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  "path": "/t/how-do-you-handle-overlapping-codex-skills-in-larger-skill-catalogs/1383626#post_3",
  "publishedAt": "2026-06-13T23:18:01.000Z",
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  "textContent": "That is close, but I think the part I am trying to separate is the difference between **merging** skills and **routing** skills.\n\nIf I merge everything into one resolved skills document, I get one clean instruction set, but it becomes static pretty quickly. It also loses some of the modularity that makes skills useful in the first place.\n\nWhat I am experimenting with is more like a small decision layer that runs before the actual task starts:\n\n  1. Look at the current task.\n\n  2. Look at the currently available skills.\n\n  3. Group skills that are effectively competing for the same job.\n\n  4. Pick the smallest useful set for this specific request.\n\n  5. Only then load/read the selected skill instructions.\n\n\n\n\nSo for example, if the task is “fix a failing GitHub Actions check”, I probably do not want a broad GitHub workflow, a codebase recon workflow, a generic testing workflow, and a CI-specific workflow all pulling context in different directions. I would rather select the CI specialist and let that own the job.\n\nBut for a larger browser game task, the best answer might be one stack-specific implementation skill plus one playtest/debug loop skill.\n\nSo the problem is not only “how do I resolve conflicts once?” but more:\n\nHow should an agent choose the right subset of specialist instructions dynamically, depending on the task?\n\nThat is the pattern I am curious about. Maybe the better long-term answer is built-in skill priority/scoping metadata, but for now I have been testing it as an instruction-only meta-routing approach.",
  "title": "How do you handle overlapping Codex skills in larger skill catalogs?"
}