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Agent Skill · 研究检索

agent-orchestrator(Agent 协调器)

agent-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。

agent-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 44,750。

总安装 894周安装 38GitHub Stars 6下载 313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:agent-orchestrator(Agent 协调器)
来源仓库:https://github.com/mrclrchtr/skills
仓库路径:skills/agent-orchestrator
安装命令:
npx skills add https://github.com/mrclrchtr/skills --skill agent-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/mrclrchtr/skills --skill agent-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。

agent-orchestrator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息检索的研究与数据整理场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

建议确认权限范围、维护状态,以及是否会触发联网或文件读写操作。可结合来源仓库 README 进一步核验具体用法和功能边界。

来源仓库内路径:skills/agent-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/mrclrchtr/skills --skill agent-orchestrator;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

agent-orchestrator 怎么安装?

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

agent-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。

agent-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/mrclrchtr/skills --skill agent-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。

agent-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。

agent-orchestrator 用的人多吗?

公开数据是累计安装 894 次,近一周安装 38 次,下载 313 次,GitHub 6 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。

agent-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
agent-orchestrator

Agent 协调器 · 本页

8946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

Agent Orchestrator

Overview

Orchestrate multi-agent work end-to-end: delegate audits and fixes, reconcile results, enforce quality gates, and deliver a validated outcome.

Follow this core pattern: delegate a fresh implementer per cluster, then run a two-stage review (spec compliance first, then code quality).

Non-negotiable rule: never implement changes directly (no coding, no file edits).

Agent Roles

Assume these roles are available in your environment. Do not edit agent definitions or configs. If a required role is missing, stop and ask the operator to configure it.

  • architect (design/decisions/contracts)
  • auditor (read-only issue finding; no fixes)
  • explorer / scout (read-only repo lookup)
  • worker (general-purpose helper)
  • implementer (code + tests)
  • spec_reviewer (read-only, PASS/FAIL: nothing missing, nothing extra)
  • quality_reviewer (read-only, PASS/FAIL: maintainability + test quality)

Workflow

  1. Use skills when they directly match a subtask

- If a skill matches the task, invoke it explicitly and follow it (e.g., $web-fetch-to-markdown <url>). - When delegating, tell sub-agents which skill to use in their prompt (e.g., “Use $commit for the commit step.”).

  1. Freeze scope + success criteria

- Restate the mission, constraints, and “done” criteria in concrete terms. - Identify any authoritative sources (docs/specs) and record what claims must be backed by evidence.

  1. Create a phase plan and keep it current

- Use your environment’s planning mechanism (e.g., update_plan if available) to track phases and prevent drifting. - Prefer 4–7 steps; keep exactly one step in progress.

  1. Decompose into subsystems

- Choose subsystems that can be audited independently (API surface, core logic, error handling, perf, integrations, tests, docs). - For each subsystem, define 2–5 invariants (what must always be true).

  1. Run dual independent audits per subsystem

- Spawn two independent auditor agents per subsystem (auditA and auditB). - For high-risk or subtle work, narrow the subsystem scope and strengthen the invariants and evidence requirements before spawning them. - Tell them to work independently until reconciliation (no cross-talk). - Require evidence for every issue (repo location, deterministic repro, expected vs actual, severity).

  1. Reconcile audits into a single confirmed issue list

- Compare auditA vs auditB outputs and keep only mutually confirmed issues (or independently verify disputed ones with explorer). - Track rejected candidates with a brief reason (weak evidence, out of scope, non-deterministic). - Use this reconciled list as the only input to implementation. - Reconciliation output: - Confirmed issues (only mutual) - Rejected candidates (reason) - Consensus achieved: YES/NO

  1. Implement in clusters with clear ownership

- Group confirmed issues into clusters that can be fixed with minimal coupling. - Spawn exactly one implementer per cluster. - Assign each implementer a file set to “own” and require them to avoid broad refactors. - Do not implement any cluster work directly; always delegate to the implementer (even for “quick” changes). - Every fix must come with a regression test (unit/integration/e2e as appropriate). - For each cluster, run a two-stage review loop: - Have the implementer complete the cluster (tests, self-review) and report what changed. - spec_reviewer validates “nothing more, nothing less” by reading code (do not trust the report). - quality_reviewer validates maintainability and test quality (only after spec compliance passes). - If any review FAILs, send concrete feedback to the implementer and repeat the failed review stage.

  1. Enforce review gates

- Do not merge/land a cluster unless spec compliance PASS and code quality PASS are both recorded with concrete references.

  1. Integrate + validate

- Run the repo’s standard validations (tests, lint, build, typecheck). - If the repo has no clear commands, discover them from README, package.json, pyproject.toml, CI config, etc.

  1. Deliver a concise completion report

- State what is usable now. - State what remains intentionally unsupported (with next steps/issues). - List commands executed (at least key validation commands) and results.

What to send to sub-agents

Keep your messages task-specific and concise. Do not restate generic role behavior; focus on the task at hand.

For any audit/review/implementation message, include:

  • Goal + success criteria (what “done” means)
  • Scope boundaries / owned files (what to touch, what not to touch)
  • Invariants (2–5) that must hold
  • Commands to run (if known), and what evidence to collect

平台分布

Codex

37.35%
按下载量换算117

Claude

26.8%
按下载量换算84

Cursor

19.46%
按下载量换算61

Gemini CLI

8.77%
按下载量换算27

安全审计

Gen Agent Trust Hub

通过

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/mrclrchtr/skills --skill agent-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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