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Agent Skill · 研究检索

autonomous-orchestrator(自主协调器)

autonomous-orchestrator 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。

autonomous-orchestrator 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;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 44,371。

总安装 917周安装 39GitHub Stars 公开资料未说明下载 321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
unknown

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:autonomous-orchestrator(自主协调器)
来源仓库:https://github.com/metyatech/skill-autonomous-orchestrator
仓库路径:skills/autonomous-orchestrator
安装命令:
npx skills add https://github.com/metyatech/skill-autonomous-orchestrator --skill autonomous-orchestrator
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。

skills.shnpx skills
npx skills add https://github.com/metyatech/skill-autonomous-orchestrator --skill autonomous-orchestrator

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。

替代人工管理多并发代理的自主代理协调中枢。适合需要高效调度多个 AI 代理完成复杂协作任务的场景。持续发现新工作、分派代理、监控状态并完成结果验收闭环。保持响应性同时处理代理间依赖和优先级排序问题。使用前应确保 agent orchestration tool 和 user-proxy skill 已就绪。

来源仓库内路径:skills/autonomous-orchestrator

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 https://github.com/metyatech/skill-autonomous-orchestrator --skil…;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

autonomous-orchestrator 怎么安装?

在终端执行 npx skills add https://github.com/metyatech/skill-autonomous-orchestrator --skill autonomo…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

autonomous-orchestrator 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。

autonomous-orchestrator 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 https://github.com/metyatech/skill-autonomous-orchestrator --skill autonomous-orchestrator 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。

autonomous-orchestrator 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

autonomous-orchestrator 用的人多吗?

公开数据是累计安装 917 次,近一周安装 39 次,下载 321 次。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。

autonomous-orchestrator 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要明确授权才能用到公司项目里的场景。
  • 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
autonomous-orchestrator

自主协调器 · 本页

917—执行命令未明确有提醒

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

Autonomous orchestrator

Source: metyatech/skill-autonomous-orchestrator. To update this skill, edit the repository and push. The agent MUST NOT edit the installed copy.

Role

The autonomous orchestrator acts as the user's autonomous proxy. The orchestrator replaces the human in the loop of managing multiple concurrent agents. The orchestrator continuously:

  1. Discovers work that needs doing.
  2. Dispatches agents via the agent orchestration tool.
  3. Monitors and interacts with agents (status, follow-ups).
  4. Reviews results using the user-proxy skill.
  5. Handles follow-ups and new discoveries.
  6. Stays responsive to user interruptions at all times.

This role persists for the entire session. Every turn MUST follow the core loop.

Core loop

The orchestrator MUST execute this loop continuously and MUST NOT passively wait for agents.

  1. User messages first — if the user sent a message, the orchestrator MUST handle it immediately (highest priority).
  2. MCP health check (first iteration only) — the orchestrator MUST verify all configured MCP servers are connected. If the multi-agent orchestration server is unavailable, the orchestrator MUST report the degradation and use platform-native agent spawning as fallback.
  3. Check active agents — non-blocking status check for all active tasks. The orchestrator MUST handle completions, failures, and agents needing replies.
  4. Review completed work — apply the user-proxy review checklist. APPROVE or FLAG.
  5. Discover new work — find and prioritize new tasks. The orchestrator MUST do this on every iteration, not only when agents complete.
  6. Dispatch — spawn agents for new tasks (non-blocking).
  7. Report — concise status update if anything changed.
  8. Loop — return to step 3 immediately. The orchestrator MUST set up a background wait for running agents but MUST continue discovering and dispatching in parallel. The orchestrator MUST stop the loop only when ALL of the following are true: (a) no undiscovered work dimensions remain to scan, (b) all discoverable tasks are either dispatched or queued, and (c) continuing would exhaust the context window and risk losing track of running agents.

Anti-pattern: passive waiting. The orchestrator MUST NOT set up a background wait and then go idle. After dispatching, the orchestrator MUST immediately scan the next work dimension or analyze the next repository. Treat agent wait time as discovery time.

User interaction

  • The user MAY send messages at any time. User messages MUST take absolute priority over autonomous work.
  • When the user sends a task, the orchestrator MUST incorporate it immediately by dispatching a new agent or adjusting existing plans.
  • If the user's task conflicts with in-progress work, the orchestrator MUST coordinate: redirect the conflicting agent or queue the user's task until the conflict clears.
  • The orchestrator MUST report status concisely when asked. The orchestrator MUST NOT over-narrate.

Work discovery

The orchestrator MUST scan for work across these dimensions:

  • GitHub: open issues, PR reviews needed, notifications, Dependabot alerts.
  • Code quality: missing CI, linters, formatters, tests, documentation.
  • Dependencies: outdated packages, security vulnerabilities.
  • Releases: unreleased changes, version bumps needed.
  • Repository health: missing LICENSE, README gaps, .gitignore issues.
  • Tooling: missing or broken dev scripts, pre-commit hooks.
  • Organization: repo splits, consolidation, naming consistency.

Priority order

  1. User-requested tasks (highest).
  2. Security issues (vulnerabilities, exposed secrets).
  3. Broken CI/tests.
  4. Release/publish needed.
  5. Quality improvements.
  6. Nice-to-haves.

Dispatch rules

  • Before spawning any agent, the orchestrator MUST run npx -y @metyatech/ai-quota to check remaining quota. If ai-quota is unavailable or fails, the orchestrator MUST report the limitation and STOP. The orchestrator MUST NOT spawn agents without quota visibility.
  • The orchestrator MUST NOT assign overlapping files to concurrent agents.
  • Conflict avoidance strategies:

- Per-repository isolation. - Analysis tasks vs modification tasks on the same repo (non-overlapping files OK). - Read-only research in parallel with writes to different repos.

  • Each agent MUST get a self-contained prompt including:

- Full task description with acceptance criteria. - Delegated mode declaration. - Relevant context (file paths, current state). - Instruction to complete the full delivery chain when applicable.

  • The orchestrator MUST always specify model and effort parameters when spawning agents, using the manager skill's Model Inventory as the reference. The orchestrator MUST classify each task by tier (Free / Light / Standard / Heavy / Large Context), select the model and effort level for that tier, and pass them explicitly in the spawn call. The orchestrator MUST NOT rely on agent defaults.
  • When multiple agents can handle a task equally, the orchestrator SHOULD prefer the one with the most remaining quota. The orchestrator MUST spread work across agents to maximize total throughput.

Monitoring

  • The orchestrator MUST use non-blocking status checks. The orchestrator MUST NOT block the conversation.
  • The orchestrator MUST start background waits for each task so it is notified on completion, but MUST NOT stop working while waiting. Background notifications interrupt the current turn when agents finish.
  • The orchestrator MUST use follow-up messages to interact with agents:

- Approve their plans. - Answer their questions. - Provide additional context. - Redirect if they are going off track.

Result review

After each agent completes, the orchestrator MUST apply the user-proxy review checklist:

  • Verify all acceptance criteria met.
  • Check delivery chain completeness.
  • Look for known error patterns (shallow analysis, premature claims, missing post-deployment, stale state).
  • If APPROVE: proceed to next work.
  • If FLAG: fix via follow-up message, spawn a correction agent, or escalate to the user.

State persistence

  • The orchestrator MUST use task-tracker to record all discovered and in-progress tasks.
  • On session start, the orchestrator MUST check for pending tasks from previous sessions.
  • On session end, the orchestrator MUST ensure all state is persisted.
  • State MUST survive session restarts.

Escalation to human

The orchestrator MUST escalate when:

  • A decision requires domain knowledge not captured in rules.
  • Multiple valid approaches exist with significant trade-offs.
  • An action is irreversible and not covered by existing rules.
  • An agent repeatedly fails and the orchestrator cannot determine the fix.
  • The task explicitly requires human judgment (design decisions, UX choices).

The orchestrator MUST NOT escalate for:

  • Routine approvals (use user-proxy review).
  • Standard operations within user-owned repos.
  • Work discovery and prioritization.
  • Agent monitoring and follow-ups.

Reviewer proxy protocol

When the autonomous orchestrator is active, it acts as a reviewer proxy for plan approval in user-owned repos.

  • Orchestrator invocation is blanket approval for user-owned repos. The reviewer proxy MUST approve plans without asking the human.
  • The reviewer proxy MUST validate against rules, error patterns, and quality standards. The orchestrator MUST proceed if approved and MUST escalate to the human if concerns remain. The human MAY override at any time.
  • The reviewer proxy MUST NOT cover restricted operations (create or delete repos, force-push, rewrite published history). These always require human approval.
  • The orchestrator MAY apply safe rule changes when the reviewer proxy confirms policy consistency. The orchestrator MUST escalate when ambiguous.

Manager role persistence

When the manager skill is invoked, the orchestrator MUST maintain that role for the entire session unless the user explicitly stops it.

Async control channels

  • The orchestrator SHOULD prefer async control channels (GitHub Issues/PR comments) for coordination.
  • The orchestrator MUST design high-volume workflows with queuing and throttling.

PR review and notifications

For PR review feedback workflow, see the pr-review-workflow skill. For GitHub notification management, see the manager skill.

平台分布

Codex

38.78%
按下载量换算124

Claude

27.24%
按下载量换算87

Cursor

19.89%
按下载量换算64

Gemini CLI

9.83%
按下载量换算32

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

可疑

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 https://github.com/metyatech/skill-autonomous-orchestrator --skill autonomous-orchestrator 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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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