goodness-of-fit indices for ML SEM

I have been asked by a reviewer to offer a better justification for the fit of my proposed ML model by "indicating the fit of the within and between model separately". After reading several chapters made for MPlus, I first looked to mxRefModels(). But, I am under the impression that it does NOT work with ML SEM. So, I tied to make the saturated and independence models for within and between myself for the various calculations. I was successful regarding the independence model but not the saturated model.

Through different combinations of the within and between parts of the independence, saturated and target/candidate model, I have noticed that all the attempts from mxTryHard() leads to "All fit attempts resulted in errors - check starting values or model specification" when I include the saturated within part with any of the above between parts. So, I am convinced the error is connected to the within part... either my code or something else.

I would be happy to include my code for your review... but basically I am trying to do what Rappaport colleagues (https://pubmed.ncbi.nlm.nih.gov/32774078/) have claimed to have already done in a 2019 paper. This is documented in their Supplementary OpenMx RCode: https://osf.io/v4mej/ [MSEMfitFunctionAppendix.R]. There are a few minor easy-to-spot syntax errors in the code as well as some (what I think are) very clear missteps in referencing (?current?) OpenMx Objects. With no other options, I will continue to try and rewrite a bunch of this RCode to "make it work". But, does anyone have a functioning version of this code or a substitute? How else might I conduct fit tests of the within and between part separately?

Thx in advance...