This is how I do it too. I run three levels:
* Orchestrator: Opus 5.5
* Feature lead: GPT 6.1 Sol
* Worker: Muse Spark 1.3 Contributor
As long as you have an appropriate project and sandbox for Muse Spark it's the real secret sauce for my setup and it's dirt cheap on OpenCode Go.GPT 6.1 Sol is surprisingly efficient too, I've been impressed with it.
My orchestration skill setup is https://github.com/beefsack/processed-beef/
And which agent checks the work that the Worker does? If it's garbage then isn't that just extra tokens consumed by the Orchestrator or Feature lead?
I'd be interested to know what the difference in cost is in this setup on building a complex feature vs using Opus directly.
Just one thing
Does anyone have any evidence that having the most powerful model being the orchestrator, and other sub agents being progressively less powerful, is optimal? Is this just common sense or it has been measured somehow?
For me it could be that this scheme may make the code itself poorly written, verbose or faulty