Directly representing things as a graph would likely reduce some of the 'translation overhead', done correctly.
I'm not so sure on the latter -- that introduces a bunch of tool calls, while the text patches are much closer to the semantic space imo and easy for harnesses
If we rephrase this as instruction following alignment, what is the concern here in practice vs a skill? (Which a model eventually internalizes)
It doesn't detract from the research - as a paper, it shows more crisply the structure is useful. I'm just not sure how necessary the encoding, and given durable tasks, novel the insight. Is there new alpha here somewhere, esp given the similarity?