multi-agent-orchestration

仓库创建 2026年5月22日最近提交 17 小时前SkillHot 收录 4 小时前
▸ 精选理由

面向构建复杂 agent 协同与人类回环的实战架构

这个 Skill 做什么

为多智能体系统提供设计、编排与有状态图工作流的生产级指南

提供多智能体系统和编排的生产级方案:覆盖 LangGraph、CrewAI、AutoGen 等图状有状态工作流、智能体集群、共享记忆和人机在环的护栏设计。用在要搭多 agent 协同、设计路由/监督模式或做可解释可回溯的工作流时。特点是把分布式代理的复杂性工程化,方便监控和故障恢复。

▸ 展开 SKILL.md 英文原文

Expert guide for designing and orchestrating multi-agent systems, agent swarms, graph-based workflows (LangGraph, CrewAI, AutoGen), shared state memory, and human-in-the-loop guardrails in English and Indonesian.

自动化集成多 Agent工作流LangGraph通用
41
Stars
7
Forks
40
仓库内 Skill
+0
7 日增星
安装 / 使用
给你的 Agent 一句话(通用)
帮我安装这个 skill:https://raw.githubusercontent.com/roedyrustam/vibes-plug/main/skills/multi-agent-orchestration/SKILL.md
或 curl 直取 SKILL.md
curl -fsSL "https://raw.githubusercontent.com/roedyrustam/vibes-plug/main/skills/multi-agent-orchestration/SKILL.md"
SKILL.MD 节选查看完整文件 ↗
# Multi-Agent Orchestration Expert

[English](#english) | [Bahasa Indonesia](#bahasa-indonesia)

---

<a name="english"></a>
## English

### Description
Production-grade architecture guide for designing, building, and operating **Multi-Agent AI Systems**. Covers stateful graph workflows (**LangGraph**), agent swarms (**CrewAI**, **AutoGen**, **OpenAI Swarm**), supervisor routing patterns, shared memory state management, tool delegation, and human-in-the-loop (HITL) approval gates.

### Trigger Conditions
- Designing complex AI systems requiring multiple specialized agents working together (e.g., Planner + Coder + Reviewer + Tester).
- Implementing stateful, cyclic AI workflows using **LangGr
via SKILL·HOT · 数据来自 GitHub 公开信息 · 原文版权归作者所有