diff --git a/R/tailor.R b/R/tailor.R
index 9abc314..bb69383 100644
--- a/R/tailor.R
+++ b/R/tailor.R
@@ -19,9 +19,6 @@
 #' with the [tidymodels](https://tidymodels.org) framework; for greatest ease
 #' of use, situate tailors in model workflows with `?workflows::add_tailor()`.
 #'
-#' @param type Character. The model sub-mode. Possible values are
-#' `"unknown"`, `"regression"`, `"binary"`, or `"multiclass"`. Only required
-#' when used independently of `?workflows::add_tailor()`.
 #' @param outcome <[`tidy-select`][dplyr::dplyr_tidy_select]> Only required
 #' when used independently of `?workflows::add_tailor()`, and can also be passed
 #' at `fit()` time instead. The column name of the outcome variable.
@@ -64,18 +61,16 @@
 #' # adjust hard class predictions
 #' predict(tlr_fit, two_class_example) %>% count(predicted)
 #' @export
-tailor <- function(type = "unknown", outcome = NULL, estimate = NULL,
-                      probabilities = NULL) {
+tailor <- function(outcome = NULL, estimate = NULL, probabilities = NULL) {
   columns <-
     list(
       outcome = outcome,
-      type = type,
       estimate = estimate,
       probabilities = probabilities
     )
 
   new_tailor(
-    type,
+    "unknown",
     adjustments = list(),
     columns = columns,
     ptype = tibble::new_tibble(list()),
@@ -84,8 +79,6 @@ tailor <- function(type = "unknown", outcome = NULL, estimate = NULL,
 }
 
 new_tailor <- function(type, adjustments, columns, ptype, call) {
-  type <- arg_match0(type, c("unknown", "regression", "binary", "multiclass"))
-
   if (!is.list(adjustments)) {
     cli_abort("The {.arg adjustments} argument should be a list.", call = call)
   }
@@ -97,8 +90,14 @@ new_tailor <- function(type, adjustments, columns, ptype, call) {
                    {.val adjustment}: {bad_adjustment}.", call = call)
   }
 
+  orderings <- adjustment_orderings(adjustments)
+
+  if (type == "unknown") {
+    type <- infer_type(orderings)
+  }
+
   # validate adjustment order and check duplicates
-  validate_order(adjustments, type, call)
+  validate_order(orderings, type, call)
 
   # check columns
   res <- list(
@@ -233,5 +232,5 @@ set_tailor_type <- function(object, y) {
 # todo setup eval_time
 # todo missing methods:
 # todo tune_args
-# todo tidy
+# todo tidy (this should probably just be `adjustment_orderings()`)
 # todo extract_parameter_set_dials
diff --git a/R/utils.R b/R/utils.R
index 4207cb5..483b4a0 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -88,6 +88,19 @@ tailor_adjustment_requires_fit <- function(x) {
   isTRUE(x$requires_fit)
 }
 
+# an tidy-esque method for adjustment lists, used in validating
+# compatibility of adjustments
+adjustment_orderings <- function(adjustments) {
+  tibble::new_tibble(list(
+    name = purrr::map_chr(adjustments, ~ class(.x)[1]),
+    input = purrr::map_chr(adjustments, ~ .x$inputs),
+    output_numeric = purrr::map_lgl(adjustments, ~ grepl("numeric", .x$outputs)),
+    output_prob = purrr::map_lgl(adjustments, ~ grepl("probability", .x$outputs)),
+    output_class = purrr::map_lgl(adjustments, ~ grepl("class", .x$outputs)),
+    output_all = purrr::map_lgl(adjustments, ~ grepl("everything", .x$outputs))
+  ))
+}
+
 # ad-hoc checking --------------------------------------------------------------
 check_tailor <- function(x, calibration_type = NULL, call = caller_env(), arg = caller_arg(x)) {
   if (!is_tailor(x)) {
diff --git a/R/validation-rules.R b/R/validation-rules.R
index fac8129..022f224 100644
--- a/R/validation-rules.R
+++ b/R/validation-rules.R
@@ -1,21 +1,9 @@
-validate_order <- function(adjustments, type, call = caller_env()) {
-  orderings <-
-    tibble::new_tibble(list(
-      name = purrr::map_chr(adjustments, ~ class(.x)[1]),
-      input = purrr::map_chr(adjustments, ~ .x$inputs),
-      output_numeric = purrr::map_lgl(adjustments, ~ grepl("numeric", .x$outputs)),
-      output_prob = purrr::map_lgl(adjustments, ~ grepl("probability", .x$outputs)),
-      output_class = purrr::map_lgl(adjustments, ~ grepl("class", .x$outputs)),
-      output_all = purrr::map_lgl(adjustments, ~ grepl("everything", .x$outputs))
-    ))
-
-  if (length(adjustments) < 2) {
+validate_order <- function(orderings, type, call = caller_env()) {
+  if (nrow(orderings) < 2) {
     return(invisible(orderings))
   }
 
-  if (type == "unknown") {
-    type <- infer_type(orderings)
-  }
+  check_incompatible_types(orderings, call)
 
   switch(
     type,
@@ -27,6 +15,24 @@ validate_order <- function(adjustments, type, call = caller_env()) {
   invisible(orderings)
 }
 
+check_incompatible_types <- function(orderings, call) {
+  if (all(c("numeric", "probability") %in% orderings$input)) {
+    numeric_adjustments <- orderings$name[which(orderings$input == "numeric")]
+    probability_adjustments <- orderings$name[which(orderings$input == "probability")]
+    cli_abort(
+      c(
+        "Can't compose adjustments for different prediction types.",
+        "i" = "{cli::qty(numeric_adjustments)}
+               Adjustment{?s} {.fn {paste0('adjust_', numeric_adjustments)}}
+               {cli::qty(numeric_adjustments[-1])} operate{?s} on numerics while
+               {.fn {paste0('adjust_', probability_adjustments)}}
+               {cli::qty(probability_adjustments[-1])} operate{?s} on probabilities."
+      ),
+      call = call
+    )
+  }
+}
+
 check_classification_order <- function(x, call) {
   cal_ind <- which(grepl("calibration$", x$name))
   eq_ind <- which(grepl("equivocal", x$name))
diff --git a/man/tailor.Rd b/man/tailor.Rd
index b0c6ac4..41763fb 100644
--- a/man/tailor.Rd
+++ b/man/tailor.Rd
@@ -4,13 +4,9 @@
 \alias{tailor}
 \title{Declare post-processing for model predictions}
 \usage{
-tailor(type = "unknown", outcome = NULL, estimate = NULL, probabilities = NULL)
+tailor(outcome = NULL, estimate = NULL, probabilities = NULL)
 }
 \arguments{
-\item{type}{Character. The model sub-mode. Possible values are
-\code{"unknown"}, \code{"regression"}, \code{"binary"}, or \code{"multiclass"}. Only required
-when used independently of \code{?workflows::add_tailor()}.}
-
 \item{outcome}{<\code{\link[dplyr:dplyr_tidy_select]{tidy-select}}> Only required
 when used independently of \code{?workflows::add_tailor()}, and can also be passed
 at \code{fit()} time instead. The column name of the outcome variable.}
diff --git a/tests/testthat/_snaps/adjust-equivocal-zone.md b/tests/testthat/_snaps/adjust-equivocal-zone.md
index 314da8c..0427c70 100644
--- a/tests/testthat/_snaps/adjust-equivocal-zone.md
+++ b/tests/testthat/_snaps/adjust-equivocal-zone.md
@@ -5,7 +5,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A binary postprocessor with 1 adjustment:
       
       * Add equivocal zone of size 0.1.
 
@@ -16,7 +16,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A binary postprocessor with 1 adjustment:
       
       * Add equivocal zone of optimized size.
 
diff --git a/tests/testthat/_snaps/adjust-numeric-calibration.md b/tests/testthat/_snaps/adjust-numeric-calibration.md
index 6f3bd2f..3e9baa9 100644
--- a/tests/testthat/_snaps/adjust-numeric-calibration.md
+++ b/tests/testthat/_snaps/adjust-numeric-calibration.md
@@ -5,7 +5,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A regression postprocessor with 1 adjustment:
       
       * Re-calibrate numeric predictions.
 
@@ -20,15 +20,7 @@
 ---
 
     Code
-      tailor("binary") %>% adjust_numeric_calibration("linear")
-    Condition
-      Error in `adjust_numeric_calibration()`:
-      ! A binary tailor is incompatible with the adjustment `adjust_numeric_calibration()`.
-
----
-
-    Code
-      tailor("regression") %>% adjust_numeric_calibration("binary")
+      tailor() %>% adjust_numeric_calibration("binary")
     Condition
       Error in `adjust_numeric_calibration()`:
       ! `method` must be one of "linear", "isotonic", or "isotonic_boot", not "binary".
diff --git a/tests/testthat/_snaps/adjust-numeric-range.md b/tests/testthat/_snaps/adjust-numeric-range.md
index 050da3b..1daaeec 100644
--- a/tests/testthat/_snaps/adjust-numeric-range.md
+++ b/tests/testthat/_snaps/adjust-numeric-range.md
@@ -5,7 +5,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A regression postprocessor with 1 adjustment:
       
       * Constrain numeric predictions to be between [-Inf, Inf].
 
@@ -16,7 +16,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A regression postprocessor with 1 adjustment:
       
       * Constrain numeric predictions to be between [?, Inf].
 
@@ -27,7 +27,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A regression postprocessor with 1 adjustment:
       
       * Constrain numeric predictions to be between [-1, ?].
 
@@ -38,7 +38,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A regression postprocessor with 1 adjustment:
       
       * Constrain numeric predictions to be between [?, 1].
 
diff --git a/tests/testthat/_snaps/adjust-probability-calibration.md b/tests/testthat/_snaps/adjust-probability-calibration.md
index e814d17..432ea81 100644
--- a/tests/testthat/_snaps/adjust-probability-calibration.md
+++ b/tests/testthat/_snaps/adjust-probability-calibration.md
@@ -5,7 +5,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A binary postprocessor with 1 adjustment:
       
       * Re-calibrate classification probabilities.
 
@@ -20,15 +20,7 @@
 ---
 
     Code
-      tailor("regression") %>% adjust_probability_calibration("binary")
-    Condition
-      Error in `adjust_probability_calibration()`:
-      ! A regression tailor is incompatible with the adjustment `adjust_probability_calibration()`.
-
----
-
-    Code
-      tailor("binary") %>% adjust_probability_calibration("linear")
+      tailor() %>% adjust_probability_calibration("linear")
     Condition
       Error in `adjust_probability_calibration()`:
       ! `method` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "linear".
diff --git a/tests/testthat/_snaps/adjust-probability-threshold.md b/tests/testthat/_snaps/adjust-probability-threshold.md
index d5a1475..0cf3857 100644
--- a/tests/testthat/_snaps/adjust-probability-threshold.md
+++ b/tests/testthat/_snaps/adjust-probability-threshold.md
@@ -5,7 +5,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A binary postprocessor with 1 adjustment:
       
       * Adjust probability threshold to 0.5.
 
@@ -16,7 +16,7 @@
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A postprocessor with 1 adjustment:
+      A binary postprocessor with 1 adjustment:
       
       * Adjust probability threshold to optimized value.
 
diff --git a/tests/testthat/_snaps/tailor.md b/tests/testthat/_snaps/tailor.md
index ddf992c..438907b 100644
--- a/tests/testthat/_snaps/tailor.md
+++ b/tests/testthat/_snaps/tailor.md
@@ -10,16 +10,16 @@
 ---
 
     Code
-      tailor(type = "binary")
+      tailor()
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A binary postprocessor with 0 adjustments.
+      A postprocessor with 0 adjustments.
 
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_probability_threshold(0.2)
+      tailor() %>% adjust_probability_threshold(0.2)
     Message
       
       -- tailor ----------------------------------------------------------------------
@@ -30,8 +30,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_probability_threshold(0.2) %>%
-        adjust_equivocal_zone()
+      tailor() %>% adjust_probability_threshold(0.2) %>% adjust_equivocal_zone()
     Message
       
       -- tailor ----------------------------------------------------------------------
diff --git a/tests/testthat/_snaps/validation-rules.md b/tests/testthat/_snaps/validation-rules.md
index 287ca17..cb63223 100644
--- a/tests/testthat/_snaps/validation-rules.md
+++ b/tests/testthat/_snaps/validation-rules.md
@@ -1,7 +1,7 @@
 # validation of adjustments (regression)
 
     Code
-      tailor(type = "regression") %>% adjust_numeric_range(lower_limit = 2) %>%
+      tailor() %>% adjust_numeric_range(lower_limit = 2) %>%
         adjust_numeric_calibration() %>% adjust_predictions_custom(squared = .pred^2)
     Condition
       Error in `adjust_numeric_calibration()`:
@@ -10,7 +10,7 @@
 # validation of adjustments (classification)
 
     Code
-      tailor(type = "binary") %>% adjust_probability_threshold(threshold = 0.4) %>%
+      tailor() %>% adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_calibration()
     Condition
       Error in `adjust_probability_calibration()`:
@@ -28,7 +28,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_predictions_custom(veg = "potato") %>%
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
         adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_calibration()
     Condition
@@ -48,7 +48,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_predictions_custom(veg = "potato") %>%
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
         adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_threshold(threshold = 0.5) %>%
         adjust_probability_calibration()
@@ -70,7 +70,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_equivocal_zone(value = 0.2) %>%
+      tailor() %>% adjust_equivocal_zone(value = 0.2) %>%
         adjust_probability_threshold(threshold = 0.4)
     Condition
       Error in `adjust_probability_threshold()`:
@@ -85,3 +85,65 @@
       Error in `adjust_probability_threshold()`:
       ! Equivocal zone addition should come after adjustments that update the class probability estimates or hard class predictions.
 
+# validation of adjustments (incompatible types)
+
+    Code
+      tailor() %>% adjust_numeric_calibration() %>% adjust_probability_threshold()
+    Condition
+      Error in `adjust_probability_threshold()`:
+      ! Can't compose adjustments for different prediction types.
+      i Adjustment `adjust_numeric_calibration()` operates on numerics while `adjust_probability_threshold()` operates on probabilities.
+
+---
+
+    Code
+      tailor() %>% adjust_probability_calibration("logistic") %>%
+        adjust_probability_threshold(threshold = 0.4) %>% adjust_numeric_range(
+        lower_limit = 2)
+    Condition
+      Error in `adjust_numeric_range()`:
+      ! Can't compose adjustments for different prediction types.
+      i Adjustment `adjust_numeric_range()` operates on numerics while `adjust_probability_calibration()` and `adjust_probability_threshold()` operate on probabilities.
+
+---
+
+    Code
+      tailor() %>% adjust_numeric_calibration() %>% adjust_numeric_range(lower_limit = 2) %>%
+        adjust_probability_threshold(threshold = 0.4)
+    Condition
+      Error in `adjust_probability_threshold()`:
+      ! Can't compose adjustments for different prediction types.
+      i Adjustments `adjust_numeric_calibration()` and `adjust_numeric_range()` operate on numerics while `adjust_probability_threshold()` operates on probabilities.
+
+---
+
+    Code
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
+        adjust_numeric_calibration() %>% adjust_probability_threshold()
+    Condition
+      Error in `adjust_probability_threshold()`:
+      ! Can't compose adjustments for different prediction types.
+      i Adjustment `adjust_numeric_calibration()` operates on numerics while `adjust_probability_threshold()` operates on probabilities.
+
+---
+
+    Code
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
+        adjust_probability_calibration("logistic") %>% adjust_probability_threshold(
+        threshold = 0.4) %>% adjust_numeric_range(lower_limit = 2)
+    Condition
+      Error in `adjust_numeric_range()`:
+      ! Can't compose adjustments for different prediction types.
+      i Adjustment `adjust_numeric_range()` operates on numerics while `adjust_probability_calibration()` and `adjust_probability_threshold()` operate on probabilities.
+
+---
+
+    Code
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
+        adjust_numeric_calibration() %>% adjust_numeric_range(lower_limit = 2) %>%
+        adjust_probability_threshold(threshold = 0.4)
+    Condition
+      Error in `adjust_probability_threshold()`:
+      ! Can't compose adjustments for different prediction types.
+      i Adjustments `adjust_numeric_calibration()` and `adjust_numeric_range()` operate on numerics while `adjust_probability_threshold()` operates on probabilities.
+
diff --git a/tests/testthat/test-adjust-numeric-calibration.R b/tests/testthat/test-adjust-numeric-calibration.R
index 703b201..20e0534 100644
--- a/tests/testthat/test-adjust-numeric-calibration.R
+++ b/tests/testthat/test-adjust-numeric-calibration.R
@@ -44,11 +44,7 @@ test_that("errors informatively with bad input", {
   expect_snapshot(error = TRUE, adjust_numeric_calibration(tailor(), "boop"))
   expect_snapshot(
     error = TRUE,
-    tailor("binary") %>% adjust_numeric_calibration("linear")
-  )
-  expect_snapshot(
-    error = TRUE,
-    tailor("regression") %>% adjust_numeric_calibration("binary")
+    tailor() %>% adjust_numeric_calibration("binary")
   )
 
   expect_no_condition(adjust_numeric_calibration(tailor()))
diff --git a/tests/testthat/test-adjust-probability-calibration.R b/tests/testthat/test-adjust-probability-calibration.R
index a19cd90..09d82bc 100644
--- a/tests/testthat/test-adjust-probability-calibration.R
+++ b/tests/testthat/test-adjust-probability-calibration.R
@@ -54,11 +54,7 @@ test_that("errors informatively with bad input", {
   expect_snapshot(error = TRUE, adjust_probability_calibration(tailor(), "boop"))
   expect_snapshot(
     error = TRUE,
-    tailor("regression") %>% adjust_probability_calibration("binary")
-  )
-  expect_snapshot(
-    error = TRUE,
-    tailor("binary") %>% adjust_probability_calibration("linear")
+    tailor() %>% adjust_probability_calibration("linear")
   )
 
   expect_no_condition(adjust_numeric_calibration(tailor()))
diff --git a/tests/testthat/test-tailor.R b/tests/testthat/test-tailor.R
index 0c45150..e951e87 100644
--- a/tests/testthat/test-tailor.R
+++ b/tests/testthat/test-tailor.R
@@ -1,12 +1,12 @@
 test_that("tailor printing", {
   expect_snapshot(tailor())
-  expect_snapshot(tailor(type = "binary"))
+  expect_snapshot(tailor())
   expect_snapshot(
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_probability_threshold(.2)
   )
   expect_snapshot(
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_probability_threshold(.2) %>%
       adjust_equivocal_zone()
   )
diff --git a/tests/testthat/test-validation-rules.R b/tests/testthat/test-validation-rules.R
index 4a50c22..77168e2 100644
--- a/tests/testthat/test-validation-rules.R
+++ b/tests/testthat/test-validation-rules.R
@@ -1,7 +1,7 @@
 test_that("validation of adjustments (regression)", {
   expect_no_condition(
     reg_tailor <-
-      tailor(type = "regression") %>%
+      tailor() %>%
       adjust_numeric_calibration() %>%
       adjust_numeric_range(lower_limit = 2) %>%
       adjust_predictions_custom(squared = .pred^2)
@@ -9,7 +9,7 @@ test_that("validation of adjustments (regression)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "regression") %>%
+    tailor() %>%
       adjust_numeric_range(lower_limit = 2) %>%
       adjust_numeric_calibration() %>%
       adjust_predictions_custom(squared = .pred^2)
@@ -19,7 +19,7 @@ test_that("validation of adjustments (regression)", {
   # modifies the prediction?
   expect_no_condition(
     reg_tailor <-
-      tailor(type = "regression") %>%
+      tailor() %>%
       adjust_predictions_custom(squared = .pred^2) %>%
       adjust_numeric_calibration() %>%
       adjust_numeric_range(lower_limit = 2)
@@ -29,14 +29,14 @@ test_that("validation of adjustments (regression)", {
 test_that("validation of adjustments (classification)", {
   expect_no_condition(
     cls_tailor_1 <-
-      tailor(type = "binary") %>%
+      tailor() %>%
       adjust_probability_calibration("logistic") %>%
       adjust_probability_threshold(threshold = .4)
   )
 
   expect_no_condition(
     cls_tailor_2 <-
-      tailor(type = "binary") %>%
+      tailor() %>%
       adjust_predictions_custom(starch = "potato") %>%
       adjust_predictions_custom(veg = "green beans") %>%
       adjust_probability_calibration("logistic") %>%
@@ -45,7 +45,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_calibration()
   )
@@ -59,7 +59,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_calibration()
@@ -75,7 +75,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_threshold(threshold = .5) %>%
@@ -93,7 +93,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_equivocal_zone(value = .2) %>%
       adjust_probability_threshold(threshold = .4)
   )
@@ -116,3 +116,75 @@ test_that("validation of adjustments (ambiguous type)", {
 
   expect_equal(ambiguous_tailor$type, "unknown")
 })
+
+test_that("validation of adjustments (incompatible types)", {
+  # one bad adjustment each
+  expect_snapshot(
+    error = TRUE,
+    tailor() %>%
+      adjust_numeric_calibration() %>%
+      adjust_probability_threshold()
+  )
+
+  # varying the pluralization...
+  expect_snapshot(
+    error = TRUE,
+    tailor() %>%
+      adjust_probability_calibration("logistic") %>%
+      adjust_probability_threshold(threshold = .4) %>%
+      adjust_numeric_range(lower_limit = 2)
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    tailor() %>%
+      adjust_numeric_calibration() %>%
+      adjust_numeric_range(lower_limit = 2) %>%
+      adjust_probability_threshold(threshold = .4)
+  )
+
+  # ensure that mixing in ambiguous adjustments doesn't cause issues
+  expect_snapshot(
+    error = TRUE,
+    tailor() %>%
+      adjust_predictions_custom(veg = "potato") %>%
+      adjust_numeric_calibration() %>%
+      adjust_probability_threshold()
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    tailor() %>%
+      adjust_predictions_custom(veg = "potato") %>%
+      adjust_probability_calibration("logistic") %>%
+      adjust_probability_threshold(threshold = .4) %>%
+      adjust_numeric_range(lower_limit = 2)
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    tailor() %>%
+      adjust_predictions_custom(veg = "potato") %>%
+      adjust_numeric_calibration() %>%
+      adjust_numeric_range(lower_limit = 2) %>%
+      adjust_probability_threshold(threshold = .4)
+  )
+
+  expect_no_condition(
+    tailor() %>%
+      adjust_predictions_custom(veg = "potato") %>%
+      adjust_numeric_calibration()
+  )
+
+  expect_no_condition(
+    tailor() %>%
+      adjust_numeric_calibration() %>%
+      adjust_predictions_custom(veg = "potato")
+  )
+
+  expect_no_condition(
+    tailor() %>%
+      adjust_probability_threshold(threshold = .4) %>%
+      adjust_predictions_custom(veg = "potato")
+  )
+})