Randomizatio inference (beyond "permute")

Hi,

I was wondering if there are any tools for randomization inference / Fisher permutation tests, that go beyond what can be achieved by the permute command. I wrote something myself a while back and was wondering whether it's worth making that into a package and putting it up somewhere.

Simple --- and probably common --- example of an analysis, which can't be done using permute: (Please correct me if I'm wrong, then my post is pointless)
An an RCT classes within school are randomly assigned to treatment. Either the whole class or no one in a class gets treatment, but treatment is stratified by schools so that within each school the same number of classes are in treatment and control group respectively. Now it is desired to use simple permutation techniques to assess whether the difference in test scores between treated and non-treated students is significant (possibly controlling for some student-level covariates). The treatment permutation would've to account for the clustered treatment assignment, as well as the strata.

Best,

Simon