> simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability

N of only a few of us working on an analytics agent, I don't think we've been finding this to be the case. We've been impressed with just how good LLMs (even smaller open weight models) are at using Python and R for visualization. Often any shortcomings go away if we iterate a bit to about ambiguity. Are there any threads of research that could better support this claim or highlight where issues might be?

A simpler spec can be used by a simpler agent. So, maybe that's the use-case here... use by smaller/cheaper agents that run in parallel as opposed to large models running one visualization at a time.

Or at least, maybe that's the idea?

IME, Claude and ChatGPT do just fine generating ggplot models, but extensive customization can get a bit hairy.

we are considering also reliability, interactivity besides expressiveness. Simpler spec with good expressiveness comes handy when you want the agent to be reliably for non-expert users and with small models.