+test_that('check_args() works', {
+  skip_if_not_installed("keras")
+  
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- multinom_reg(mixture = -1) %>% 
+        set_engine("keras") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- multinom_reg(penalty = -1) %>% 
+        set_engine("keras") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+})
diff --git a/tests/testthat/test_nearest_neighbor.R b/tests/testthat/test_nearest_neighbor.R
index 784d957da..c834dc570 100644
--- a/tests/testthat/test_nearest_neighbor.R
+++ b/tests/testthat/test_nearest_neighbor.R
@@ -10,3 +10,28 @@ test_that('bad input', {
   expect_error(nearest_neighbor(mode = "reallyunknown"))
   expect_error(nearest_neighbor() %>% set_engine( NULL))
 })
+
+test_that('check_args() works', {
+  skip_if_not_installed("kknn")
+
+  hpc <- hpc_data[1:150, c(2:5, 8)]
+  
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- nearest_neighbor(neighbors = -1) %>% 
+        set_engine("kknn") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+  expect_snapshot(
+    error = TRUE,
+    {
+      spec <- nearest_neighbor(weight_func = 2) %>% 
+        set_engine("kknn") %>%
+        set_mode("classification")
+      fit(spec, class ~ ., hpc)
+    }
+  )
+})
diff --git a/tests/testthat/test_nullmodel.R b/tests/testthat/test_nullmodel.R
index 7b31c8a80..2f112c5f3 100644
--- a/tests/testthat/test_nullmodel.R
+++ b/tests/testthat/test_nullmodel.R
@@ -124,5 +124,7 @@ test_that('null_model printing', {
   )
 })
 
-
-
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})
diff --git a/tests/testthat/test_rand_forest.R b/tests/testthat/test_rand_forest.R
index e74b5e7c7..b05633146 100644
--- a/tests/testthat/test_rand_forest.R
+++ b/tests/testthat/test_rand_forest.R
@@ -14,3 +14,7 @@ test_that('bad input', {
   expect_error(translate(rand_forest(mode = "classification", ytest = 2)))
 })
 
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+}) 
diff --git a/tests/testthat/test_svm_linear.R b/tests/testthat/test_svm_linear.R
index 0b875c093..31c8bfc41 100644
--- a/tests/testthat/test_svm_linear.R
+++ b/tests/testthat/test_svm_linear.R
@@ -370,5 +370,7 @@ test_that('linear svm classification prediction: kernlab', {
 
 })
 
-
-
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})
diff --git a/tests/testthat/test_svm_poly.R b/tests/testthat/test_svm_poly.R
index 910bf978f..dda70dc52 100644
--- a/tests/testthat/test_svm_poly.R
+++ b/tests/testthat/test_svm_poly.R
@@ -185,3 +185,8 @@ test_that('svm poly classification probabilities', {
   parsnip_xy_probs <- predict(cls_xy_form, hpc_no_m[ind, -5], type = "prob")
   expect_equal(as.data.frame(kern_probs), as.data.frame(parsnip_xy_probs))
 })
+
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})
diff --git a/tests/testthat/test_svm_rbf.R b/tests/testthat/test_svm_rbf.R
index db9d5d1f5..8e0c4bc4c 100644
--- a/tests/testthat/test_svm_rbf.R
+++ b/tests/testthat/test_svm_rbf.R
@@ -195,4 +195,7 @@ test_that('svm rbf classification probabilities', {
   expect_equal(as.data.frame(kern_probs), as.data.frame(parsnip_xy_probs))
 })
 
-
+test_that("check_args() works", {
+  # Here for completeness, no checking is done
+  expect_true(TRUE)
+})