Dataset.resample() adds time dimension to independent variables

Code Sample, a copy-pastable example if possible

ds = ds.resample(time='1D',keep_attrs=True).mean()

Problem description

I'm downsampling in time a dataset which also contains timeless variables.
I've noticed that resample adds the time dimension to the timeless variables.
One workaround is:

1. Split the dataset in a timeless and a time-dependent dataset
2. Resample the time-dependent dataset
3. Merge the two datasets

This is not a big deal, but I was wondering if I'm missing some flag that avoids this behavior.
If not, is it something that can be easily implemented in resample?
It would be very useful for datasets with variables on staggered grids.

Output of xr.show_versions()

Start at the Dataset.resample() entry point and reproduce the provided example with both time-dependent and timeless variables. Trace how resampling handles independent variables; done means timeless variables retain no time dimension while time-dependent variables are resampled as before.