To summarize: The scheduler should assign tasks the the agent first, which gives a queue the highest priority.

The issue here you assume both are idle and you need global priority based on resource preference. I understand your scenario now, but it will only hold if enqueuing order is "optimal". For example, if machine Y is running a Task B that is about to be completed (e.g. in a minute) then still machine X will pick the new Task B, and again we end up in the scenario where Task A is waiting and machine Y is idle.
The solution you are looking for is global dynamic resource scheduling and moving jobs between resources, this is a very complicated task 🙂 and actually out of scope for ClearML that said, you can check SLURM, which is the best HPC scheduling solution I'm aware of, and even there it will be hard to create a policy for such a scenario. The good news clearml integrates with slurm, so you could have slurm run the scheduling and clearml as the "external interface". I have to warn in advance, managing a SLURM cluster is challenging.