diff --git a/DESCRIPTION b/DESCRIPTION
index 747fa76..8d276a8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: container
 Title: Sandbox for a postprocessor object
-Version: 0.0.0.9000
+Version: 0.0.0.9001
 Authors@R: c(
     person("Simon", "Couch", , "simon.couch@posit.co", role = "aut"),
     person("Hannah", "Frick", , "hannah@posit.co", role = "aut"),
diff --git a/R/adjust-equivocal-zone.R b/R/adjust-equivocal-zone.R
index 6df78b8..8f785a1 100644
--- a/R/adjust-equivocal-zone.R
+++ b/R/adjust-equivocal-zone.R
@@ -9,7 +9,7 @@
 #' library(modeldata)
 #'
 #' post_obj <-
-#'   container(mode = "classification") %>%
+#'   container() %>%
 #'   adjust_equivocal_zone(value = 1 / 4)
 #'
 #'
@@ -43,7 +43,6 @@ adjust_equivocal_zone <- function(x, value = 0.1, threshold = 1 / 2) {
     )
 
   new_container(
-    mode = x$mode,
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
diff --git a/R/adjust-numeric-calibration.R b/R/adjust-numeric-calibration.R
index 19c3176..7e38327 100644
--- a/R/adjust-numeric-calibration.R
+++ b/R/adjust-numeric-calibration.R
@@ -1,7 +1,7 @@
 #' Re-calibrate numeric predictions
 #'
 #' @param x A [container()].
-#' @param type Character. One of `"linear"`, `"isotonic"`, or
+#' @param method Character. One of `"linear"`, `"isotonic"`, or
 #' `"isotonic_boot"`, corresponding to the function from the \pkg{probably}
 #' package [probably::cal_estimate_linear()],
 #' [probably::cal_estimate_isotonic()], or
@@ -19,21 +19,21 @@
 #'
 #' # specify calibration
 #' reg_ctr <-
-#'   container(mode = "regression") %>%
-#'   adjust_numeric_calibration(type = "linear")
+#'   container() %>%
+#'   adjust_numeric_calibration(method = "linear")
 #'
 #' # train container
 #' reg_ctr_trained <- fit(reg_ctr, dat, outcome = y, estimate = y_pred)
 #'
 #' predict(reg_ctr_trained, dat)
 #' @export
-adjust_numeric_calibration <- function(x, type = NULL) {
+adjust_numeric_calibration <- function(x, method = NULL) {
   # to-do: add argument specifying `prop` in initial_split
   check_container(x, calibration_type = "numeric")
-  # wait to `check_type()` until `fit()` time
-  if (!is.null(type)) {
+  # wait to `check_method()` until `fit()` time
+  if (!is.null(method)) {
     arg_match0(
-      type,
+      method,
       c("linear", "isotonic", "isotonic_boot")
     )
   }
@@ -43,13 +43,12 @@ adjust_numeric_calibration <- function(x, type = NULL) {
       "numeric_calibration",
       inputs = "numeric",
       outputs = "numeric",
-      arguments = list(type = type),
+      arguments = list(method = method),
       results = list(),
       trained = FALSE
     )
 
   new_container(
-    mode = x$mode,
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
@@ -67,13 +66,13 @@ print.numeric_calibration <- function(x, ...) {
 
 #' @export
 fit.numeric_calibration <- function(object, data, container = NULL, ...) {
-  type <- check_type(object$type, container$type)
+  method <- check_method(object$method, container$type)
   # todo: adjust_numeric_calibration() should take arguments to pass to
   # cal_estimate_* via dots
   fit <-
     eval_bare(
       call2(
-        paste0("cal_estimate_", type),
+        paste0("cal_estimate_", method),
         .data = data,
         truth = container$columns$outcome,
         estimate = container$columns$estimate,
diff --git a/R/adjust-numeric-range.R b/R/adjust-numeric-range.R
index 3a5e21c..49b77bb 100644
--- a/R/adjust-numeric-range.R
+++ b/R/adjust-numeric-range.R
@@ -19,7 +19,6 @@ adjust_numeric_range <- function(x, lower_limit = -Inf, upper_limit = Inf) {
     )
 
   new_container(
-    mode = x$mode,
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
diff --git a/R/adjust-predictions-custom.R b/R/adjust-predictions-custom.R
index 8b61ab9..ef8e7c4 100644
--- a/R/adjust-predictions-custom.R
+++ b/R/adjust-predictions-custom.R
@@ -9,7 +9,7 @@
 #' library(modeldata)
 #'
 #' post_obj <-
-#'   container(mode = "classification") %>%
+#'   container() %>%
 #'   adjust_equivocal_zone() %>%
 #'   adjust_predictions_custom(linear_predictor = binomial()$linkfun(Class2))
 #'
@@ -39,7 +39,6 @@ adjust_predictions_custom <- function(x, ..., .pkgs = character(0)) {
     )
 
   new_container(
-    mode = x$mode,
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
diff --git a/R/adjust-probability-calibration.R b/R/adjust-probability-calibration.R
index 6206d53..35ea6e3 100644
--- a/R/adjust-probability-calibration.R
+++ b/R/adjust-probability-calibration.R
@@ -1,18 +1,18 @@
 #' Re-calibrate classification probability predictions
 #'
 #' @param x A [container()].
-#' @param type Character. One of `"logistic"`, `"multinomial"`,
+#' @param method Character. One of `"logistic"`, `"multinomial"`,
 #' `"beta"`, `"isotonic"`, or `"isotonic_boot"`, corresponding to the
 #' function from the \pkg{probably} package [probably::cal_estimate_logistic()],
 #' [probably::cal_estimate_multinomial()], etc., respectively.
 #' @export
-adjust_probability_calibration <- function(x, type = NULL) {
+adjust_probability_calibration <- function(x, method = NULL) {
   # to-do: add argument specifying `prop` in initial_split
   check_container(x, calibration_type = "probability")
-  # wait to `check_type()` until `fit()` time
-  if (!is.null(type)) {
+  # wait to `check_method()` until `fit()` time
+  if (!is.null(method)) {
     arg_match(
-      type,
+      method,
       c("logistic", "multinomial", "beta", "isotonic", "isotonic_boot")
     )
   }
@@ -22,13 +22,12 @@ adjust_probability_calibration <- function(x, type = NULL) {
       "probability_calibration",
       inputs = "probability",
       outputs = "probability_class",
-      arguments = list(type = type),
+      arguments = list(method = method),
       results = list(),
       trained = FALSE
     )
 
   new_container(
-    mode = x$mode,
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
@@ -46,14 +45,14 @@ print.probability_calibration <- function(x, ...) {
 
 #' @export
 fit.probability_calibration <- function(object, data, container = NULL, ...) {
-  type <- check_type(object$type, container$type)
+  method <- check_method(object$method, container$type)
   # todo: adjust_probability_calibration() should take arguments to pass to
   # cal_estimate_* via dots
   # to-do: add argument specifying `prop` in initial_split
   fit <-
     eval_bare(
       call2(
-        paste0("cal_estimate_", type),
+        paste0("cal_estimate_", method),
         .data = data,
         # todo: make getters for the entries in `columns`
         truth = container$columns$outcome,
diff --git a/R/adjust-probability-threshold.R b/R/adjust-probability-threshold.R
index fcf13a3..69eed9c 100644
--- a/R/adjust-probability-threshold.R
+++ b/R/adjust-probability-threshold.R
@@ -7,7 +7,7 @@
 #' library(modeldata)
 #'
 #' post_obj <-
-#'   container(mode = "classification") %>%
+#'   container() %>%
 #'   adjust_probability_threshold(threshold = .1)
 #'
 #' two_class_example %>% count(predicted)
@@ -39,7 +39,6 @@ adjust_probability_threshold <- function(x, threshold = 0.5) {
     )
 
   new_container(
-    mode = x$mode,
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
diff --git a/R/container.R b/R/container.R
index a07e852..d3a232a 100644
--- a/R/container.R
+++ b/R/container.R
@@ -1,7 +1,5 @@
 #' Declare post-processing for model predictions
 #'
-#' @param mode The model's mode, one of `"classification"`, or `"regression"`.
-#' Modes of `"censored regression"` are not currently supported.
 #' @param type The model sub-type. Possible values are `"unknown"`, `"regression"`,
 #' `"binary"`, or `"multiclass"`.
 #' @param outcome The name of the outcome variable.
@@ -14,9 +12,9 @@
 #' @param time The name of the predicted event time. (not yet supported)
 #' @examples
 #'
-#' container(mode = "regression")
+#' container()
 #' @export
-container <- function(mode, type = "unknown", outcome = NULL, estimate = NULL,
+container <- function(type = "unknown", outcome = NULL, estimate = NULL,
                       probabilities = NULL, time = NULL) {
   columns <-
     list(
@@ -28,7 +26,6 @@ container <- function(mode, type = "unknown", outcome = NULL, estimate = NULL,
     )
 
   new_container(
-    mode,
     type,
     operations = list(),
     columns = columns,
@@ -37,13 +34,7 @@ container <- function(mode, type = "unknown", outcome = NULL, estimate = NULL,
   )
 }
 
-new_container <- function(mode, type, operations, columns, ptype, call) {
-  mode <- arg_match0(mode, c("regression", "classification"))
-
-  if (mode == "regression") {
-    type <- "regression"
-  }
-
+new_container <- function(type, operations, columns, ptype, call) {
   type <- arg_match0(type, c("unknown", "regression", "binary", "multiclass"))
 
   if (!is.list(operations)) {
@@ -58,11 +49,11 @@ new_container <- function(mode, type, operations, columns, ptype, call) {
   }
 
   # validate operation order and check duplicates
-  validate_order(operations, mode, call)
+  validate_order(operations, type, call)
 
   # check columns
   res <- list(
-    mode = mode, type = type, operations = operations,
+    type = type, operations = operations,
     columns = columns, ptype = ptype
   )
   class(res) <- "container"
@@ -120,7 +111,6 @@ fit.container <- function(object, .data, outcome, estimate, probabilities = c(),
   object <- set_container_type(object, .data[[columns$outcome]])
 
   object <- new_container(
-    object$mode,
     object$type,
     operations = object$operations,
     columns = columns,
diff --git a/R/utils.R b/R/utils.R
index b6bcef7..616ed04 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -61,13 +61,13 @@ check_container <- function(x, calibration_type = NULL, call = caller_env(), arg
   # check that the type of calibration ("numeric" or "probability") is
   # compatible with the container type
   if (!is.null(calibration_type)) {
-    container_type <- x$type
+    type <- x$type
     switch(
-      container_type,
+      type,
       regression =
-        check_calibration_type(calibration_type, "numeric", container_type, call = call),
-      binary = , multinomial =
-        check_calibration_type(calibration_type, "probability", container_type, call = call)
+        check_calibration_type(calibration_type, "numeric", type, call = call),
+      binary = , multiclass =
+        check_calibration_type(calibration_type, "probability", type, call = call)
     )
   }
 
@@ -90,20 +90,19 @@ types_binary <- c("logistic", "beta", "isotonic", "isotonic_boot")
 types_multiclass <- c("multinomial", "beta", "isotonic", "isotonic_boot")
 # a check function to be called when a container is being `fit()`ted.
 # by the time a container is fitted, we have:
-# * `adjust_type`, the `type` argument passed to an `adjust_*` function
+# * `method`, the `method` argument passed to an `adjust_*` function
 #     * this argument has already been checked to agree with the kind of
 #       `adjust_*()` function via `arg_match0()`.
 # * `container_type`, the `type` argument either specified in `container()`
 #   or inferred in `fit.container()`.
-check_type <- function(adjust_type,
-                       container_type,
-                       arg = caller_arg(adjust_type),
+check_method <- function(method,
+                       type,
+                       arg = caller_arg(method),
                        call = caller_env()) {
-  # if no `adjust_type` was supplied, infer a reasonable one based on the
-  # `container_type`
-  if (is.null(adjust_type)) {
+  # if no `method` was supplied, infer a reasonable one based on the `type`
+  if (is.null(method)) {
     switch(
-      container_type,
+      type,
       regression = return("linear"),
       binary = return("logistic"),
       multiclass = return("multinomial")
@@ -111,33 +110,33 @@ check_type <- function(adjust_type,
   }
 
   switch(
-    container_type,
+    type,
     regression = arg_match0(
-      adjust_type,
+      method,
       types_regression,
       arg_nm = arg,
       error_call = call
     ),
     binary = arg_match0(
-      adjust_type,
+      method,
       types_binary,
       arg_nm = arg,
       error_call = call
     ),
     multiclass = arg_match0(
-      adjust_type,
+      method,
       types_multiclass,
       arg_nm = arg,
       error_call = call
     ),
     arg_match0(
-      adjust_type,
+      method,
       unique(c(types_regression, types_binary, types_multiclass)),
       arg_nm = arg,
       error_call = call
     )
   )
 
-  adjust_type
+  method
 }
 
diff --git a/R/validation-rules.R b/R/validation-rules.R
index a6a74a7..7a8e2a9 100644
--- a/R/validation-rules.R
+++ b/R/validation-rules.R
@@ -1,4 +1,4 @@
-validate_order <- function(ops, mode, call) {
+validate_order <- function(ops, type, call = caller_env()) {
   orderings <-
     tibble::new_tibble(list(
       name = purrr::map_chr(ops, ~ class(.x)[1]),
@@ -13,12 +13,17 @@ validate_order <- function(ops, mode, call) {
     return(invisible(orderings))
   }
 
-  if (mode == "classification") {
-    check_classification_order(orderings, call)
-  } else {
-    check_regression_order(orderings, call)
+  if (type == "unknown") {
+    type <- infer_type(orderings)
   }
 
+  switch(
+    type,
+    regression = check_regression_order(orderings, call),
+    binary = , multiclass = check_classification_order(orderings, call),
+    invisible()
+  )
+
   invisible(orderings)
 }
 
@@ -83,3 +88,19 @@ check_duplicates <- function(x, call) {
   }
   invisible(x)
 }
+
+infer_type <- function(orderings) {
+  if (all(orderings$output_all)) {
+    return("unknown")
+  }
+
+  if (all(orderings$output_numeric | orderings$output_all)) {
+    return("regression")
+  }
+
+  if (all(orderings$output_prob | orderings$output_class | orderings$output_all)) {
+    return("binary")
+  }
+
+  "unknown"
+}
diff --git a/inst/examples/container_regression_example.qmd b/inst/examples/container_regression_example.qmd
index bebdb00..6ff8480 100644
--- a/inst/examples/container_regression_example.qmd
+++ b/inst/examples/container_regression_example.qmd
@@ -101,7 +101,7 @@ We could manually use `cal_apply()` to adjust predictions, but instead, we'll ad
 #| label: post-1
 
 post_obj <-
-  container(mode = "regression") %>%
+  container() %>%
   adjust_numeric_calibration(bst_cal) 
 post_obj
 ```
diff --git a/man/adjust_equivocal_zone.Rd b/man/adjust_equivocal_zone.Rd
index 705f41e..75e55f5 100644
--- a/man/adjust_equivocal_zone.Rd
+++ b/man/adjust_equivocal_zone.Rd
@@ -22,7 +22,7 @@ library(dplyr)
 library(modeldata)
 
 post_obj <-
-  container(mode = "classification") \%>\%
+  container() \%>\%
   adjust_equivocal_zone(value = 1 / 4)
 
 
diff --git a/man/adjust_numeric_calibration.Rd b/man/adjust_numeric_calibration.Rd
index 0650ac0..f37da10 100644
--- a/man/adjust_numeric_calibration.Rd
+++ b/man/adjust_numeric_calibration.Rd
@@ -4,12 +4,12 @@
 \alias{adjust_numeric_calibration}
 \title{Re-calibrate numeric predictions}
 \usage{
-adjust_numeric_calibration(x, type = NULL)
+adjust_numeric_calibration(x, method = NULL)
 }
 \arguments{
 \item{x}{A \code{\link[=container]{container()}}.}
 
-\item{type}{Character. One of \code{"linear"}, \code{"isotonic"}, or
+\item{method}{Character. One of \code{"linear"}, \code{"isotonic"}, or
 \code{"isotonic_boot"}, corresponding to the function from the \pkg{probably}
 package \code{\link[probably:cal_estimate_linear]{probably::cal_estimate_linear()}},
 \code{\link[probably:cal_estimate_isotonic]{probably::cal_estimate_isotonic()}}, or
@@ -31,8 +31,8 @@ dat
 
 # specify calibration
 reg_ctr <-
-  container(mode = "regression") \%>\%
-  adjust_numeric_calibration(type = "linear")
+  container() \%>\%
+  adjust_numeric_calibration(method = "linear")
 
 # train container
 reg_ctr_trained <- fit(reg_ctr, dat, outcome = y, estimate = y_pred)
diff --git a/man/adjust_predictions_custom.Rd b/man/adjust_predictions_custom.Rd
index 4f54ced..2413ec6 100644
--- a/man/adjust_predictions_custom.Rd
+++ b/man/adjust_predictions_custom.Rd
@@ -22,7 +22,7 @@ library(dplyr)
 library(modeldata)
 
 post_obj <-
-  container(mode = "classification") \%>\%
+  container() \%>\%
   adjust_equivocal_zone() \%>\%
   adjust_predictions_custom(linear_predictor = binomial()$linkfun(Class2))
 
diff --git a/man/adjust_probability_calibration.Rd b/man/adjust_probability_calibration.Rd
index 3bd2adf..e174da9 100644
--- a/man/adjust_probability_calibration.Rd
+++ b/man/adjust_probability_calibration.Rd
@@ -4,12 +4,12 @@
 \alias{adjust_probability_calibration}
 \title{Re-calibrate classification probability predictions}
 \usage{
-adjust_probability_calibration(x, type = NULL)
+adjust_probability_calibration(x, method = NULL)
 }
 \arguments{
 \item{x}{A \code{\link[=container]{container()}}.}
 
-\item{type}{Character. One of \code{"logistic"}, \code{"multinomial"},
+\item{method}{Character. One of \code{"logistic"}, \code{"multinomial"},
 \code{"beta"}, \code{"isotonic"}, or \code{"isotonic_boot"}, corresponding to the
 function from the \pkg{probably} package \code{\link[probably:cal_estimate_logistic]{probably::cal_estimate_logistic()}},
 \code{\link[probably:cal_estimate_multinomial]{probably::cal_estimate_multinomial()}}, etc., respectively.}
diff --git a/man/adjust_probability_threshold.Rd b/man/adjust_probability_threshold.Rd
index ea227dd..b6881df 100644
--- a/man/adjust_probability_threshold.Rd
+++ b/man/adjust_probability_threshold.Rd
@@ -19,7 +19,7 @@ library(dplyr)
 library(modeldata)
 
 post_obj <-
-  container(mode = "classification") \%>\%
+  container() \%>\%
   adjust_probability_threshold(threshold = .1)
 
 two_class_example \%>\% count(predicted)
diff --git a/man/container.Rd b/man/container.Rd
index 1d074b5..53b68f1 100644
--- a/man/container.Rd
+++ b/man/container.Rd
@@ -5,7 +5,6 @@
 \title{Declare post-processing for model predictions}
 \usage{
 container(
-  mode,
   type = "unknown",
   outcome = NULL,
   estimate = NULL,
@@ -14,9 +13,6 @@ container(
 )
 }
 \arguments{
-\item{mode}{The model's mode, one of \code{"classification"}, or \code{"regression"}.
-Modes of \code{"censored regression"} are not currently supported.}
-
 \item{type}{The model sub-type. Possible values are \code{"unknown"}, \code{"regression"},
 \code{"binary"}, or \code{"multiclass"}.}
 
@@ -37,5 +33,5 @@ Declare post-processing for model predictions
 }
 \examples{
 
-container(mode = "regression")
+container()
 }
diff --git a/tests/testthat/_snaps/adjust-equivocal-zone.md b/tests/testthat/_snaps/adjust-equivocal-zone.md
index 4021efc..392c9b9 100644
--- a/tests/testthat/_snaps/adjust-equivocal-zone.md
+++ b/tests/testthat/_snaps/adjust-equivocal-zone.md
@@ -1,7 +1,7 @@
 # adjustment printing
 
     Code
-      ctr_cls %>% adjust_equivocal_zone()
+      container() %>% adjust_equivocal_zone()
     Message
       
       -- Container -------------------------------------------------------------------
@@ -12,7 +12,7 @@
 ---
 
     Code
-      ctr_cls %>% adjust_equivocal_zone(hardhat::tune())
+      container() %>% adjust_equivocal_zone(hardhat::tune())
     Message
       
       -- Container -------------------------------------------------------------------
diff --git a/tests/testthat/_snaps/adjust-numeric-calibration.md b/tests/testthat/_snaps/adjust-numeric-calibration.md
index 0d904a3..06aac0e 100644
--- a/tests/testthat/_snaps/adjust-numeric-calibration.md
+++ b/tests/testthat/_snaps/adjust-numeric-calibration.md
@@ -1,26 +1,26 @@
 # adjustment printing
 
     Code
-      ctr_reg %>% adjust_numeric_calibration()
+      container() %>% adjust_numeric_calibration()
     Message
       
       -- Container -------------------------------------------------------------------
-      A regression postprocessor with 1 operation:
+      A postprocessor with 1 operation:
       
       * Re-calibrate numeric predictions.
 
 # errors informatively with bad input
 
     Code
-      adjust_numeric_calibration(ctr_reg, "boop")
+      adjust_numeric_calibration(container(), "boop")
     Condition
       Error in `adjust_numeric_calibration()`:
-      ! `type` must be one of "linear", "isotonic", or "isotonic_boot", not "boop".
+      ! `method` must be one of "linear", "isotonic", or "isotonic_boot", not "boop".
 
 ---
 
     Code
-      container("classification", "binary") %>% adjust_numeric_calibration("linear")
+      container("binary") %>% adjust_numeric_calibration("linear")
     Condition
       Error in `adjust_numeric_calibration()`:
       ! A binary container is incompatible with the operation `adjust_numeric_calibration()`.
@@ -28,9 +28,9 @@
 ---
 
     Code
-      container("regression", "regression") %>% adjust_numeric_calibration("binary")
+      container("regression") %>% adjust_numeric_calibration("binary")
     Condition
       Error in `adjust_numeric_calibration()`:
-      ! `type` must be one of "linear", "isotonic", or "isotonic_boot", not "binary".
+      ! `method` must be one of "linear", "isotonic", or "isotonic_boot", not "binary".
       i Did you mean "linear"?
 
diff --git a/tests/testthat/_snaps/adjust-numeric-range.md b/tests/testthat/_snaps/adjust-numeric-range.md
index b3df879..2e02acd 100644
--- a/tests/testthat/_snaps/adjust-numeric-range.md
+++ b/tests/testthat/_snaps/adjust-numeric-range.md
@@ -1,44 +1,44 @@
 # adjustment printing
 
     Code
-      ctr_reg %>% adjust_numeric_range()
+      container() %>% adjust_numeric_range()
     Message
       
       -- Container -------------------------------------------------------------------
-      A regression postprocessor with 1 operation:
+      A postprocessor with 1 operation:
       
       * Constrain numeric predictions to be between [-Inf, Inf].
 
 ---
 
     Code
-      ctr_reg %>% adjust_numeric_range(hardhat::tune())
+      container() %>% adjust_numeric_range(hardhat::tune())
     Message
       
       -- Container -------------------------------------------------------------------
-      A regression postprocessor with 1 operation:
+      A postprocessor with 1 operation:
       
       * Constrain numeric predictions to be between [?, Inf].
 
 ---
 
     Code
-      ctr_reg %>% adjust_numeric_range(-1, hardhat::tune())
+      container() %>% adjust_numeric_range(-1, hardhat::tune())
     Message
       
       -- Container -------------------------------------------------------------------
-      A regression postprocessor with 1 operation:
+      A postprocessor with 1 operation:
       
       * Constrain numeric predictions to be between [-1, ?].
 
 ---
 
     Code
-      ctr_reg %>% adjust_numeric_range(hardhat::tune(), 1)
+      container() %>% adjust_numeric_range(hardhat::tune(), 1)
     Message
       
       -- Container -------------------------------------------------------------------
-      A regression postprocessor with 1 operation:
+      A postprocessor with 1 operation:
       
       * Constrain numeric predictions to be between [?, 1].
 
diff --git a/tests/testthat/_snaps/adjust-predictions-custom.md b/tests/testthat/_snaps/adjust-predictions-custom.md
index 71e9e76..50ccfce 100644
--- a/tests/testthat/_snaps/adjust-predictions-custom.md
+++ b/tests/testthat/_snaps/adjust-predictions-custom.md
@@ -1,7 +1,7 @@
 # adjustment printing
 
     Code
-      ctr_cls %>% adjust_predictions_custom()
+      container() %>% adjust_predictions_custom()
     Message
       
       -- Container -------------------------------------------------------------------
diff --git a/tests/testthat/_snaps/adjust-probability-calibration.md b/tests/testthat/_snaps/adjust-probability-calibration.md
index 2fefbea..9b6376b 100644
--- a/tests/testthat/_snaps/adjust-probability-calibration.md
+++ b/tests/testthat/_snaps/adjust-probability-calibration.md
@@ -1,7 +1,7 @@
 # adjustment printing
 
     Code
-      ctr_cls %>% adjust_probability_calibration("logistic")
+      container() %>% adjust_probability_calibration("logistic")
     Message
       
       -- Container -------------------------------------------------------------------
@@ -12,16 +12,15 @@
 # errors informatively with bad input
 
     Code
-      adjust_probability_calibration(ctr_cls, "boop")
+      adjust_probability_calibration(container(), "boop")
     Condition
       Error in `adjust_probability_calibration()`:
-      ! `type` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "boop".
+      ! `method` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "boop".
 
 ---
 
     Code
-      container("regression", "regression") %>% adjust_probability_calibration(
-        "binary")
+      container("regression") %>% adjust_probability_calibration("binary")
     Condition
       Error in `adjust_probability_calibration()`:
       ! A regression container is incompatible with the operation `adjust_probability_calibration()`.
@@ -29,9 +28,8 @@
 ---
 
     Code
-      container("classification", "binary") %>% adjust_probability_calibration(
-        "linear")
+      container("binary") %>% adjust_probability_calibration("linear")
     Condition
       Error in `adjust_probability_calibration()`:
-      ! `type` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "linear".
+      ! `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 2affcca..5e4b29f 100644
--- a/tests/testthat/_snaps/adjust-probability-threshold.md
+++ b/tests/testthat/_snaps/adjust-probability-threshold.md
@@ -1,7 +1,7 @@
 # adjustment printing
 
     Code
-      ctr_cls %>% adjust_probability_threshold()
+      container() %>% adjust_probability_threshold()
     Message
       
       -- Container -------------------------------------------------------------------
@@ -12,7 +12,7 @@
 ---
 
     Code
-      ctr_cls %>% adjust_probability_threshold(hardhat::tune())
+      container() %>% adjust_probability_threshold(hardhat::tune())
     Message
       
       -- Container -------------------------------------------------------------------
diff --git a/tests/testthat/_snaps/container.md b/tests/testthat/_snaps/container.md
index 24aa650..f5f9ab8 100644
--- a/tests/testthat/_snaps/container.md
+++ b/tests/testthat/_snaps/container.md
@@ -1,7 +1,7 @@
 # container printing
 
     Code
-      ctr_cls
+      container()
     Message
       
       -- Container -------------------------------------------------------------------
@@ -10,7 +10,7 @@
 ---
 
     Code
-      container(mode = "classification", type = "binary")
+      container(type = "binary")
     Message
       
       -- Container -------------------------------------------------------------------
@@ -19,8 +19,7 @@
 ---
 
     Code
-      container(mode = "classification", type = "binary") %>%
-        adjust_probability_threshold(0.2)
+      container(type = "binary") %>% adjust_probability_threshold(0.2)
     Message
       
       -- Container -------------------------------------------------------------------
@@ -31,8 +30,8 @@
 ---
 
     Code
-      container(mode = "classification", type = "binary") %>%
-        adjust_probability_threshold(0.2) %>% adjust_equivocal_zone()
+      container(type = "binary") %>% adjust_probability_threshold(0.2) %>%
+        adjust_equivocal_zone()
     Message
       
       -- Container -------------------------------------------------------------------
diff --git a/tests/testthat/_snaps/validation-rules.md b/tests/testthat/_snaps/validation-rules.md
index df42bda..0e9f3ff 100644
--- a/tests/testthat/_snaps/validation-rules.md
+++ b/tests/testthat/_snaps/validation-rules.md
@@ -1,7 +1,7 @@
 # validation of operations (regression)
 
     Code
-      container(mode = "regression") %>% adjust_numeric_range(lower_limit = 2) %>%
+      container(type = "regression") %>% 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 operations (classification)
 
     Code
-      container(mode = "classification") %>% adjust_probability_threshold(threshold = 0.4) %>%
+      container(type = "binary") %>% adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_calibration()
     Condition
       Error in `adjust_probability_calibration()`:
@@ -19,7 +19,26 @@
 ---
 
     Code
-      container(mode = "classification") %>% adjust_predictions_custom(veg = "potato") %>%
+      container() %>% adjust_probability_threshold(threshold = 0.4) %>%
+        adjust_probability_calibration()
+    Condition
+      Error in `adjust_probability_calibration()`:
+      ! Operations that change the hard class predictions must come after operations that update the class probability estimates.
+
+---
+
+    Code
+      container(type = "binary") %>% adjust_predictions_custom(veg = "potato") %>%
+        adjust_probability_threshold(threshold = 0.4) %>%
+        adjust_probability_calibration()
+    Condition
+      Error in `adjust_probability_calibration()`:
+      ! Operations that change the hard class predictions must come after operations that update the class probability estimates.
+
+---
+
+    Code
+      container() %>% adjust_predictions_custom(veg = "potato") %>%
         adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_calibration()
     Condition
@@ -29,7 +48,7 @@
 ---
 
     Code
-      container(mode = "classification") %>% adjust_predictions_custom(veg = "potato") %>%
+      container(type = "binary") %>% adjust_predictions_custom(veg = "potato") %>%
         adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_threshold(threshold = 0.5) %>%
         adjust_probability_calibration()
@@ -40,7 +59,27 @@
 ---
 
     Code
-      container(mode = "classification") %>% adjust_equivocal_zone(value = 0.2) %>%
+      container() %>% adjust_predictions_custom(veg = "potato") %>%
+        adjust_probability_threshold(threshold = 0.4) %>%
+        adjust_probability_threshold(threshold = 0.5) %>%
+        adjust_probability_calibration()
+    Condition
+      Error in `adjust_probability_threshold()`:
+      ! Operations cannot be duplicated: "probability_threshold"
+
+---
+
+    Code
+      container(type = "binary") %>% adjust_equivocal_zone(value = 0.2) %>%
+        adjust_probability_threshold(threshold = 0.4)
+    Condition
+      Error in `adjust_probability_threshold()`:
+      ! Equivocal zone addition should come after operations that update the class probability estimates or hard class predictions.
+
+---
+
+    Code
+      container() %>% adjust_equivocal_zone(value = 0.2) %>%
         adjust_probability_threshold(threshold = 0.4)
     Condition
       Error in `adjust_probability_threshold()`:
diff --git a/tests/testthat/helper-objects.R b/tests/testthat/helper-objects.R
deleted file mode 100644
index 2f53f8c..0000000
--- a/tests/testthat/helper-objects.R
+++ /dev/null
@@ -1,2 +0,0 @@
-ctr_cls <- container(mode = "classification")
-ctr_reg <- container(mode = "regression")
diff --git a/tests/testthat/test-adjust-equivocal-zone.R b/tests/testthat/test-adjust-equivocal-zone.R
index ab0793e..4ba9b0c 100644
--- a/tests/testthat/test-adjust-equivocal-zone.R
+++ b/tests/testthat/test-adjust-equivocal-zone.R
@@ -1,4 +1,4 @@
 test_that("adjustment printing", {
-  expect_snapshot(ctr_cls %>% adjust_equivocal_zone())
-  expect_snapshot(ctr_cls %>% adjust_equivocal_zone(hardhat::tune()))
+  expect_snapshot(container() %>% adjust_equivocal_zone())
+  expect_snapshot(container() %>% adjust_equivocal_zone(hardhat::tune()))
 })
diff --git a/tests/testthat/test-adjust-numeric-calibration.R b/tests/testthat/test-adjust-numeric-calibration.R
index d664653..d9392ef 100644
--- a/tests/testthat/test-adjust-numeric-calibration.R
+++ b/tests/testthat/test-adjust-numeric-calibration.R
@@ -1,22 +1,20 @@
 test_that("adjustment printing", {
-  expect_snapshot(ctr_reg %>% adjust_numeric_calibration())
+  expect_snapshot(container() %>% adjust_numeric_calibration())
 })
 
 test_that("errors informatively with bad input", {
   # check for `adjust_numeric_calibration(container)` is in `utils.R` tests
 
-  expect_snapshot(error = TRUE, adjust_numeric_calibration(ctr_reg, "boop"))
+  expect_snapshot(error = TRUE, adjust_numeric_calibration(container(), "boop"))
   expect_snapshot(
     error = TRUE,
-    container("classification", "binary") %>% adjust_numeric_calibration("linear")
+    container("binary") %>% adjust_numeric_calibration("linear")
   )
   expect_snapshot(
     error = TRUE,
-    container("regression", "regression") %>% adjust_numeric_calibration("binary")
+    container("regression") %>% adjust_numeric_calibration("binary")
   )
-  # todo: this should error, mode is incompatible even though type is fine
-  # expect_snapshot(error = TRUE, adjust_numeric_calibration(ctr_cls, "linear"))
 
-  expect_no_condition(adjust_numeric_calibration(ctr_reg))
-  expect_no_condition(adjust_numeric_calibration(ctr_reg, "linear"))
+  expect_no_condition(adjust_numeric_calibration(container()))
+  expect_no_condition(adjust_numeric_calibration(container(), "linear"))
 })
diff --git a/tests/testthat/test-adjust-numeric-range.R b/tests/testthat/test-adjust-numeric-range.R
index 6e04c75..a2fcad7 100644
--- a/tests/testthat/test-adjust-numeric-range.R
+++ b/tests/testthat/test-adjust-numeric-range.R
@@ -1,7 +1,7 @@
 test_that("adjustment printing", {
-  expect_snapshot(ctr_reg %>% adjust_numeric_range())
-  expect_snapshot(ctr_reg %>% adjust_numeric_range(hardhat::tune()))
-  expect_snapshot(ctr_reg %>% adjust_numeric_range(-1, hardhat::tune()))
-  expect_snapshot(ctr_reg %>% adjust_numeric_range(hardhat::tune(), 1))
+  expect_snapshot(container() %>% adjust_numeric_range())
+  expect_snapshot(container() %>% adjust_numeric_range(hardhat::tune()))
+  expect_snapshot(container() %>% adjust_numeric_range(-1, hardhat::tune()))
+  expect_snapshot(container() %>% adjust_numeric_range(hardhat::tune(), 1))
 })
 
diff --git a/tests/testthat/test-adjust-predictions-custom.R b/tests/testthat/test-adjust-predictions-custom.R
index 70c6359..f74f6b5 100644
--- a/tests/testthat/test-adjust-predictions-custom.R
+++ b/tests/testthat/test-adjust-predictions-custom.R
@@ -1,3 +1,3 @@
 test_that("adjustment printing", {
-  expect_snapshot(ctr_cls %>% adjust_predictions_custom())
+  expect_snapshot(container() %>% adjust_predictions_custom())
 })
diff --git a/tests/testthat/test-adjust-probability-calibration.R b/tests/testthat/test-adjust-probability-calibration.R
index 9e68d51..170d12a 100644
--- a/tests/testthat/test-adjust-probability-calibration.R
+++ b/tests/testthat/test-adjust-probability-calibration.R
@@ -1,22 +1,20 @@
 test_that("adjustment printing", {
-  expect_snapshot(ctr_cls %>% adjust_probability_calibration("logistic"))
+  expect_snapshot(container() %>% adjust_probability_calibration("logistic"))
 })
 
 test_that("errors informatively with bad input", {
   # check for `adjust_probably_calibration(container)` is in `utils.R` tests
 
-  expect_snapshot(error = TRUE, adjust_probability_calibration(ctr_cls, "boop"))
+  expect_snapshot(error = TRUE, adjust_probability_calibration(container(), "boop"))
   expect_snapshot(
     error = TRUE,
-    container("regression", "regression") %>% adjust_probability_calibration("binary")
+    container("regression") %>% adjust_probability_calibration("binary")
   )
   expect_snapshot(
     error = TRUE,
-    container("classification", "binary") %>% adjust_probability_calibration("linear")
+    container("binary") %>% adjust_probability_calibration("linear")
   )
-  # todo: this should error, mode is incompatible even though type is fine
-  # expect_snapshot(error = TRUE, adjust_numeric_calibration(ctr_cls, "linear"))
 
-  expect_no_condition(adjust_numeric_calibration(ctr_reg))
-  expect_no_condition(adjust_numeric_calibration(ctr_reg, "linear"))
+  expect_no_condition(adjust_numeric_calibration(container()))
+  expect_no_condition(adjust_numeric_calibration(container(), "linear"))
 })
diff --git a/tests/testthat/test-adjust-probability-threshold.R b/tests/testthat/test-adjust-probability-threshold.R
index 38ae223..94933d7 100644
--- a/tests/testthat/test-adjust-probability-threshold.R
+++ b/tests/testthat/test-adjust-probability-threshold.R
@@ -1,4 +1,4 @@
 test_that("adjustment printing", {
-  expect_snapshot(ctr_cls %>% adjust_probability_threshold())
-  expect_snapshot(ctr_cls %>% adjust_probability_threshold(hardhat::tune()))
+  expect_snapshot(container() %>% adjust_probability_threshold())
+  expect_snapshot(container() %>% adjust_probability_threshold(hardhat::tune()))
 })
diff --git a/tests/testthat/test-container.R b/tests/testthat/test-container.R
index 35837a5..2bc3cfa 100644
--- a/tests/testthat/test-container.R
+++ b/tests/testthat/test-container.R
@@ -1,12 +1,12 @@
 test_that("container printing", {
-  expect_snapshot(ctr_cls)
-  expect_snapshot(container(mode = "classification", type = "binary"))
+  expect_snapshot(container())
+  expect_snapshot(container(type = "binary"))
   expect_snapshot(
-    container(mode = "classification", type = "binary") %>%
+    container(type = "binary") %>%
       adjust_probability_threshold(.2)
   )
   expect_snapshot(
-    container(mode = "classification", type = "binary") %>%
+    container(type = "binary") %>%
       adjust_probability_threshold(.2) %>%
       adjust_equivocal_zone()
   )
diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R
index 41b093a..f6bd959 100644
--- a/tests/testthat/test-utils.R
+++ b/tests/testthat/test-utils.R
@@ -1,4 +1,4 @@
 test_that("check_container raises informative error", {
   expect_snapshot(error = TRUE, adjust_probability_threshold("boop"))
-  expect_no_condition(ctr_cls %>% adjust_probability_threshold(.5))
+  expect_no_condition(container() %>% adjust_probability_threshold(.5))
 })
diff --git a/tests/testthat/test-validation-rules.R b/tests/testthat/test-validation-rules.R
index 421130a..1a6e477 100644
--- a/tests/testthat/test-validation-rules.R
+++ b/tests/testthat/test-validation-rules.R
@@ -1,25 +1,25 @@
 test_that("validation of operations (regression)", {
-  expect_silent(
+  expect_no_condition(
     reg_ctr <-
-      container(mode = "regression") %>%
+      container(type = "regression") %>%
       adjust_numeric_calibration() %>%
       adjust_numeric_range(lower_limit = 2) %>%
       adjust_predictions_custom(squared = .pred^2)
   )
 
   expect_snapshot(
-    container(mode = "regression") %>%
+    error = TRUE,
+    container(type = "regression") %>%
       adjust_numeric_range(lower_limit = 2) %>%
       adjust_numeric_calibration() %>%
-      adjust_predictions_custom(squared = .pred^2),
-    error = TRUE
+      adjust_predictions_custom(squared = .pred^2)
   )
 
   # todo should we error if a mutate occurs beforehand? Can we detect if it
   # modifies the prediction?
-  expect_silent(
+  expect_no_condition(
     reg_ctr <-
-      container(mode = "regression") %>%
+      container(type = "regression") %>%
       adjust_predictions_custom(squared = .pred^2) %>%
       adjust_numeric_calibration() %>%
       adjust_numeric_range(lower_limit = 2)
@@ -27,17 +27,16 @@ test_that("validation of operations (regression)", {
 })
 
 test_that("validation of operations (classification)", {
-  expect_silent(
+  expect_no_condition(
     cls_ctr_1 <-
-      container(mode = "classification") %>%
-      # to-do: should be able to supply no `type` argument here
+      container(type = "binary") %>%
       adjust_probability_calibration("logistic") %>%
       adjust_probability_threshold(threshold = .4)
   )
 
-  expect_silent(
+  expect_no_condition(
     cls_ctr_2 <-
-      container(mode = "classification") %>%
+      container(type = "binary") %>%
       adjust_predictions_custom(starch = "potato") %>%
       adjust_predictions_custom(veg = "green beans") %>%
       adjust_probability_calibration("logistic") %>%
@@ -45,33 +44,75 @@ test_that("validation of operations (classification)", {
   )
 
   expect_snapshot(
-    container(mode = "classification") %>%
+    error = TRUE,
+    container(type = "binary") %>%
+      adjust_probability_threshold(threshold = .4) %>%
+      adjust_probability_calibration()
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    container() %>%
+      adjust_probability_threshold(threshold = .4) %>%
+      adjust_probability_calibration()
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    container(type = "binary") %>%
+      adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
-      adjust_probability_calibration(),
-    error = TRUE
+      adjust_probability_calibration()
   )
 
   expect_snapshot(
-    container(mode = "classification") %>%
+    error = TRUE,
+    container() %>%
       adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
-      adjust_probability_calibration(),
-    error = TRUE
+      adjust_probability_calibration()
   )
 
   expect_snapshot(
-    container(mode = "classification") %>%
+    error = TRUE,
+    container(type = "binary") %>%
       adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_threshold(threshold = .5) %>%
-      adjust_probability_calibration(),
-    error = TRUE
+      adjust_probability_calibration()
   )
 
   expect_snapshot(
-    container(mode = "classification") %>%
+    error = TRUE,
+    container() %>%
+      adjust_predictions_custom(veg = "potato") %>%
+      adjust_probability_threshold(threshold = .4) %>%
+      adjust_probability_threshold(threshold = .5) %>%
+      adjust_probability_calibration()
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    container(type = "binary") %>%
       adjust_equivocal_zone(value = .2) %>%
-      adjust_probability_threshold(threshold = .4),
-    error = TRUE
+      adjust_probability_threshold(threshold = .4)
   )
+
+  expect_snapshot(
+    error = TRUE,
+    container() %>%
+      adjust_equivocal_zone(value = .2) %>%
+      adjust_probability_threshold(threshold = .4)
+  )
+})
+
+test_that("validation of operations (ambiguous type)", {
+  expect_no_condition(
+    ambiguous_ctr <-
+      container() %>%
+      adjust_predictions_custom(squared = .pred^2) %>%
+      adjust_predictions_custom(boop = boop)
+  )
+
+  expect_equal(ambiguous_ctr$type, "unknown")
 })