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Agent Skill · 研究检索

codex-orchestration(Codex orchestration 搜索)

codex-orchestration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

codex-orchestration 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 73,230。

总安装 118周安装 5GitHub Stars 177下载 41核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:codex-orchestration(Codex orchestration 搜索)
来源仓库:https://github.com/moltbot/skills
仓库路径:skills/codex-orchestration
安装命令:
npx skills add moltbot/skills --skill "codex-orchestration"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add moltbot/skills --skill "codex-orchestration"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

Codex 的通用编排。使用 update_plan 加上后台 PTY 终端来运行并行 Codex exec 工作程序。

来源仓库内路径:skills/codex-orchestration

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add moltbot/skills --skill "codex-orchestration";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

codex-orchestration 怎么安装?

在终端执行 npx skills add moltbot/skills --skill "codex-orchestration"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codex-orchestration 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

codex-orchestration 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add moltbot/skills --skill "codex-orchestration" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

codex-orchestration 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

codex-orchestration 用的人多吗?

公开数据是累计安装 118 次,近一周安装 5 次,下载 41 次,GitHub 177 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

codex-orchestration 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
codex-orchestration

Codex orchestration 搜索 · 本页

118177执行命令MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
codex-orchestration
description
General-purpose orchestration for Codex. Uses update_plan plus background PTY terminals to run parallel codex exec workers.

Codex orchestration

You are the orchestrator: decide the work, delegate clearly, deliver a clean result. Workers do the legwork; you own judgement.

This guide is steering, not bureaucracy. Use common sense. If something is simple, just do it.

Default assumptions

  • YOLO config (no approvals); web search enabled.
  • PTY execution available via exec_command and write_stdin.
  • Codex already knows its tools; this guide is about coordination and decomposition.

Two modes

Orchestrator mode (default)

  • Split work into sensible tracks.
  • Use parallel workers when it helps.
  • Keep the main thread for synthesis, decisions, and final output.

Worker mode (only when explicitly invoked)

A worker prompt begins with CONTEXT: WORKER.

  • Do only the assigned task.
  • Do not spawn other workers.
  • Report back crisply with evidence.

Planning with update_plan

Use update_plan when any of these apply:

  • More than 2 steps.
  • Parallel work would help.
  • The situation is unclear, messy, or high stakes.

Keep it light:

  • 3 to 6 steps max.
  • Short steps, one sentence each.
  • Exactly one step in_progress.
  • Update the plan when you complete a step or change direction.
  • Skip the plan entirely for trivial tasks.

Parallelism: "sub-agents" as background codex exec sessions

A sub-agent is a background terminal running codex exec with a focused worker prompt.

Use parallel workers for:

  • Scouting and mapping (where things are, current state)
  • Independent reviews (different lenses on the same artefact)
  • Web research (sources, definitions, comparisons)
  • Long-running checks (tests, builds, analyses, data pipelines)
  • Drafting alternatives (outlines, rewrites, options)

Avoid parallel workers that edit the same artefact. Default rule: many readers, one writer.

Background PTY terminals (exec_command + write_stdin)

Use PTY sessions to run work without blocking the main thread.

  • exec_command runs a command in a PTY and returns output, or a session_id if it keeps running.
  • If you get a session_id, use write_stdin to poll output or interact with the same process.

Practical habits:

  • Start long tasks with small yield_time_ms so you do not stall.
  • Keep max_output_tokens modest, then poll again.
  • Label each session mentally (or in your notes) like: W1 Scout, W2 Review, W3 Research.
  • Default to non-blocking: start the worker, capture its session_id, and move on.
  • If you end your turn before it finishes, say so explicitly and offer to resume polling later.
  • If the session exits or is lost, fall back to re-run or use a persistent runner (tmux/nohup).
  • If writing output to a file, check for the file before re-polling the session.

Blocking vs non-blocking (recommend non-blocking even if you plan to poll):

  • Default to non-blocking; poll once or twice if you need quick feedback.
  • Blocking is fine only for short, predictable tasks (<30–60s).

Stopping jobs:

  • Prefer graceful shutdown when possible.
  • If needed, send Ctrl+C via write_stdin.

Capturing worker output (keep context small)

Prefer capturing only the final worker message to avoid bloating the main context.

Recommended (simple):

  • Use --output-last-message to write the final response to a file, then read it.
  • Example: codex exec --skip-git-repo-check --output-last-message /tmp/w1.txt "CONTEXT: WORKER ..."
  • If you are outside a git repo, add --skip-git-repo-check.

Alternative (structured):

  • Use --json and filter for the final agent message.
  • Example: codex exec --json "CONTEXT: WORKER ..." | jq -r 'select(.type=="item.completed" and .item.type=="agent_message") | .item.text'

Orchestration patterns (general-purpose)

Pick a pattern, then run it. Do not over-engineer.

Pattern A: Triangulated review (fan-out, read-only)

Use when: you want multiple perspectives on the same thing.

Run 2 to 4 reviewers with different lenses, then merge.

Example lenses (choose what fits):

  • Clarity/structure
  • Correctness/completeness
  • Risks/failure modes
  • Consistency/style
  • Evidence quality
  • Practicality
  • Accessibility/audience fit
  • If relevant: security, performance, backward compatibility

Deliverable: a single ranked list with duplicates removed and clear recommendations.

Pattern B: Review -> fix (serial chain)

Use when: you want a clean funnel. 1) Reviewer produces an issue list ranked by impact. 2) Implementer addresses the top items. 3) Verifier checks the result.

This works for code, documents, and analyses.

Pattern C: Scout -> act -> verify (classic)

Use when: lack of context is the biggest risk. 1) Scout gathers the minimum context. 2) Orchestrator condenses it and chooses the approach. 3) Implementer executes. 4) Verifier sanity-checks.

Pattern D: Split by sections (fan-out, then merge)

Use when: work divides cleanly (sections, modules, datasets, figures). Each worker owns a distinct slice; merge for consistency.

Pattern E: Research -> synthesis -> next actions

Use when: the task is primarily web search and judgement. Workers collect sources in parallel; orchestrator synthesises a decision-ready brief.

Pattern F: Options sprint (generate 2 to 3 good alternatives)

Use when: you are choosing direction (outline, methods plan, analysis, UI). Workers propose options; orchestrator selects and refines one.

Context: supply what workers cannot infer

Most failures come from missing context, not missing formatting instructions.

Use a Context Pack when:

  • the work touches an existing project with history,
  • the goal is subtle,
  • constraints are non-obvious,
  • or preferences matter.

Skip it when:

  • the task is a simple web lookup,
  • a small isolated edit,
  • or a straightforward one-off.

Context Pack (use as much or as little as needed)

  • Goal: what "good" looks like.
  • Non-goals: what not to do.
  • Constraints: style, scope boundaries, must keep, must not change.
  • Pointers: key files, folders, documents, notes, links.
  • Prior decisions: why things are the way they are.
  • Success check: how we know it is done (tests, criteria, checklist).

Academic writing note:

  • For manuscripts or scholarly text, use APA 7 where appropriate.

Worker prompt templates (neutral)

Prepend the Worker preamble to every worker prompt.

Worker preamble (use for all workers)

CONTEXT: WORKER
ROLE: You are a sub-agent run by the ORCHESTRATOR. Do only the assigned task.
RULES: No extra scope, no other workers.
Your final output will be provided back to the ORCHESTRATOR.

Minimal worker command (example):

codex exec --skip-git-repo-check --output-last-message /tmp/w1.txt "CONTEXT: WORKER
ROLE: You are a sub-agent run by the ORCHESTRATOR. Do only the assigned task.
RULES: No extra scope, no other workers.
Your final output will be provided back to the ORCHESTRATOR.
TASK: <what to do>
SCOPE: read-only"

Reviewer worker

CONTEXT: WORKER TASK: Review <artefact> and produce improvements. SCOPE: read-only LENS: <pick one or two lenses> DO:

  • Inspect the artefact and note issues and opportunities.
  • Prioritise what matters most.

OUTPUT:

  • Top findings (ranked, brief)
  • Evidence (where you saw it)
  • Recommended fixes (concise, actionable)
  • Optional: quick rewrite or outline snippet

DO NOT:

  • Expand scope
  • Make edits

Research worker (web search)

CONTEXT: WORKER TASK: Find and summarise reliable information on <topic>. SCOPE: read-only DO:

  • Use web search.
  • Prefer primary sources, official docs, and high-quality references.

OUTPUT:

  • 5 to 10 bullet synthesis
  • Key sources (with short notes on why they matter)
  • Uncertainty or disagreements between sources

DO NOT:

  • Speculate beyond evidence

Implementer worker (build, write, analyse, edit)

CONTEXT: WORKER TASK: Produce <deliverable>. SCOPE: may edit <specific files/sections> or "write new artefact" DO:

  • Follow the Context Pack if provided.
  • Make changes proportionate to the request.

OUTPUT:

  • What you changed or produced
  • Where it lives (paths, filenames)
  • How to reproduce (commands, steps) if relevant
  • Risks or follow-ups (brief)

DO NOT:

  • Drift into unrelated improvements

Verifier worker

CONTEXT: WORKER TASK: Verify the deliverable meets the Goal and Success check. SCOPE: read-only (unless explicitly allowed) DO:

  • Run checks (tests, builds, analyses, reference checks) if relevant.
  • Look for obvious omissions and regressions.

OUTPUT:

  • Pass/fail summary
  • Issues with repro steps or concrete examples
  • Suggested fixes (brief)

Orchestrator habits (fast, not fussy)

  • Skim the artefact yourself before delegating.
  • Ask a quick clarification if a term or goal is ambiguous.
  • Use parallel workers when it reduces time or uncertainty.
  • Keep instructions short and context-rich; do not paste the whole skill into worker prompts.
  • If a worker misunderstood, do not argue. Re-run with better context.
  • Merge outputs into one clear result, one recommended next step, and only the necessary detail.

Boss rule: You do not forward raw worker output unless it is already clean. You curate it.

平台分布

openclaw

39.33%
按下载量换算16

Codex

28.82%
按下载量换算12

Claude Code

18.05%
按下载量换算7

Gemini CLI

8.43%
按下载量换算3

安全审计

暂无安全审计结果可展示。

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add moltbot/skills --skill "codex-orchestration" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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