I think I can answer 3: if you want to include correlations in your prior, then you need to create a covariance matrix, which will contain the information about correlations between variables (covariance is a measure of how the variables vary together). Then you need to load that covariance matrix into a multivariate distribution, which in your case will be:
cfs = pm.MvNormal("cfs", mu=[100, 100, 100], cov=your_covariance_matrix, shape=3)