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codex-dispatch
Use when routing well-specified implementation work from Fable to Codex or another side worker.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Use when routing well-specified implementation work from Fable to Codex or another side worker.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
Use when preparing a repository, project kit, plugin, skillpack, or developer tool for public release or maintainer-ready public operations.
Use when improving a public README, repository homepage, docs landing page, or developer-facing first impression.
Use before delegating work from a Fable or premium-model orchestration session.
Use when choosing between cheap probes, worker runs, expensive ruler runs, or long keepalive waits.
| name | codex-dispatch |
| description | Use when routing well-specified implementation work from Fable to Codex or another side worker. |
Premium tokens buy judgment. Codex or side-worker capacity buys implementation volume when the task is well specified.
Include:
Some lanes are reachable through a CLI rather than a workflow model parameter. When a background shell launches a side worker, close stdin explicitly if the tool expects EOF. For Codex CLI, use:
codex exec --cd <worktree> "<prompt>" < /dev/null
Without the redirected stdin, some background shells can leave the worker waiting at startup instead of doing work.
Side workers do not automatically see every local Claude skill. Port skills on demand when a dispatch needs them; do not mirror an entire skill library by default.
Example:
ln -sfn "$HOME/.claude/skills/<skill>" "$HOME/.codex/skills/<skill>"
Name the required skill in the dispatch packet and keep the accepted output bounded. If the side worker lacks a required skill and the work is not self-contained, keep the task with Fable or a local lane.
If the diff or report is large, ask a fast worker for a bounded digest first. Fable reads the digest and flagged hunks, not the whole raw output.
This dispatch pattern is inspired in part by blader/arbitrage, which focuses on premium-model judgment plus Codex implementation. Claude Code users who want a slash-command bridge to Codex review and delegation workflows can also look at openai/codex-plugin-cc.
FTSO's own guidance remains tool-agnostic: write the spec first, dispatch only bounded work, review the output before accepting it, keep turns dense while lanes run, and name the proof boundary.