diff --git a/tests/testthat/_snaps/survival-tune-eval-time-arguments.md b/tests/testthat/_snaps/survival-tune-eval-time-arguments.md
new file mode 100644
index 0000000..9d45c7b
--- /dev/null
+++ b/tests/testthat/_snaps/survival-tune-eval-time-arguments.md
@@ -0,0 +1,795 @@
+# evaluation time argument to tune objects
+
+    Code
+      spec %>% tune_grid(Surv(time, status) ~ ., resamples = rs, metrics = mtr)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      spec %>% tune_grid(Surv(time, status) ~ ., resamples = rs, metrics = reg_mtr)
+    Condition
+      Error in `tune_grid()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      linear_reg() %>% tune_grid(age ~ ., resamples = rs, metrics = reg_mtr,
+      eval_time = 1)
+    Condition
+      Warning:
+      Evaluation times are only required when the model mode is "censored regression" (and will be ignored).
+      Warning:
+      No tuning parameters have been detected, performance will be evaluated using the resamples with no tuning. Did you want to [tune()] parameters?
+    Output
+      # Tuning results
+      # 10-fold cross-validation using stratification 
+      # A tibble: 10 x 4
+         splits           id     .metrics         .notes          
+         <list>           <chr>  <list>           <list>          
+       1 <split [164/20]> Fold01 <tibble [1 x 4]> <tibble [0 x 3]>
+       2 <split [165/19]> Fold02 <tibble [1 x 4]> <tibble [0 x 3]>
+       3 <split [165/19]> Fold03 <tibble [1 x 4]> <tibble [0 x 3]>
+       4 <split [166/18]> Fold04 <tibble [1 x 4]> <tibble [0 x 3]>
+       5 <split [166/18]> Fold05 <tibble [1 x 4]> <tibble [0 x 3]>
+       6 <split [166/18]> Fold06 <tibble [1 x 4]> <tibble [0 x 3]>
+       7 <split [166/18]> Fold07 <tibble [1 x 4]> <tibble [0 x 3]>
+       8 <split [166/18]> Fold08 <tibble [1 x 4]> <tibble [0 x 3]>
+       9 <split [166/18]> Fold09 <tibble [1 x 4]> <tibble [0 x 3]>
+      10 <split [166/18]> Fold10 <tibble [1 x 4]> <tibble [0 x 3]>
+
+---
+
+    Code
+      no_usable_times <- spec %>% tune_grid(Surv(time, status) ~ ., resamples = rs,
+      metrics = mtr, eval_time = c(-1, Inf))
+    Condition
+      Error:
+      ! There were no usable evaluation times (finite, non-missing, and >= 0).
+
+# eval time inputs are checked for censored regression models
+
+    Code
+      check_eval_time_arg(NULL, met_stc)
+    Output
+      NULL
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_dyn)
+    Condition
+      Error:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_int)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_stc_dyn)
+    Condition
+      Error:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_stc_int)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_dyn_stc)
+    Condition
+      Error:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_dyn_int)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_int_stc)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(NULL, met_int_dyn)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      check_eval_time_arg(2, met_stc)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+    Output
+      NULL
+
+---
+
+    Code
+      check_eval_time_arg(2, met_dyn)
+    Output
+      [1] 2
+
+---
+
+    Code
+      check_eval_time_arg(2, met_int)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      check_eval_time_arg(2, met_stc_dyn)
+    Output
+      [1] 2
+
+---
+
+    Code
+      check_eval_time_arg(2, met_stc_int)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      check_eval_time_arg(2, met_dyn_stc)
+    Output
+      [1] 2
+
+---
+
+    Code
+      check_eval_time_arg(2, met_dyn_int)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      check_eval_time_arg(2, met_int_stc)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      check_eval_time_arg(2, met_int_dyn)
+    Condition
+      Error:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_stc)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+    Output
+      NULL
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_dyn)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_int)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_stc_dyn)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_stc_int)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_dyn_stc)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_dyn_int)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_int_stc)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      check_eval_time_arg(1:3, met_int_dyn)
+    Output
+      [1] 1 2 3
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_stc)
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_dyn)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_int)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_stc_dyn)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_stc_int)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_dyn_stc)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_dyn_int)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_int_stc)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_int_dyn)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_stc, eval_time = 2)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_dyn, eval_time = 2)
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_int, eval_time = 2)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_stc_dyn, eval_time = 2)
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_stc_int, eval_time = 2)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_dyn_stc, eval_time = 2)
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_dyn_int, eval_time = 2)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_int_stc, eval_time = 2)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_int_dyn, eval_time = 2)
+    Condition
+      Error in `fit_resamples()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_stc, eval_time = 1:3)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_stc_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_stc_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_dyn_stc, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_dyn_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_int_stc, eval_time = 1:3)
+
+---
+
+    Code
+      res <- fit_resamples(wflow, rs, metrics = met_int_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_stc)
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_dyn)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_int)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_stc_dyn)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_stc_int)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_dyn_stc)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_dyn_int)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_int_stc)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_int_dyn)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_stc, eval_time = 2)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_dyn, eval_time = 2)
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_int, eval_time = 2)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_stc_dyn, eval_time = 2)
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_stc_int, eval_time = 2)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_dyn_stc, eval_time = 2)
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_dyn_int, eval_time = 2)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_int_stc, eval_time = 2)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_int_dyn, eval_time = 2)
+    Condition
+      Error in `tune_grid()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_stc, eval_time = 1:3)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_stc_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_stc_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_dyn_stc, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_dyn_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_int_stc, eval_time = 1:3)
+
+---
+
+    Code
+      res <- tune_grid(wflow_tune, rs, metrics = met_int_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_dyn)
+    Condition
+      Error in `last_fit()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_int)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_stc_dyn)
+    Condition
+      Error in `last_fit()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_stc_int)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_dyn_stc)
+    Condition
+      Error in `last_fit()`:
+      ! At least 1 evaluation time is required for the metric type(s) requested: "dynamic_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_dyn_int)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_int_stc)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_int_dyn)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 0 unique times were given.
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_stc, eval_time = 2)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_dyn, eval_time = 2)
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_int, eval_time = 2)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_stc_dyn, eval_time = 2)
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_stc_int, eval_time = 2)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_dyn_stc, eval_time = 2)
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_dyn_int, eval_time = 2)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_int_stc, eval_time = 2)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "integrated_survival_metric" and "static_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_int_dyn, eval_time = 2)
+    Condition
+      Error in `last_fit()`:
+      ! At least 2 evaluation times are required for the metric type(s) requested: "dynamic_survival_metric" and "integrated_survival_metric". Only 1 unique time was given.
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_stc, eval_time = 1:3)
+    Condition
+      Warning:
+      Evaluation times are only required when dynmanic or integrated metrics are used (and will be ignored here).
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_stc_dyn, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_stc_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_dyn_stc, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_dyn_int, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_int_stc, eval_time = 1:3)
+
+---
+
+    Code
+      res <- last_fit(wflow, split, metrics = met_int_dyn, eval_time = 1:3)
+
diff --git a/tests/testthat/_snaps/survival-tune-metric-arguments.md b/tests/testthat/_snaps/survival-tune-metric-arguments.md
new file mode 100644
index 0000000..bdd7f33
--- /dev/null
+++ b/tests/testthat/_snaps/survival-tune-metric-arguments.md
@@ -0,0 +1,96 @@
+# metric inputs are checked for censored regression models
+
+    Code
+      check_metrics_arg(NULL, wflow)
+    Output
+      A metric set, consisting of:
+      - `brier_survival()`, a dynamic survival metric | direction: minimize
+
+---
+
+    Code
+      check_metrics_arg(met_reg, wflow)
+    Condition
+      Error:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      check_metrics_arg(met_cls, wflow)
+    Condition
+      Error:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      check_metrics_arg(met_srv, wflow)
+    Output
+      A metric set, consisting of:
+      - `concordance_survival()`, a static survival metric | direction: maximize
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_cls)
+    Condition
+      Error in `fit_resamples()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      fit_resamples(wflow, rs, metrics = met_reg)
+    Condition
+      Error in `fit_resamples()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_cls)
+    Condition
+      Error in `tune_grid()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      tune_grid(wflow_tune, rs, metrics = met_reg)
+    Condition
+      Error in `tune_grid()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      tune_bayes(wflow_tune, rs, metrics = met_cls)
+    Condition
+      Error in `tune_bayes()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      tune_bayes(wflow_tune, rs, metrics = met_reg)
+    Condition
+      Error in `tune_bayes()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_cls)
+    Condition
+      Error in `last_fit()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
+---
+
+    Code
+      last_fit(wflow, split, metrics = met_reg)
+    Condition
+      Error in `last_fit()`:
+      ! The parsnip model has `mode` value of "censored regression", but the `metrics` is a metric set for a different model mode.
+
diff --git a/tests/testthat/test-survival-tune-eval-time-arguments.R b/tests/testthat/test-survival-tune-eval-time-arguments.R
new file mode 100644
index 0000000..9d2e5dc
--- /dev/null
+++ b/tests/testthat/test-survival-tune-eval-time-arguments.R
@@ -0,0 +1,260 @@
+test_that("evaluation time argument to tune objects", {
+  skip_if_not_installed("yardstick", minimum_version = "1.1.0.9000")
+
+  suppressPackageStartupMessages(library(tune))
+  suppressPackageStartupMessages(library(censored))
+  suppressPackageStartupMessages(library(yardstick))
+  suppressPackageStartupMessages(library(rsample))
+
+  spec <- survival_reg()
+  set.seed(1)
+  rs <- vfold_cv(stanford2, strata = status)
+  .time <- seq(1, 1000, length = 5)
+  mtr <- metric_set(brier_survival)
+  reg_mtr <- metric_set(rmse)
+
+  expect_snapshot(error = TRUE,
+                  spec %>% tune_grid(Surv(time, status) ~ ., resamples = rs, metrics = mtr)
+  )
+  expect_snapshot(error = TRUE,
+                  spec %>% tune_grid(Surv(time, status) ~ ., resamples = rs, metrics = reg_mtr)
+  )
+  expect_snapshot(
+    linear_reg() %>% tune_grid(age ~ ., resamples = rs, metrics = reg_mtr, eval_time = 1)
+  )
+
+  expect_snapshot(error = TRUE,
+                  no_usable_times <-
+                    spec %>%
+                    tune_grid(Surv(time, status) ~ ., resamples = rs, metrics = mtr, eval_time = c(-1, Inf))
+  )
+
+  times <- 4:1
+  expect_equal(get_metric_time(metric_set(brier_survival), times), 4)
+  expect_equal(get_metric_time(metric_set(concordance_survival), times), NULL)
+  expect_equal(get_metric_time(metric_set(brier_survival_integrated), times), NULL)
+  expect_equal(
+    get_metric_time(
+      metric_set(brier_survival, brier_survival_integrated, concordance_survival),
+      times
+    ),
+    4
+  )
+
+})
+
+
+test_that("eval time inputs are checked for censored regression models", {
+  skip_if_not_installed("censored")
+
+  library(parsnip)
+  library(workflows)
+  library(yardstick)
+  library(rsample)
+  suppressPackageStartupMessages(library(censored))
+
+  stanford2$event_time <- Surv(stanford2$time, stanford2$status)
+  stanford2 <- stanford2[, c("event_time", "age")]
+
+  wflow <- workflow(event_time ~ age, survival_reg())
+  sr_spec <- survival_reg(dist = tune())
+  wflow_tune <- workflow(event_time ~ age, sr_spec)
+
+  set.seed(1)
+  split <- initial_split(stanford2)
+  rs <- vfold_cv(stanford2)
+
+  # ------------------------------------------------------------------------------
+  # setup metric sets
+
+  met_stc <- metric_set(concordance_survival)
+  met_dyn <- metric_set(brier_survival)
+  met_int <- metric_set(brier_survival_integrated)
+  met_stc_dyn <- metric_set(concordance_survival, brier_survival)
+  met_stc_int <- metric_set(concordance_survival, brier_survival_integrated)
+  met_dyn_stc <- metric_set(brier_survival, concordance_survival)
+  met_dyn_int <- metric_set(brier_survival, brier_survival_integrated)
+  met_int_stc <- metric_set(brier_survival_integrated, concordance_survival)
+  met_int_dyn <- metric_set(brier_survival_integrated, brier_survival)
+
+  # ------------------------------------------------------------------------------
+  # check inputs when eval_time left out
+
+  expect_snapshot(check_eval_time_arg(NULL, met_stc))
+  expect_snapshot(check_eval_time_arg(NULL, met_dyn), error = TRUE)
+  expect_snapshot(check_eval_time_arg(NULL, met_int), error = TRUE)
+
+  expect_snapshot(check_eval_time_arg(NULL, met_stc_dyn), error = TRUE)
+  expect_snapshot(check_eval_time_arg(NULL, met_stc_int), error = TRUE)
+  expect_snapshot(check_eval_time_arg(NULL, met_dyn_stc), error = TRUE)
+
+  expect_snapshot(check_eval_time_arg(NULL, met_dyn_int), error = TRUE)
+  expect_snapshot(check_eval_time_arg(NULL, met_int_stc), error = TRUE)
+  expect_snapshot(check_eval_time_arg(NULL, met_int_dyn), error = TRUE)
+
+  # ------------------------------------------------------------------------------
+  # check inputs with single eval times
+
+  expect_snapshot(check_eval_time_arg(2, met_stc))
+  expect_snapshot(check_eval_time_arg(2, met_dyn))
+  expect_snapshot(check_eval_time_arg(2, met_int), error = TRUE)
+
+  expect_snapshot(check_eval_time_arg(2, met_stc_dyn))
+  expect_snapshot(check_eval_time_arg(2, met_stc_int), error = TRUE)
+
+  expect_snapshot(check_eval_time_arg(2, met_dyn_stc))
+  expect_snapshot(check_eval_time_arg(2, met_dyn_int), error = TRUE)
+
+  expect_snapshot(check_eval_time_arg(2, met_int_stc), error = TRUE)
+  expect_snapshot(check_eval_time_arg(2, met_int_dyn), error = TRUE)
+
+  # ------------------------------------------------------------------------------
+  # check inputs with multiple eval times
+
+  expect_snapshot(check_eval_time_arg(1:3, met_stc))
+  expect_snapshot(check_eval_time_arg(1:3, met_dyn))
+  expect_snapshot(check_eval_time_arg(1:3, met_int))
+
+  expect_snapshot(check_eval_time_arg(1:3, met_stc_dyn))
+  expect_snapshot(check_eval_time_arg(1:3, met_stc_int))
+  expect_snapshot(check_eval_time_arg(1:3, met_dyn_stc))
+
+  expect_snapshot(check_eval_time_arg(1:3, met_dyn_int))
+  expect_snapshot(check_eval_time_arg(1:3, met_int_stc))
+  expect_snapshot(check_eval_time_arg(1:3, met_int_dyn))
+
+  # ------------------------------------------------------------------------------
+  # resampling
+
+  # no eval time
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_stc))
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_dyn), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_int), error = TRUE)
+
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_stc_dyn), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_stc_int), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_dyn_stc), error = TRUE)
+
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_dyn_int), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_int_stc), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_int_dyn), error = TRUE)
+
+  # one eval time
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_stc, eval_time = 2))
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_dyn, eval_time = 2))
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_stc_dyn, eval_time = 2))
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_stc_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_dyn_stc, eval_time = 2))
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_dyn_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_int_stc, eval_time = 2), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_int_dyn, eval_time = 2), error = TRUE)
+
+  # multiple eval times
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_stc, eval_time = 1:3))
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_dyn, eval_time = 1:3))
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_int, eval_time = 1:3))
+
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_stc_dyn, eval_time = 1:3))
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_stc_int, eval_time = 1:3))
+
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_dyn_stc, eval_time = 1:3))
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_dyn_int, eval_time = 1:3))
+
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_int_stc, eval_time = 1:3))
+  expect_snapshot(res <- fit_resamples(wflow, rs, metrics = met_int_dyn, eval_time = 1:3))
+
+  # ------------------------------------------------------------------------------
+  # grid tuning (tune bayes tests in extratests repo)
+
+  # no eval time
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_stc))
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_dyn), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_int), error = TRUE)
+
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_stc_dyn), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_stc_int), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_dyn_stc), error = TRUE)
+
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_dyn_int), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_int_stc), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_int_dyn), error = TRUE)
+
+  # one eval time
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_stc, eval_time = 2))
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_dyn, eval_time = 2))
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_stc_dyn, eval_time = 2))
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_stc_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_dyn_stc, eval_time = 2))
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_dyn_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_int_stc, eval_time = 2), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_int_dyn, eval_time = 2), error = TRUE)
+
+  # multiple eval times
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_stc, eval_time = 1:3))
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_dyn, eval_time = 1:3))
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_int, eval_time = 1:3))
+
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_stc_dyn, eval_time = 1:3))
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_stc_int, eval_time = 1:3))
+
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_dyn_stc, eval_time = 1:3))
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_dyn_int, eval_time = 1:3))
+
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_int_stc, eval_time = 1:3))
+  expect_snapshot(res <- tune_grid(wflow_tune, rs, metrics = met_int_dyn, eval_time = 1:3))
+
+  # ------------------------------------------------------------------------------
+  # last fit
+
+  # no eval time
+  expect_silent(res <- last_fit(wflow, split, metrics = met_stc))
+  expect_snapshot(last_fit(wflow, split, metrics = met_dyn), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_int), error = TRUE)
+
+  expect_snapshot(last_fit(wflow, split, metrics = met_stc_dyn), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_stc_int), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_dyn_stc), error = TRUE)
+
+  expect_snapshot(last_fit(wflow, split, metrics = met_dyn_int), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_int_stc), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_int_dyn), error = TRUE)
+
+  # one eval time
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_stc, eval_time = 2))
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_dyn, eval_time = 2))
+  expect_snapshot(last_fit(wflow, split, metrics = met_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_stc_dyn, eval_time = 2))
+  expect_snapshot(last_fit(wflow, split, metrics = met_stc_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_dyn_stc, eval_time = 2))
+  expect_snapshot(last_fit(wflow, split, metrics = met_dyn_int, eval_time = 2), error = TRUE)
+
+  expect_snapshot(last_fit(wflow, split, metrics = met_int_stc, eval_time = 2), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_int_dyn, eval_time = 2), error = TRUE)
+
+  # multiple eval times
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_stc, eval_time = 1:3))
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_dyn, eval_time = 1:3))
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_int, eval_time = 1:3))
+
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_stc_dyn, eval_time = 1:3))
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_stc_int, eval_time = 1:3))
+
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_dyn_stc, eval_time = 1:3))
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_dyn_int, eval_time = 1:3))
+
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_int_stc, eval_time = 1:3))
+  expect_snapshot(res <- last_fit(wflow, split, metrics = met_int_dyn, eval_time = 1:3))
+
+
+})
+
diff --git a/tests/testthat/test-survival-tune-metric-arguments.R b/tests/testthat/test-survival-tune-metric-arguments.R
new file mode 100644
index 0000000..89fdbad
--- /dev/null
+++ b/tests/testthat/test-survival-tune-metric-arguments.R
@@ -0,0 +1,60 @@
+
+test_that("metric inputs are checked for censored regression models", {
+  skip_if_not_installed("censored")
+  library(parsnip)
+  library(workflows)
+  library(yardstick)
+  library(rsample)
+  library(censored)
+
+  stanford2$event_time <- Surv(stanford2$time, stanford2$status)
+  stanford2 <- stanford2[, c("event_time", "age")]
+
+  wflow <- workflow(event_time ~ age, survival_reg())
+  sr_spec <- survival_reg(dist = tune())
+  wflow_tune <- workflow(event_time ~ age, sr_spec)
+
+  set.seed(1)
+  split <- initial_split(stanford2)
+  rs <- vfold_cv(stanford2)
+
+  # ------------------------------------------------------------------------------
+  # setup metric sets
+
+  met_srv <- metric_set(concordance_survival)
+  met_reg <- metric_set(rmse)
+  met_cls <- metric_set(brier_class)
+
+  # ------------------------------------------------------------------------------
+  # check inputs
+
+  expect_snapshot(check_metrics_arg(NULL, wflow))
+
+  expect_snapshot(check_metrics_arg(met_reg, wflow), error = TRUE)
+  expect_snapshot(check_metrics_arg(met_cls, wflow), error = TRUE)
+  expect_snapshot(check_metrics_arg(met_srv, wflow))
+
+  # ------------------------------------------------------------------------------
+  # resampling
+
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_cls), error = TRUE)
+  expect_snapshot(fit_resamples(wflow, rs, metrics = met_reg), error = TRUE)
+
+  # ------------------------------------------------------------------------------
+  # tuning
+
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_cls), error = TRUE)
+  expect_snapshot(tune_grid(wflow_tune, rs, metrics = met_reg), error = TRUE)
+
+  expect_snapshot(tune_bayes(wflow_tune, rs, metrics = met_cls), error = TRUE)
+  expect_snapshot(tune_bayes(wflow_tune, rs, metrics = met_reg), error = TRUE)
+
+  # ------------------------------------------------------------------------------
+  # final fit
+
+  expect_snapshot(last_fit(wflow, split, metrics = met_cls), error = TRUE)
+  expect_snapshot(last_fit(wflow, split, metrics = met_reg), error = TRUE)
+
+})
+
+