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Yeah, through trial and error I found that Codex (now gpt-5.4) has really good feedback once there's a plan file. Kinda like someone on the internet who suddenly becomes an expert once you make concrete claims for them to shred into. I have an AGENTS.md prompt that specifies how to review a plan. Something like: for every finding, rank the top solutions internally and then recommend a solution. And if there's a simpl…
Nice. I have a similar loop (Opus 4.6 plan Codex xhigh review) that I kind of run in an iterative feedback loop until meaningful actionables converge down to zero. I initially gave some thought to automating this because CC/Codex do have SDKs... but every once in a while Codex will propose some absurdly over-engineered stack advice that I have to manually reject before passing it back to Claude.
Yeah, I also thought about automating it before. Especially when I'm middlemanning noncritical plans where I don't care what the solution is.
I did make a skill /ask-codex that gets Claude to call Codex for one round of feedback which is pretty useful.
But for critical plans, I suppose being the middleman gives me a good opportunity to learn about the solution and its trade-offs as it's being incrementally refined. Especially in a domain I don't know much about.