Just chiming in with a couple suggestions:
You should do some prior predictive checks to help decide the scale of these priors if you don’t have a good intuition off the bat. For example, I’ve seen even normal(0,1) criticized as too broad and implying rather unrealistic data in some circumstances.
Note also that your model presently does not attempt inference on potential correlations in the manifestation of effects across subjects. If you want to see what it would look like to add inference on the correlations too, a lecture is here that walks through a dataset like yours and models it hierarchically. Don’t worry that you only have one observation per participant per within-subject condition; for binomial outcomes, it’s fine to model things hierarchically in that circumstance.