diff --git a/.Rbuildignore b/.Rbuildignore
index 849c555..498bcf2 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -15,3 +15,5 @@
 ^vignettes/articles$
 ^CRAN-SUBMISSION$
 ^revdep$
+^[.]?air[.]toml$
+^\.vscode$
diff --git a/.github/workflows/format-check.yaml b/.github/workflows/format-check.yaml
new file mode 100644
index 0000000..e29e3c4
--- /dev/null
+++ b/.github/workflows/format-check.yaml
@@ -0,0 +1,23 @@
+# Workflow derived from https://github.com/posit-dev/setup-air/tree/main/examples
+
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+
+name: format-check.yaml
+
+permissions: read-all
+
+jobs:
+  format-check:
+    name: format-check
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install
+        uses: posit-dev/setup-air@v1
+
+      - name: Check
+        run: air format . --check
diff --git a/.github/workflows/format-suggest.yaml b/.github/workflows/format-suggest.yaml
new file mode 100644
index 0000000..8c4f117
--- /dev/null
+++ b/.github/workflows/format-suggest.yaml
@@ -0,0 +1,46 @@
+# Workflow derived from https://github.com/posit-dev/setup-air/tree/main/examples
+
+on:
+  # Using `pull_request_target` over `pull_request` for elevated `GITHUB_TOKEN`
+  # privileges, otherwise we can't set `pull-requests: write` when the pull
+  # request comes from a fork, which is our main use case (external contributors).
+  #
+  # `pull_request_target` runs in the context of the target branch (`main`, usually),
+  # rather than in the context of the pull request like `pull_request` does. Due
+  # to this, we must explicitly checkout `ref: ${{ github.event.pull_request.head.sha }}`.
+  # This is typically frowned upon by GitHub, as it exposes you to potentially running
+  # untrusted code in a context where you have elevated privileges, but they explicitly
+  # call out the use case of reformatting and committing back / commenting on the PR
+  # as a situation that should be safe (because we aren't actually running the untrusted
+  # code, we are just treating it as passive data).
+  # https://securitylab.github.com/resources/github-actions-preventing-pwn-requests/
+  pull_request_target:
+
+name: format-suggest.yaml
+
+jobs:
+  format-suggest:
+    name: format-suggest
+    runs-on: ubuntu-latest
+
+    permissions:
+      # Required to push suggestion comments to the PR
+      pull-requests: write
+
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          ref: ${{ github.event.pull_request.head.sha }}
+
+      - name: Install
+        uses: posit-dev/setup-air@v1
+
+      - name: Format
+        run: air format .
+
+      - name: Suggest
+        uses: reviewdog/action-suggester@v1
+        with:
+          level: error
+          fail_level: error
+          tool_name: air
diff --git a/.vscode/extensions.json b/.vscode/extensions.json
new file mode 100644
index 0000000..344f76e
--- /dev/null
+++ b/.vscode/extensions.json
@@ -0,0 +1,5 @@
+{
+    "recommendations": [
+        "Posit.air-vscode"
+    ]
+}
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000..a9f69fe
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,10 @@
+{
+    "[r]": {
+        "editor.formatOnSave": true,
+        "editor.defaultFormatter": "Posit.air-vscode"
+    },
+    "[quarto]": {
+        "editor.formatOnSave": true,
+        "editor.defaultFormatter": "quarto.quarto"
+    }
+}
diff --git a/R/autoplot.R b/R/autoplot.R
index 5e1ca0c..b049a85 100644
--- a/R/autoplot.R
+++ b/R/autoplot.R
@@ -64,10 +64,11 @@ autoplot.spatial_rset <- function(object, ..., alpha = 0.6) {
     mapping = ggplot2::aes(color = .fold., fill = .fold.)
   )
   p <- p + ggplot2::geom_sf(..., alpha = alpha)
-  p <- p + ggplot2::guides(
-    colour = ggplot2::guide_legend("Fold"),
-    fill = ggplot2::guide_legend("Fold")
-  )
+  p <- p +
+    ggplot2::guides(
+      colour = ggplot2::guide_legend("Fold"),
+      fill = ggplot2::guide_legend("Fold")
+    )
 
   if (sum(bool_id_columns) == 2) {
     p <- p + ggplot2::facet_wrap(ggplot2::vars(.facet.))
@@ -97,10 +98,11 @@ autoplot.spatial_rsplit <- function(object, ..., alpha = 0.6) {
     data = object,
     mapping = ggplot2::aes(color = .class., fill = .class.)
   )
-  p <- p + ggplot2::guides(
-    colour = ggplot2::guide_legend("Class"),
-    fill = ggplot2::guide_legend("Class")
-  )
+  p <- p +
+    ggplot2::guides(
+      colour = ggplot2::guide_legend("Class"),
+      fill = ggplot2::guide_legend("Class")
+    )
   p <- p + ggplot2::geom_sf(..., alpha = alpha)
   p + ggplot2::coord_sf()
 }
@@ -109,7 +111,12 @@ autoplot.spatial_rsplit <- function(object, ..., alpha = 0.6) {
 #' @param show_grid When plotting [spatial_block_cv] objects, should the grid
 #' itself be drawn on top of the data? Set to FALSE to remove the grid.
 #' @export
-autoplot.spatial_block_cv <- function(object, show_grid = TRUE, ..., alpha = 0.6) {
+autoplot.spatial_block_cv <- function(
+  object,
+  show_grid = TRUE,
+  ...,
+  alpha = 0.6
+) {
   p <- autoplot.spatial_rset(object, ..., alpha = alpha)
 
   if (!show_grid) {
diff --git a/R/buffer.R b/R/buffer.R
index 99aa44c..fa1a45d 100644
--- a/R/buffer.R
+++ b/R/buffer.R
@@ -10,7 +10,13 @@
 #' or assessment set. If `NULL`, no buffer is applied.
 #'
 #' @keywords internal
-buffer_indices <- function(data, indices, radius, buffer, call = rlang::caller_env()) {
+buffer_indices <- function(
+  data,
+  indices,
+  radius,
+  buffer,
+  call = rlang::caller_env()
+) {
   standard_checks(data, "Buffering", call)
 
   n <- nrow(data)
@@ -30,15 +36,21 @@ buffer_indices <- function(data, indices, radius, buffer, call = rlang::caller_e
   run_radius <- !is.null(radius)
   if (run_radius && units::set_units(radius, NULL) > 0) {
     # In case `radius` has no units, assume it's in the same units as `data`
-    if (!identical(sf::st_crs(data), sf::NA_crs_)) units(radius) <- units(distmat)
+    if (!identical(sf::st_crs(data), sf::NA_crs_)) {
+      units(radius) <- units(distmat)
+    }
     indices <- row_ids_within_dist(distmat, indices, radius)
   }
 
   # `buffer_indices` are _always_ needed
   # so re-code a NULL buffer as a 0, which will buffer nothing
-  if (is.null(buffer)) buffer <- 0L
+  if (is.null(buffer)) {
+    buffer <- 0L
+  }
   # In case `buffer` has no units, assume it's in the same units as `data`
-  if (!identical(sf::st_crs(data), sf::NA_crs_)) units(buffer) <- units(distmat)
+  if (!identical(sf::st_crs(data), sf::NA_crs_)) {
+    units(buffer) <- units(distmat)
+  }
   buffer_indices <- row_ids_within_dist(distmat, indices, buffer)
 
   purrr::map2(indices, buffer_indices, buffered_complement, n = n)
diff --git a/R/checks.R b/R/checks.R
index ecee3b5..b82a8ae 100644
--- a/R/checks.R
+++ b/R/checks.R
@@ -14,7 +14,9 @@ check_s2 <- function(data, calling_function, call = rlang::caller_env()) {
   if (is_longlat(data) && !sf::sf_use_s2()) {
     rlang::abort(
       c(
-        glue::glue("{calling_function} can only process geographic coordinates when using the s2 geometry library."),
+        glue::glue(
+          "{calling_function} can only process geographic coordinates when using the s2 geometry library."
+        ),
         "i" = "Reproject your data into a projected coordinate reference system using `sf::st_transform()`.",
         "i" = "Or install the `s2` package and enable it using `sf::sf_use_s2(TRUE)`."
       ),
@@ -27,16 +29,24 @@ check_na_crs <- function(data, calling_function, call = rlang::caller_env()) {
   if (sf::st_crs(data) == sf::NA_crs_) {
     rlang::warn(
       c(
-        glue::glue("{calling_function} expects your data to have an appropriate coordinate reference system (CRS)."),
+        glue::glue(
+          "{calling_function} expects your data to have an appropriate coordinate reference system (CRS)."
+        ),
         i = "If possible, try setting a CRS using `sf::st_set_crs()`.",
-        i = glue::glue("Otherwise, {tolower(calling_function)} will assume your data is in projected coordinates.")
+        i = glue::glue(
+          "Otherwise, {tolower(calling_function)} will assume your data is in projected coordinates."
+        )
       ),
       call = call
     )
   }
 }
 
-standard_checks <- function(data, calling_function, call = rlang::caller_env()) {
+standard_checks <- function(
+  data,
+  calling_function,
+  call = rlang::caller_env()
+) {
   check_sf(data, calling_function, call)
   check_na_crs(data, calling_function, call)
   check_s2(data, calling_function, call)
@@ -47,12 +57,16 @@ standard_checks <- function(data, calling_function, call = rlang::caller_env())
 #' @param v The number of partitions for the resampling. Set to `NULL` or `Inf`
 #' for the maximum sensible value (for leave-one-X-out cross-validation).
 #' @keywords internal
-check_v <- function(v,
-                    max_v,
-                    objects,
-                    allow_max_v = TRUE,
-                    call = rlang::caller_env()) {
-  if (is.null(v)) v <- Inf
+check_v <- function(
+  v,
+  max_v,
+  objects,
+  allow_max_v = TRUE,
+  call = rlang::caller_env()
+) {
+  if (is.null(v)) {
+    v <- Inf
+  }
 
   if (!rlang::is_integerish(v) || length(v) != 1 || v < 1) {
     rlang::abort("`v` must be a single positive integer.", call = call)
diff --git a/R/compat-vctrs-helpers.R b/R/compat-vctrs-helpers.R
index ea02d9b..1ca5a45 100644
--- a/R/compat-vctrs-helpers.R
+++ b/R/compat-vctrs-helpers.R
@@ -14,11 +14,21 @@ delayedAssign("rset_subclasses", {
     withr::with_seed(
       123,
       list(
-        spatial_block_cv              = spatial_block_cv(test_data()),
-        spatial_clustering_cv         = spatial_clustering_cv(test_data()),
-        spatial_buffer_vfold_cv       = spatial_buffer_vfold_cv(test_data(), radius = 1, buffer = 1),
-        spatial_leave_location_out_cv = spatial_leave_location_out_cv(test_data(), idx),
-        spatial_nndm_cv               = spatial_nndm_cv(test_data()[1:500, ], test_data()[501:682, ])
+        spatial_block_cv = spatial_block_cv(test_data()),
+        spatial_clustering_cv = spatial_clustering_cv(test_data()),
+        spatial_buffer_vfold_cv = spatial_buffer_vfold_cv(
+          test_data(),
+          radius = 1,
+          buffer = 1
+        ),
+        spatial_leave_location_out_cv = spatial_leave_location_out_cv(
+          test_data(),
+          idx
+        ),
+        spatial_nndm_cv = spatial_nndm_cv(
+          test_data()[1:500, ],
+          test_data()[501:682, ]
+        )
       )
     )
   } else {
diff --git a/R/compat-vctrs.R b/R/compat-vctrs.R
index fe36635..31e3097 100644
--- a/R/compat-vctrs.R
+++ b/R/compat-vctrs.R
@@ -5,7 +5,13 @@
 
 stop_incompatible_cast_rset <- function(x, to, ..., x_arg, to_arg) {
   details <- "Can't cast to an rset because attributes are likely incompatible."
-  vctrs::stop_incompatible_cast(x, to, x_arg = x_arg, to_arg = to_arg, details = details)
+  vctrs::stop_incompatible_cast(
+    x,
+    to,
+    x_arg = x_arg,
+    to_arg = to_arg,
+    details = details
+  )
 }
 
 stop_never_called <- function(fn) {
diff --git a/R/labels.R b/R/labels.R
index 690001b..44a3313 100644
--- a/R/labels.R
+++ b/R/labels.R
@@ -8,11 +8,14 @@ pretty.spatial_clustering_cv <- function(x, ...) {
 #' @export
 print.spatial_clustering_cv <- function(x, ...) {
   cat("# ", pretty(x), "\n")
-  class(x) <- class(x)[!(class(x) %in% c(
-    "spatial_clustering_cv",
-    "spatial_rset",
-    "rset"
-  ))]
+  class(x) <- class(x)[
+    !(class(x) %in%
+      c(
+        "spatial_clustering_cv",
+        "spatial_rset",
+        "rset"
+      ))
+  ]
   print(x, ...)
 }
 
@@ -26,11 +29,14 @@ pretty.spatial_block_cv <- function(x, ...) {
 #' @export
 print.spatial_block_cv <- function(x, ...) {
   cat("# ", pretty(x), "\n")
-  class(x) <- class(x)[!(class(x) %in% c(
-    "spatial_block_cv",
-    "spatial_rset",
-    "rset"
-  ))]
+  class(x) <- class(x)[
+    !(class(x) %in%
+      c(
+        "spatial_block_cv",
+        "spatial_rset",
+        "rset"
+      ))
+  ]
   print(x, ...)
 }
 
@@ -44,11 +50,14 @@ pretty.spatial_leave_location_out_cv <- function(x, ...) {
 #' @export
 print.spatial_leave_location_out_cv <- function(x, ...) {
   cat("# ", pretty(x), "\n")
-  class(x) <- class(x)[!(class(x) %in% c(
-    "spatial_leave_location_out_cv",
-    "spatial_rset",
-    "rset"
-  ))]
+  class(x) <- class(x)[
+    !(class(x) %in%
+      c(
+        "spatial_leave_location_out_cv",
+        "spatial_rset",
+        "rset"
+      ))
+  ]
   print(x, ...)
 }
 
@@ -62,10 +71,13 @@ pretty.spatial_buffer_vfold_cv <- function(x, ...) {
 #' @export
 print.spatial_buffer_vfold_cv <- function(x, ...) {
   cat("# ", pretty(x), "\n")
-  class(x) <- class(x)[!(class(x) %in% c(
-    "spatial_buffer_vfold_cv",
-    "spatial_rset",
-    "rset"
-  ))]
+  class(x) <- class(x)[
+    !(class(x) %in%
+      c(
+        "spatial_buffer_vfold_cv",
+        "spatial_rset",
+        "rset"
+      ))
+  ]
   print(x, ...)
 }
diff --git a/R/misc.R b/R/misc.R
index 006c36e..1cd0cec 100644
--- a/R/misc.R
+++ b/R/misc.R
@@ -27,7 +27,9 @@ split_unnamed <- function(x, f) {
 
 ## This will remove the assessment indices from an rsplit object
 rm_out <- function(x, buffer = NULL) {
-  if (is.null(buffer)) x$out_id <- NA
+  if (is.null(buffer)) {
+    x$out_id <- NA
+  }
   x
 }
 
diff --git a/R/spatial_block_cv.R b/R/spatial_block_cv.R
index 30a9007..0937ce7 100644
--- a/R/spatial_block_cv.R
+++ b/R/spatial_block_cv.R
@@ -61,15 +61,17 @@
 #' Ecography 40(8), pp. 913-929, doi: 10.1111/ecog.02881.
 #'
 #' @export
-spatial_block_cv <- function(data,
-                             method = c("random", "snake", "continuous"),
-                             v = 10,
-                             relevant_only = TRUE,
-                             radius = NULL,
-                             buffer = NULL,
-                             ...,
-                             repeats = 1,
-                             expand_bbox = 0.00001) {
+spatial_block_cv <- function(
+  data,
+  method = c("random", "snake", "continuous"),
+  v = 10,
+  relevant_only = TRUE,
+  radius = NULL,
+  buffer = NULL,
+  ...,
+  repeats = 1,
+  expand_bbox = 0.00001
+) {
   method <- rlang::arg_match(method)
 
   if (method != "random" && repeats != 1) {
@@ -103,7 +105,8 @@ spatial_block_cv <- function(data,
   original_number_of_blocks <- length(grid_blocks)
 
   block_fun <- function(method) {
-    switch(method,
+    switch(
+      method,
       "random" = random_block_cv(
         data,
         centroids,
@@ -140,7 +143,8 @@ spatial_block_cv <- function(data,
     }
   }
 
-  percent_used <- split_objs$filtered_number_of_blocks[[1]] / original_number_of_blocks
+  percent_used <- split_objs$filtered_number_of_blocks[[1]] /
+    original_number_of_blocks
 
   if (percent_used < 0.1) {
     percent_used <- round(percent_used * 100, 2)
@@ -186,12 +190,14 @@ expand_grid <- function(grid_box, expansion = 0.00001) {
   grid_box
 }
 
-random_block_cv <- function(data,
-                            centroids,
-                            grid_blocks,
-                            v,
-                            radius = NULL,
-                            buffer = NULL) {
+random_block_cv <- function(
+  data,
+  centroids,
+  grid_blocks,
+  v,
+  radius = NULL,
+  buffer = NULL
+) {
   n <- length(centroids)
 
   grid_blocks <- filter_grid_blocks(grid_blocks, centroids)
@@ -205,35 +211,45 @@ random_block_cv <- function(data,
   generate_folds_from_blocks(data, centroids, grid_blocks, v, n, radius, buffer)
 }
 
-systematic_block_cv <- function(data,
-                                centroids,
-                                grid_blocks,
-                                v,
-                                ordering = c("snake", "continuous"),
-                                relevant_only = TRUE,
-                                radius = NULL,
-                                buffer = NULL) {
+systematic_block_cv <- function(
+  data,
+  centroids,
+  grid_blocks,
+  v,
+  ordering = c("snake", "continuous"),
+  relevant_only = TRUE,
+  radius = NULL,
+  buffer = NULL
+) {
   n <- length(centroids)
   ordering <- rlang::arg_match(ordering)
 
-  if (relevant_only) grid_blocks <- filter_grid_blocks(grid_blocks, centroids)
+  if (relevant_only) {
+    grid_blocks <- filter_grid_blocks(grid_blocks, centroids)
+  }
 
   n_blocks <- length(grid_blocks)
   v <- check_v(v, n_blocks, "blocks", call = rlang::caller_env(2))
 
   folds <- rep(seq_len(v), length.out = length(grid_blocks))
-  if (ordering == "snake") folds <- make_snake_ordering(folds, grid_blocks)
+  if (ordering == "snake") {
+    folds <- make_snake_ordering(folds, grid_blocks)
+  }
 
   grid_blocks <- sf::st_as_sf(grid_blocks)
   grid_blocks$fold <- folds
-  if (!relevant_only) grid_blocks <- filter_grid_blocks(grid_blocks, centroids)
+  if (!relevant_only) {
+    grid_blocks <- filter_grid_blocks(grid_blocks, centroids)
+  }
 
   num_folds <- length(unique(grid_blocks$fold))
   if (num_folds != v) {
     rlang::warn(c(
       "Not all folds contained blocks with data:",
-      x = glue::glue("{v} folds were requested, \\
-                     but only {num_folds} contain any data."),
+      x = glue::glue(
+        "{v} folds were requested, \\
+                     but only {num_folds} contain any data."
+      ),
       x = "Empty folds were dropped.",
       i = "To avoid this, set `relevant_only = TRUE`."
     ))
@@ -243,7 +259,15 @@ systematic_block_cv <- function(data,
   generate_folds_from_blocks(data, centroids, grid_blocks, v, n, radius, buffer)
 }
 
-generate_folds_from_blocks <- function(data, centroids, grid_blocks, v, n, radius, buffer) {
+generate_folds_from_blocks <- function(
+  data,
+  centroids,
+  grid_blocks,
+  v,
+  n,
+  radius,
+  buffer
+) {
   filtered_number_of_blocks <- nrow(grid_blocks)
   grid_blocks <- split_unnamed(grid_blocks, grid_blocks$fold)
 
diff --git a/R/spatial_clustering_cv.R b/R/spatial_clustering_cv.R
index a1a587a..e7e7e33 100644
--- a/R/spatial_clustering_cv.R
+++ b/R/spatial_clustering_cv.R
@@ -82,14 +82,16 @@
 #'
 #' @rdname spatial_clustering_cv
 #' @export
-spatial_clustering_cv <- function(data,
-                                  v = 10,
-                                  cluster_function = c("kmeans", "hclust"),
-                                  radius = NULL,
-                                  buffer = NULL,
-                                  ...,
-                                  repeats = 1,
-                                  distance_function = function(x) as.dist(sf::st_distance(x))) {
+spatial_clustering_cv <- function(
+  data,
+  v = 10,
+  cluster_function = c("kmeans", "hclust"),
+  radius = NULL,
+  buffer = NULL,
+  ...,
+  repeats = 1,
+  distance_function = function(x) as.dist(sf::st_distance(x))
+) {
   if (!rlang::is_function(cluster_function)) {
     cluster_function <- rlang::arg_match(cluster_function)
   }
diff --git a/R/spatial_nndm_cv.R b/R/spatial_nndm_cv.R
index fad578f..5b512d8 100644
--- a/R/spatial_nndm_cv.R
+++ b/R/spatial_nndm_cv.R
@@ -63,10 +63,14 @@
 #' spatial_nndm_cv(ames_sf[1:100, ], ames_sf[2001:2100, ])
 #'
 #' @export
-spatial_nndm_cv <- function(data, prediction_sites, ...,
-                            autocorrelation_range = NULL,
-                            prediction_sample_size = 1000,
-                            min_analysis_proportion = 0.5) {
+spatial_nndm_cv <- function(
+  data,
+  prediction_sites,
+  ...,
+  autocorrelation_range = NULL,
+  prediction_sample_size = 1000,
+  min_analysis_proportion = 0.5
+) {
   # Data validation: check that all dots are used,
   # that data and prediction_sites are sf objects,
   # that data has a CRS and s2 is enabled if necessary
@@ -120,10 +124,8 @@ spatial_nndm_cv <- function(data, prediction_sites, ...,
   pred_geometry <- unique(sf::st_geometry_type(prediction_sites))
 
   use_provided_points <- length(pred_geometry) == 1 && pred_geometry == "POINT"
-  sample_provided_poly <- length(pred_geometry) == 1 && pred_geometry %in% c(
-    "POLYGON",
-    "MULTIPOLYGON"
-  )
+  sample_provided_poly <- length(pred_geometry) == 1 &&
+    pred_geometry %in% c("POLYGON", "MULTIPOLYGON")
 
   if (use_provided_points) {
     prediction_sites <- prediction_sites
@@ -221,11 +223,13 @@ spatial_nndm_cv <- function(data, prediction_sites, ...,
     # How much data remains in analysis sets?
     prop_remaining <- sum(
       !is.na(distance_matrix[current_neighbor$row, ])
-    ) / n_training
-
-    if ((prop_close_training >= prop_close_prediction) &
-      (prop_remaining > min_analysis_proportion)) {
+    ) /
+      n_training
 
+    if (
+      (prop_close_training >= prop_close_prediction) &
+        (prop_remaining > min_analysis_proportion)
+    ) {
       # Remove nearest neighbors from analysis sets until the % of points with
       # an NN in analysis at distance X in analysis ~= the % of points
       # in predict with NN in train at distance X
@@ -287,10 +291,22 @@ spatial_nndm_cv <- function(data, prediction_sites, ...,
   )
 }
 
-find_next_neighbor <- function(current_neighbor, dist_to_nn_training, distance_matrix, equal_distance_ok = FALSE) {
+find_next_neighbor <- function(
+  current_neighbor,
+  dist_to_nn_training,
+  distance_matrix,
+  equal_distance_ok = FALSE
+) {
   operator <- if (equal_distance_ok) `>=` else `>`
-  current_neighbor$distance <- min(dist_to_nn_training[operator(dist_to_nn_training, current_neighbor$distance)])
-  current_neighbor$row <- which(dist_to_nn_training == current_neighbor$distance)[1]
-  current_neighbor$col <- which(distance_matrix[current_neighbor$row, ] == current_neighbor$distance)
+  current_neighbor$distance <- min(dist_to_nn_training[operator(
+    dist_to_nn_training,
+    current_neighbor$distance
+  )])
+  current_neighbor$row <- which(
+    dist_to_nn_training == current_neighbor$distance
+  )[1]
+  current_neighbor$col <- which(
+    distance_matrix[current_neighbor$row, ] == current_neighbor$distance
+  )
   current_neighbor
 }
diff --git a/R/spatial_vfold_cv.R b/R/spatial_vfold_cv.R
index c029131..6d1863e 100644
--- a/R/spatial_vfold_cv.R
+++ b/R/spatial_vfold_cv.R
@@ -61,21 +61,25 @@
 #' ames_neighborhoods <- spatial_leave_location_out_cv(ames_sf, Neighborhood)
 #'
 #' @export
-spatial_buffer_vfold_cv <- function(data,
-                                    radius,
-                                    buffer,
-                                    v = 10,
-                                    repeats = 1,
-                                    strata = NULL,
-                                    breaks = 4,
-                                    pool = 0.1,
-                                    ...) {
+spatial_buffer_vfold_cv <- function(
+  data,
+  radius,
+  buffer,
+  v = 10,
+  repeats = 1,
+  strata = NULL,
+  breaks = 4,
+  pool = 0.1,
+  ...
+) {
   standard_checks(data, "`spatial_buffer_vfold_cv()`")
 
   if (missing(radius) || missing(buffer)) {
     use_vfold <- NULL
     if (missing(radius) && missing(buffer)) {
-      use_vfold <- c(i = "Or use `rsample::vfold_cv() to use a non-spatial V-fold.")
+      use_vfold <- c(
+        i = "Or use `rsample::vfold_cv() to use a non-spatial V-fold."
+      )
     }
     rlang::abort(
       c(
@@ -121,7 +125,9 @@ spatial_buffer_vfold_cv <- function(data,
     if (length(strata) == 0) strata <- NULL
   }
 
-  if (!is.null(strata)) names(strata) <- NULL
+  if (!is.null(strata)) {
+    names(strata) <- NULL
+  }
   cv_att <- list(
     v = v,
     repeats = repeats,
@@ -159,13 +165,15 @@ spatial_buffer_vfold_cv <- function(data,
 #' @rdname spatial_vfold
 #'
 #' @export
-spatial_leave_location_out_cv <- function(data,
-                                          group,
-                                          v = NULL,
-                                          radius = NULL,
-                                          buffer = NULL,
-                                          ...,
-                                          repeats = 1) {
+spatial_leave_location_out_cv <- function(
+  data,
+  group,
+  v = NULL,
+  radius = NULL,
+  buffer = NULL,
+  ...,
+  repeats = 1
+) {
   if (!missing(group)) {
     group <- tidyselect::eval_select(rlang::enquo(group), data)
   }
@@ -173,7 +181,9 @@ spatial_leave_location_out_cv <- function(data,
   if (missing(group) || length(group) == 0) {
     group <- NULL
   } else {
-    if (is.null(v)) v <- length(unique(data[[group]]))
+    if (is.null(v)) {
+      v <- length(unique(data[[group]]))
+    }
     v <- check_v(v, length(unique(data[[group]])), "locations")
     n <- nrow(data)
     if (v == n && repeats > 1) {
@@ -223,15 +233,17 @@ spatial_leave_location_out_cv <- function(data,
   )
 }
 
-posthoc_buffer_rset <- function(data,
-                                rset,
-                                rsplit_class,
-                                rset_class,
-                                radius,
-                                buffer,
-                                n,
-                                v,
-                                cv_att) {
+posthoc_buffer_rset <- function(
+  data,
+  rset,
+  rsplit_class,
+  rset_class,
+  radius,
+  buffer,
+  n,
+  v,
+  cv_att
+) {
   # This basically undoes everything post-`split_unnamed` for us
   # so we're back to an unnamed list of assessment-set indices
   indices <- purrr::map(rset$splits, as.integer, "assessment")
diff --git a/R/zzz-compat-vctrs-spatial_block_cv.R b/R/zzz-compat-vctrs-spatial_block_cv.R
index 7e2d071..dea4ce4 100644
--- a/R/zzz-compat-vctrs-spatial_block_cv.R
+++ b/R/zzz-compat-vctrs-spatial_block_cv.R
@@ -58,23 +58,53 @@ vec_restore.spatial_block_cv <- function(x, to, ...) {
 # bootstraps object.
 
 #' @export
-vec_ptype2.spatial_block_cv.spatial_block_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_block_cv.spatial_block_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_block_cv.spatial_block_cv")
 }
 #' @export
-vec_ptype2.spatial_block_cv.tbl_df <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_block_cv.tbl_df <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_block_cv.tbl_df")
 }
 #' @export
-vec_ptype2.tbl_df.spatial_block_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.tbl_df.spatial_block_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.tbl_df.spatial_block_cv")
 }
 #' @export
-vec_ptype2.spatial_block_cv.data.frame <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_block_cv.data.frame <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_block_cv.data.frame")
 }
 #' @export
-vec_ptype2.data.frame.spatial_block_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.data.frame.spatial_block_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.data.frame.spatial_block_cv")
 }
 
@@ -90,22 +120,52 @@ vec_ptype2.data.frame.spatial_block_cv <- function(x, y, ..., x_arg = "", y_arg
 # with all of the data in `x` cast to the type of `to`.
 
 #' @export
-vec_cast.spatial_block_cv.spatial_block_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_block_cv.spatial_block_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_block_cv.tbl_df <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_block_cv.tbl_df <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.tbl_df.spatial_block_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.tbl_df.spatial_block_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   tib_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_block_cv.data.frame <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_block_cv.data.frame <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.data.frame.spatial_block_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.data.frame.spatial_block_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   df_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
diff --git a/R/zzz-compat-vctrs-spatial_buffer_vfold_cv.R b/R/zzz-compat-vctrs-spatial_buffer_vfold_cv.R
index dcc3b6b..a35d154 100644
--- a/R/zzz-compat-vctrs-spatial_buffer_vfold_cv.R
+++ b/R/zzz-compat-vctrs-spatial_buffer_vfold_cv.R
@@ -58,23 +58,55 @@ vec_restore.spatial_buffer_vfold_cv <- function(x, to, ...) {
 # bootstraps object.
 
 #' @export
-vec_ptype2.spatial_buffer_vfold_cv.spatial_buffer_vfold_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
-  stop_never_called("vec_ptype2.spatial_buffer_vfold_cv.spatial_buffer_vfold_cv")
+vec_ptype2.spatial_buffer_vfold_cv.spatial_buffer_vfold_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
+  stop_never_called(
+    "vec_ptype2.spatial_buffer_vfold_cv.spatial_buffer_vfold_cv"
+  )
 }
 #' @export
-vec_ptype2.spatial_buffer_vfold_cv.tbl_df <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_buffer_vfold_cv.tbl_df <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_buffer_vfold_cv.tbl_df")
 }
 #' @export
-vec_ptype2.tbl_df.spatial_buffer_vfold_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.tbl_df.spatial_buffer_vfold_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.tbl_df.spatial_buffer_vfold_cv")
 }
 #' @export
-vec_ptype2.spatial_buffer_vfold_cv.data.frame <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_buffer_vfold_cv.data.frame <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_buffer_vfold_cv.data.frame")
 }
 #' @export
-vec_ptype2.data.frame.spatial_buffer_vfold_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.data.frame.spatial_buffer_vfold_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.data.frame.spatial_buffer_vfold_cv")
 }
 
@@ -90,22 +122,52 @@ vec_ptype2.data.frame.spatial_buffer_vfold_cv <- function(x, y, ..., x_arg = "",
 # with all of the data in `x` cast to the type of `to`.
 
 #' @export
-vec_cast.spatial_buffer_vfold_cv.spatial_buffer_vfold_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_buffer_vfold_cv.spatial_buffer_vfold_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_buffer_vfold_cv.tbl_df <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_buffer_vfold_cv.tbl_df <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.tbl_df.spatial_buffer_vfold_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.tbl_df.spatial_buffer_vfold_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   tib_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_buffer_vfold_cv.data.frame <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_buffer_vfold_cv.data.frame <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.data.frame.spatial_buffer_vfold_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.data.frame.spatial_buffer_vfold_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   df_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
diff --git a/R/zzz-compat-vctrs-spatial_clustering_cv.R b/R/zzz-compat-vctrs-spatial_clustering_cv.R
index 6036fd9..d84cb0b 100644
--- a/R/zzz-compat-vctrs-spatial_clustering_cv.R
+++ b/R/zzz-compat-vctrs-spatial_clustering_cv.R
@@ -58,23 +58,53 @@ vec_restore.spatial_clustering_cv <- function(x, to, ...) {
 # bootstraps object.
 
 #' @export
-vec_ptype2.spatial_clustering_cv.spatial_clustering_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_clustering_cv.spatial_clustering_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_clustering_cv.spatial_clustering_cv")
 }
 #' @export
-vec_ptype2.spatial_clustering_cv.tbl_df <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_clustering_cv.tbl_df <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_clustering_cv.tbl_df")
 }
 #' @export
-vec_ptype2.tbl_df.spatial_clustering_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.tbl_df.spatial_clustering_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.tbl_df.spatial_clustering_cv")
 }
 #' @export
-vec_ptype2.spatial_clustering_cv.data.frame <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_clustering_cv.data.frame <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_clustering_cv.data.frame")
 }
 #' @export
-vec_ptype2.data.frame.spatial_clustering_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.data.frame.spatial_clustering_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.data.frame.spatial_clustering_cv")
 }
 
@@ -90,22 +120,52 @@ vec_ptype2.data.frame.spatial_clustering_cv <- function(x, y, ..., x_arg = "", y
 # with all of the data in `x` cast to the type of `to`.
 
 #' @export
-vec_cast.spatial_clustering_cv.spatial_clustering_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_clustering_cv.spatial_clustering_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_clustering_cv.tbl_df <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_clustering_cv.tbl_df <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.tbl_df.spatial_clustering_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.tbl_df.spatial_clustering_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   tib_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_clustering_cv.data.frame <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_clustering_cv.data.frame <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.data.frame.spatial_clustering_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.data.frame.spatial_clustering_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   df_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
diff --git a/R/zzz-compat-vctrs-spatial_leave_location_out_cv.R b/R/zzz-compat-vctrs-spatial_leave_location_out_cv.R
index 58e0019..4ed7d2b 100644
--- a/R/zzz-compat-vctrs-spatial_leave_location_out_cv.R
+++ b/R/zzz-compat-vctrs-spatial_leave_location_out_cv.R
@@ -58,23 +58,55 @@ vec_restore.spatial_leave_location_out_cv <- function(x, to, ...) {
 # bootstraps object.
 
 #' @export
-vec_ptype2.spatial_leave_location_out_cv.spatial_leave_location_out_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
-  stop_never_called("vec_ptype2.spatial_leave_location_out_cv.spatial_leave_location_out_cv")
+vec_ptype2.spatial_leave_location_out_cv.spatial_leave_location_out_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
+  stop_never_called(
+    "vec_ptype2.spatial_leave_location_out_cv.spatial_leave_location_out_cv"
+  )
 }
 #' @export
-vec_ptype2.spatial_leave_location_out_cv.tbl_df <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_leave_location_out_cv.tbl_df <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_leave_location_out_cv.tbl_df")
 }
 #' @export
-vec_ptype2.tbl_df.spatial_leave_location_out_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.tbl_df.spatial_leave_location_out_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.tbl_df.spatial_leave_location_out_cv")
 }
 #' @export
-vec_ptype2.spatial_leave_location_out_cv.data.frame <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_leave_location_out_cv.data.frame <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_leave_location_out_cv.data.frame")
 }
 #' @export
-vec_ptype2.data.frame.spatial_leave_location_out_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.data.frame.spatial_leave_location_out_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.data.frame.spatial_leave_location_out_cv")
 }
 
@@ -90,22 +122,52 @@ vec_ptype2.data.frame.spatial_leave_location_out_cv <- function(x, y, ..., x_arg
 # with all of the data in `x` cast to the type of `to`.
 
 #' @export
-vec_cast.spatial_leave_location_out_cv.spatial_leave_location_out_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_leave_location_out_cv.spatial_leave_location_out_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_leave_location_out_cv.tbl_df <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_leave_location_out_cv.tbl_df <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.tbl_df.spatial_leave_location_out_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.tbl_df.spatial_leave_location_out_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   tib_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_leave_location_out_cv.data.frame <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_leave_location_out_cv.data.frame <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.data.frame.spatial_leave_location_out_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.data.frame.spatial_leave_location_out_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   df_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
diff --git a/R/zzz-compat-vctrs-spatial_nndm_cv.R b/R/zzz-compat-vctrs-spatial_nndm_cv.R
index 92e04a6..467a49b 100644
--- a/R/zzz-compat-vctrs-spatial_nndm_cv.R
+++ b/R/zzz-compat-vctrs-spatial_nndm_cv.R
@@ -58,23 +58,53 @@ vec_restore.spatial_nndm_cv <- function(x, to, ...) {
 # bootstraps object.
 
 #' @export
-vec_ptype2.spatial_nndm_cv.spatial_nndm_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_nndm_cv.spatial_nndm_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_nndm_cv.spatial_nndm_cv")
 }
 #' @export
-vec_ptype2.spatial_nndm_cv.tbl_df <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_nndm_cv.tbl_df <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_nndm_cv.tbl_df")
 }
 #' @export
-vec_ptype2.tbl_df.spatial_nndm_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.tbl_df.spatial_nndm_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.tbl_df.spatial_nndm_cv")
 }
 #' @export
-vec_ptype2.spatial_nndm_cv.data.frame <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.spatial_nndm_cv.data.frame <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.spatial_nndm_cv.data.frame")
 }
 #' @export
-vec_ptype2.data.frame.spatial_nndm_cv <- function(x, y, ..., x_arg = "", y_arg = "") {
+vec_ptype2.data.frame.spatial_nndm_cv <- function(
+  x,
+  y,
+  ...,
+  x_arg = "",
+  y_arg = ""
+) {
   stop_never_called("vec_ptype2.data.frame.spatial_nndm_cv")
 }
 
@@ -90,22 +120,52 @@ vec_ptype2.data.frame.spatial_nndm_cv <- function(x, y, ..., x_arg = "", y_arg =
 # with all of the data in `x` cast to the type of `to`.
 
 #' @export
-vec_cast.spatial_nndm_cv.spatial_nndm_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_nndm_cv.spatial_nndm_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_nndm_cv.tbl_df <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_nndm_cv.tbl_df <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.tbl_df.spatial_nndm_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.tbl_df.spatial_nndm_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   tib_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.spatial_nndm_cv.data.frame <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.spatial_nndm_cv.data.frame <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   stop_incompatible_cast_rset(x, to, x_arg = x_arg, to_arg = to_arg)
 }
 #' @export
-vec_cast.data.frame.spatial_nndm_cv <- function(x, to, ..., x_arg = "", to_arg = "") {
+vec_cast.data.frame.spatial_nndm_cv <- function(
+  x,
+  to,
+  ...,
+  x_arg = "",
+  to_arg = ""
+) {
   df_cast(x, to, ..., x_arg = x_arg, to_arg = to_arg)
 }
diff --git a/air.toml b/air.toml
new file mode 100644
index 0000000..b2c21bf
--- /dev/null
+++ b/air.toml
@@ -0,0 +1,2 @@
+[format]
+exclude = ["inst/vctrs_template.R"]
diff --git a/data-raw/boston_canopy.R b/data-raw/boston_canopy.R
index 8a19759..8416e6f 100644
--- a/data-raw/boston_canopy.R
+++ b/data-raw/boston_canopy.R
@@ -1,6 +1,8 @@
 ## code to prepare `boston_canopy` dataset goes here
 working_dir <- file.path(tempdir(), "boston_canopy")
-if (!dir.exists(working_dir)) dir.create(working_dir)
+if (!dir.exists(working_dir)) {
+  dir.create(working_dir)
+}
 
 download.file(
   "https://bostonopendata-boston.opendata.arcgis.com/datasets/boston::hex-tree-canopy-change-metrics.zip?outSR=%7B%22latestWkid%22%3A2249%2C%22wkid%22%3A102686%7D",
diff --git a/data/boston_canopy.R b/data/boston_canopy.R
index 4472d57..c512e60 100644
--- a/data/boston_canopy.R
+++ b/data/boston_canopy.R
@@ -1,4 +1,7 @@
-delayedAssign("boston_canopy", local({
-  requireNamespace("sf", quietly = TRUE)
-  spatialsample:::boston_canopy
-}))
+delayedAssign(
+  "boston_canopy",
+  local({
+    requireNamespace("sf", quietly = TRUE)
+    spatialsample:::boston_canopy
+  })
+)
diff --git a/tests/testthat/test-buffer.R b/tests/testthat/test-buffer.R
index 4b1b4bb..262c2be 100644
--- a/tests/testthat/test-buffer.R
+++ b/tests/testthat/test-buffer.R
@@ -248,7 +248,6 @@ test_that("using buffers", {
     )
   )
 
-
   # The default RNG changed in 3.6.0
   skip_if_not(getRversion() >= numeric_version("3.6.0"))
 
diff --git a/tests/testthat/test-compat-dplyr.R b/tests/testthat/test-compat-dplyr.R
index c41724e..76791d6 100644
--- a/tests/testthat/test-compat-dplyr.R
+++ b/tests/testthat/test-compat-dplyr.R
@@ -132,7 +132,11 @@ test_that("summarise() always drops the rset class", {
 test_that("group_by() always returns a bare grouped-df or bare tibble", {
   for (x in rset_subclasses) {
     expect_s3_class_bare_tibble(group_by(x))
-    expect_s3_class(group_by(x, splits), c("grouped_df", "tbl_df", "tbl", "data.frame"), exact = TRUE)
+    expect_s3_class(
+      group_by(x, splits),
+      c("grouped_df", "tbl_df", "tbl", "data.frame"),
+      exact = TRUE
+    )
   }
 })
 
diff --git a/tests/testthat/test-spatial_block_cv.R b/tests/testthat/test-spatial_block_cv.R
index 676f776..9e7d1cd 100644
--- a/tests/testthat/test-spatial_block_cv.R
+++ b/tests/testthat/test-spatial_block_cv.R
@@ -148,7 +148,8 @@ test_that("systematic assignment -- continuous", {
   expect_true(all(good_holdout))
 
   set.seed(123)
-  rs3 <- spatial_block_cv(ames_sf,
+  rs3 <- spatial_block_cv(
+    ames_sf,
     method = "continuous",
     relevant_only = FALSE,
     v = 4
diff --git a/tests/testthat/test-spatial_nndm_cv.R b/tests/testthat/test-spatial_nndm_cv.R
index aad44c8..f2e8328 100644
--- a/tests/testthat/test-spatial_nndm_cv.R
+++ b/tests/testthat/test-spatial_nndm_cv.R
@@ -11,7 +11,6 @@ Smithsonian_sf <- sf::st_as_sf(
 )
 
 test_that("bad args", {
-
   expect_snapshot(
     spatial_nndm_cv(Smithsonian_sf[1:15, ], Smithsonian[16:20, ]),
     error = TRUE
@@ -97,7 +96,6 @@ test_that("can pass a single polygon to sample within", {
 })
 
 
-
 test_that("printing", {
   skip_if_not(sf::sf_use_s2())
   # The default RNG changed in 3.6.0
@@ -120,7 +118,7 @@ test_that("passing a polygon works correctly", {
   skip_if_not(sf::sf_use_s2())
   ames_sf <- sf::st_as_sf(
     modeldata::ames,
-    coords = c("Longitude", "Latitude"), 
+    coords = c("Longitude", "Latitude"),
     crs = 4326
   )
   ch <- sf::st_as_sfc(sf::st_bbox(ames_sf))
@@ -136,4 +134,4 @@ test_that("passing a polygon works correctly", {
     nndm_2 <- spatial_nndm_cv(ames_sf[1:100, ], ch)
   )
   expect_identical(nndm_1, nndm_2)
-})
\ No newline at end of file
+})
diff --git a/tests/testthat/test-spatial_vfold_cv.R b/tests/testthat/test-spatial_vfold_cv.R
index e99380b..c6e1fe5 100644
--- a/tests/testthat/test-spatial_vfold_cv.R
+++ b/tests/testthat/test-spatial_vfold_cv.R
@@ -15,7 +15,11 @@ test_that("erroring when no S2", {
     error = TRUE
   )
   expect_snapshot(
-    suppressMessages(spatial_leave_location_out_cv(ames_sf, Neighborhood, buffer = 500)),
+    suppressMessages(spatial_leave_location_out_cv(
+      ames_sf,
+      Neighborhood,
+      buffer = 500
+    )),
     error = TRUE
   )
   sf::sf_use_s2(s2_store)
@@ -185,7 +189,12 @@ test_that("bad args", {
 
   set.seed(123)
   expect_snapshot(
-    spatial_buffer_vfold_cv(ames_sf, v = c(5, 10), buffer = NULL, radius = NULL),
+    spatial_buffer_vfold_cv(
+      ames_sf,
+      v = c(5, 10),
+      buffer = NULL,
+      radius = NULL
+    ),
     error = TRUE
   )
 
@@ -198,7 +207,12 @@ test_that("bad args", {
 
   set.seed(123)
   expect_snapshot(
-    spatial_buffer_vfold_cv(boston_canopy, v = 683, buffer = NULL, radius = NULL)
+    spatial_buffer_vfold_cv(
+      boston_canopy,
+      v = 683,
+      buffer = NULL,
+      radius = NULL
+    )
   )
 
   set.seed(123)