A lot of the cases I've found Fable useful for is verifying complicated answers / designs / claims around complex interconnected systems. e.g. "I maintain X which teams A, B, and C use for product Y and code review highlighted these risks / imperfections in the code. Are these valid concerns based on how B and C plug into Y assuming ...?" followed by lots of followup questions.

Also "code review" above is often others' LLM skills reviewing the code and often flagging based on total falsehoods. I've taken to running a `/code-review` skill myself to preempt these claims (since findings by the same model tend to be pretty deterministic in my experience, even the ones that end up being wrong), usually at Opus 5.5, to preempt others' slop, and then end up arguing 90% of the points to confirm it wasn't accurate based on our usage of the system.

This is all horribly inefficient, and many aspects of our codebases across the monorepo have proliferated into spaghetti code by LLM-accelerated developers, but Fable often helps with analyzing the harder questions and saves me time on occasion arguing with (my or others') Opus findings, which are often still inaccurate for a sufficiently large interconnected system.

edit: I honestly don't know what percentile of "complexity" our typical usage is where I work, but I suspect it's a bit higher than the average. Monorepos, or at least companies with codebase sizes and demand to justify using them, probably make it worse. Opus has worked well enough for me on my personal projects, even some of the ones that have grown decently in size and complexity. I suspect part of this is an LLM extension of the old "my code makes sense, everybody else's doesn't" trend that necessitated stronger style guides in the past