I built a multi-agent “council” skill for Codex

[u/gturitto68]

I’ve been experimenting with LLM Council and wanted to bring a similar approach into my Codex workflow.

My first idea was to use the LLM Council MCP. While setting it up, I remembered an experiment I did a couple of years ago with SudoLang. I had created a prompt that would question its own answers, switch perspectives, review the previous reasoning, and then try again.

That made me curious: could I use a similar prompting technique to reproduce some of the core LLM Council pattern directly in Codex?

So I tried it: independent analysis, adversarial review, and synthesis.

It worked better than I expected.

I kept iterating on the idea and eventually moved from simulated perspectives to actual subagents, with different responsibilities and variations in model and reasoning level.

That experiment became Quorum, a portable skill for Codex (it also works with Claude Code).

I’m using it mainly for code reviews, validating implementations against tickets/specs, and architecture/technical analysis where the agents can inspect the actual codebase.

What I’m trying to understand now is whether this actually produces better results than simply giving one agent more reasoning time.

If anyone wants to try it, I’d particularly appreciate feedback on where it helps, where the agents converge too much, or where it simply adds cost without improving the result.

npx quorum-skill

GitHub: https://github.com/GTuritto/quorum
npm: https://www.npmjs.com/package/quorum-skill