Manually parsing geojson into a dataframe

I would like to work step by step to convert a .geojson into a tibble (or dataframe).

Here's a minimalistic geojson example which I stored in a file called test.geojson (note that the geometry field is null but this does not matter here) :

{"type": "FeatureCollection",
  "features": [
    { "type": "Feature", "properties": { "VAR_1": 31,"VAR_2": "abc","VAR_3": 255 }, "geometry" : null },
    { "type": "Feature", "properties": { "VAR_1": 23,"VAR_2": "def","VAR_3": 876 }, "geometry" : null }
	]}

Desired result (here assuming that geometry is filled with two coordinates instead of being null)

# A tibble: 2 x 3
  VAR_1 VAR_2 VAR_3 geometry
  <dbl> <chr> <dbl> <list>
1    31 abc     255 <dbl [2]>
2    23 def     876 <dbl [2]>

I'd partiularly like a {tidyverse} based solution. What I've been trying for now is iterate through each features to try and build a dataframe but I can't find a way to nicely add the geometry field :

# Read geojson
js <- jsonlite::read_json("test.geojson") 

# Iterate through each features ... 
map_dfr(1:length(js$features), .f = function(i){
  
  df <- js$features[[i]]$properties # this works but only importing VAR_1, VAR_2, VAR_3
 
  df |> mutate(geometry = js$features[[i]]$geometry) # this does not work
  
})

Note : One could use {geojsonsf} to import this directly as sf object with sf <- geojsonsf::geojson_sf("test.geojson") but I want to do it step by step, ending up on a tibble and understanding what I'm doing.

Thanks a lot for helping !

Assuming the data is something like this:

x <- '{"type": "FeatureCollection",
  "features": [
    { "type": "Feature", "properties": { "VAR_1": 31,"VAR_2": "abc","VAR_3": 255 }, "geometry" : [-74.0060, 40.7128]},
    { "type": "Feature", "properties": { "VAR_1": 23,"VAR_2": "def","VAR_3": 876 }, "geometry" : [-74.0060, 40.7128]}
    ]}'

You can do this:

library(tidyverse)

jsonlite::fromJSON(x)$features |>
  as_tibble() |>
  select(properties, geometry) |>
  unnest(properties)

# Output:
# A tibble: 2 × 4
  VAR_1 VAR_2 VAR_3 geometry 
  <int> <chr> <int> <list>   
1    31 abc     255 <dbl [2]>
2    23 def     876 <dbl [2]>