I'm not convinced that this is a fair portrayal of what the proponent of CDT says. That's not to weigh in on whether they're right but I don't think they fail to be self-consistent in the way you have outlined.
The proponent of CDT doesn't assign non-zero odds to the predictor being imperfect, they just say that it doesn't matter if the predictor is perfect or not as, given that the boxes are already filled, it is too late to influence the thing which would lead you to get the $M (your agent type at t=0 rather than your decision at t=1).
The CDT agent will agree that the predictor is perfect but just deny that this is relevant because it doesn't change the fact that NP rewards people based on agent type (at t=0) and not decision, nor does it change the fact that the decision now can't causally influence the agent type at t=0.
Whether this is the right question to ask seems to me to be open to debate but I don't think that the proponent of CDT has an internal inconsistency in their consideration of whether the predictor is perfect.
they just say that it doesn't matter if the predictor is perfect or not as, given that the boxes are already filled, it is too late to influence the thing which would lead you to get the $M (your agent type at t=0 rather than your decision at t=1).
That's where they lose me. By definition of a perfect predictor, there is no option of "two-box and get $1000 and $1,000,000" in the problem setup, why would they even consider it?
With much help from crazy88, I'm still developing my Decision Theory FAQ. Here's the current section on Decision Theory and "Winning". I feel pretty uncertain about it, so I'm posting it here for feedback. (In the FAQ, CDT and EDT and TDT and Newcomblike problems have already been explained.)