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在 OpenClaw 中安装
/install collaborative-agent
功能描述
ARC多智能体协作:规划/执行/审查/总结/研究/批评,迭代评审
使用说明 (SKILL.md)
Skill: collaborative-agent
ARC 式多智能体协作框架
归属管理
- 归属核心:
think-expand(想核心) - 上级负责:复杂决策任务由think-expand分解后委托协作框架执行
功能范围
- 多角色协作:规划者/执行者/审查者/总结者/研究者/批评者
- 迭代式同行评审:产出→评审→反馈→优化
- 任务分解:复杂任务自动拆分为子任务
- 依赖管理:子任务按依赖顺序执行
- 结果综合:多步结果整合为结构化报告
原理
源自 ARC (AutoResearchClaw 2026) 研究:
- 多智能体同行评审协作
- 自我强化循环
- 集成已有能力:ScriptDB / VSAEngine / SkillEvolver / CognitiveReasoner
用法
import sys; sys.path.insert(0, r'D:\coze-local\db')
from collaborative_agent import ARCWorkflow, AgentRole
# 创建协作工作流
wf = ARCWorkflow()
# 添加任务(自动分配角色)
wf.add_task("研究Transformer优化方案", role="researcher")
wf.add_task("制定实现计划", role="planner", depends_on=[0])
wf.add_task("实现并测试", role="executor", depends_on=[1])
wf.add_task("审查代码质量", role="reviewer", depends_on=[2])
wf.add_task("生成总结报告", role="summarizer", depends_on=[3])
# 执行所有任务
results = wf.run_all()
# 获取最终报告
report = wf.get_report()
触发场景
- 复杂问题需要分步骤处理(规划→执行→审查→总结)
- 需要多角度分析的研究任务
- 需要质量审查的代码/内容生成
- 需要从多来源综合信息的任务
集成
- 内部自动调用
capability_executor.detect_and_execute()执行已注册能力 - 使用
CognitiveReasoner提供语言/数值反馈 - 使用
SkillEvolver记录失败并进化
Base directory: file:///C:/Users/pc/.config/opencode/skills/collaborative-agent \r \r
B站学习\r
学习时间: 2026-06-01 20:57\r \r
- 安逸Ai丶: Agent中为什么需要 tracing 和 observability?\r
- 关键词: Agent中为什么需要, tracing, observability\r
- 银色海豚KK: OpenClaw v2026.5.28 更新快报 | ClawPDF Claude Opus 4.8 Agent协作\r
- 关键词: OpenClaw, v2026, 28, 更新快报, ClawPDF\r \r
B站学习\r
学习时间: 2026-06-01 21:01\r \r
- 安逸Ai丶: Agent中为什么需要 tracing 和 observability?\r
- 银色海豚KK: OpenClaw v2026.5.28 更新快报 | ClawPDF Claude Opus 4.8 Agent协作\r
- 智能体老王: AI给自己写工具?字节团队出品 MUSE-Autoskill 让Agent实现技能自进化,推动skills成为可复用的知识资产\r \r
融合来源: collaborative-agent-1fe479\r
融合时间: 自动合并\r \r 学习时间: 2026-06-01 21:07\r
- WJ_UPC: 20221216_王钧_Advances in Collaborative Neurodynamic Optimization\r
- 树欲静心不止: 250908- Coding Agent实战心得:从工具到伙伴的协作之道 / Coding Agent Mastery: Collaborative Devel\r
- UncleScto: 3D LMI Gocator with HANWHA collaborative robot\r
融合时间: 自动合并\r 学习时间: 2026-06-02 07:52\r
- dailyrain: 3GC Collaborative and Creative Content Generation in Game Design\r
- dailyrain: 3GC Collaborative and Creative Content Generation in Game Design\r
- Tracy春雪: The Teachers' Room - Collaborative Writing 1 - Planning\r \r
B站学习 (第1轮)\r
学习时间: 2026-06-02 09:20\r \r
- 安逸Ai丶: Agent中为什么需要 tracing 和 observability?\r https://www.bilibili.com/video/BV1BwVd6xEd8\r
- AIlazy俊: 66K 星的 Caveman:让 Agent 少废话,还能省 tokens\r https://www.bilibili.com/video/BV1hdV96rEiV\r
- 智能体老王: AI给自己写工具?字节团队出品 MUSE-Autoskill 让Agent实现技能自进化,推动skills成为可复用的知识资产\r https://www.bilibili.com/video/BV1QPVf6QEF1\r \r
B站学习 (第2轮)\r
学习时间: 2026-06-02 09:33\r \r
- 安逸Ai丶: Agent中为什么需要 tracing 和 observability?\r https://www.bilibili.com/video/BV1BwVd6xEd8\r
- AIlazy俊: 66K 星的 Caveman:让 Agent 少废话,还能省 tokens\r https://www.bilibili.com/video/BV1hdV96rEiV\r
- 智能体老王: AI给自己写工具?字节团队出品 MUSE-Autoskill 让Agent实现技能自进化,推动skills成为可复用的知识资产\r https://www.bilibili.com/video/BV1QPVf6QEF1\r
安全使用建议
Review this skill before installing if your environment has powerful registered capabilities, private data stores, or tools that can modify files, accounts, services, or installed skills. Prefer using it only where capability execution requires explicit approval and where SkillEvolver logging or behavior changes are understood and controllable.
能力评估
Purpose & Capability
The stated purpose is multi-role planning, execution, review, research, and summarization, which fits the described workflow; however, automatically executing registered capabilities can become high-impact depending on what capabilities are available.
Instruction Scope
Trigger conditions cover broad complex, research, code/content generation, and synthesis tasks, and the integration notes say it internally calls `capability_executor.detect_and_execute()` without defining limits, dry-run behavior, approval checkpoints, or sensitive-task exclusions.
Install Mechanism
The package contains only a markdown skill file, no executable scripts, dependency declarations, installer, or bundled binary artifacts.
Credentials
The example imports code from a local Windows path and references local components such as ScriptDB, VSAEngine, SkillEvolver, and CognitiveReasoner; these are purpose-related but their permissions and data access are not described in the artifact.
Persistence & Privilege
The skill says it uses `SkillEvolver` to record failures and evolve, implying persistent behavior changes or logging, but it does not explain where data is stored, how users can inspect it, or how to disable or reverse it.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install collaborative-agent - 安装完成后,直接呼叫该 Skill 的名称或使用
/collaborative-agent触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
collaborative-agent v1.0.0
- Initial release of an ARC-style multi-agent collaboration framework.
- Supports multi-role collaboration: planner, executor, reviewer, summarizer, researcher, critic.
- Features iterative peer review, automatic task decomposition, and dependency-based execution.
- Integrates existing capabilities: ScriptDB, VSAEngine, SkillEvolver, CognitiveReasoner.
- Provides structured and modular workflow for complex decision-making and multi-perspective research tasks.
元数据
常见问题
Collaborative Agent 是什么?
ARC多智能体协作:规划/执行/审查/总结/研究/批评,迭代评审. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 45 次。
如何安装 Collaborative Agent?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install collaborative-agent」即可一键安装,无需额外配置。
Collaborative Agent 是免费的吗?
是的,Collaborative Agent 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Collaborative Agent 支持哪些平台?
Collaborative Agent 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Collaborative Agent?
由 534422530(@534422530)开发并维护,当前版本 v1.0.0。
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