Uncertainty Quantification - Regression

Given that uncertainty quantification is used often in many settings when confidence in predictions is required it would be nice to include a task in Flaml that tackles this setting.

There are a couple of questions that about how to do this.

1) Should we create a separate tasks or is it enough to give instructions on how to use the uncertainty estimates on models like Catboost.
2) If we create another task, is it necessary to implement other validation metrics like proper-scoring rules (e.g log-likelihood, CRPS, etc)?
3) Should we only focus on Catboost or would it be helpful to implement other methods for uncertainty quantification?