Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orch...
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install openserv-multi-agent-workflows或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install openserv-multi-agent-workflows⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/openserv-multi-agent-workflows/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: openserv-multi-agent-workflows description: Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents. ---
Build workflows where multiple AI agents collaborate to complete complex tasks.
Reference files:
reference.md - Workflow patterns, declarative sync, triggers, monitoringtroubleshooting.md - Common issues and solutionsexamples/ - Complete pipeline examples (blog, youtube-to-blog, etc.)---
See examples/ for complete runnable examples:
blog-pipeline.md - Simple 2-agent workflow (research → write)content-creation-pipeline.md - 3-agent workflow (research → write → image)life-coaching-pipeline.md - Complex 6-agent workflow with comprehensive input schemaRecommended pattern using workflows.sync():
client.authenticate()client.agents.listMarketplace()client.workflows.create() including:- Triggers - Tasks - Edges (⚠️ CRITICAL - connects triggers and tasks together)
⚠️ CRITICAL: Always define edges when creating workflows. Setting task dependencies is NOT enough - you must create workflow edges to actually connect triggers to tasks and tasks to each other.
---
When creating workflows (via workflows.create() or provision()), two properties are critical:
name (string) - This becomes the agent name in ERC-8004. Make it polished, punchy, and memorable — this is the public-facing brand name users see. Think product launch, not variable name. Examples: 'Instant Blog Machine', 'AI Video Studio', 'Polymarket Intelligence'.goal (string, required) - A detailed description of what the workflow accomplishes. Must be descriptive and thorough — short or vague goals will cause API calls to fail. Write at least a full sentence explaining the end-to-end purpose of the workflow.---
A workflow (workspace) is a container that holds multiple agents and their tasks.
dependencies: [taskId1, taskId2]done// Search marketplace for agents by name/capability (semantic search)
const result = await client.agents.listMarketplace({ search: 'research' })
const agents = result.items // Array of marketplace agents
// Get agent details
const agent = await client.agents.get({ id: 123 })
console.log(agent.capabilities_description)
// Note: client.agents.searchOwned() only searches YOUR OWN agents
// Use listMarketplace() to find public agents for multi-agent workflows
Common agent types: Research (Grok, Perplexity), Content writers, Data analysis, Social media (Nano Banana Pro), Video/audio creators.
---
CRITICAL: Carefully design your workflow edges to avoid creating tangled "spaghetti" graphs.
A well-designed workflow has clear, intentional data flow. Common mistakes lead to unmaintainable workflows.
┌──────────────────────────────────┐
│ ┌─────────┐ │
│ ┌─────┤ Agent A ├─────┐ │
│ │ └────┬────┘ │ │
│ │ │ │ │
Trigger ─┼─────┼──────────┼──────────┼──────┤
│ │ │ │ │
│ │ ┌────┴────┐ │ │
│ └─────┤ Agent B ├─────┘ │
│ └─────────┘ │
└──────────────────────────────────┘
(Spaghetti - avoid this!)
This creates:
Sequential Pipeline:
Trigger → Research → Content → Enhancement → Output
Staged Fan-Out:
┌─ Task A ─┐
Trigger → Research ─┼─ Task B ─┼─→ Combiner → Output
└─ Task C ─┘
Conditional Branching (v1.1.3+):
┌─[approved]─→ Process
Trigger → Review ──┤
└─[rejected]─→ Reject Handler
Use outputOptions on tasks and sourcePort on edges for branching.
---
This skill may be outdated. The OpenServ team ships updates regularly—new features, API changes, and bug fixes won't be reflected here until you update. If something isn't working as expected, or you want to make sure you have the latest information, update the skill before proceeding.
# Check if updates are available
npx skills check
# Update all installed skills to latest versions
npx skills update
Or reinstall the OpenServ skills directly:
npx skills add openserv-labs/skills
---
安装 OpenServ Multi Agent Workflows 后,可以对 AI 说这些话来触发它
Help me get started with OpenServ Multi Agent Workflows
Explains what OpenServ Multi Agent Workflows does, walks through the setup, and runs a quick demo based on your current project
Use OpenServ Multi Agent Workflows to multi-agent workflow examples to work together on the OpenServ Plat...
Invokes OpenServ Multi Agent Workflows with the right parameters and returns the result directly in the conversation
What can I do with OpenServ Multi Agent Workflows in my ai agent & automation workflow?
Lists the top use cases for OpenServ Multi Agent Workflows, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/openserv-multi-agent-workflows/ 目录(个人级,所有项目可用),或 .claude/skills/openserv-multi-agent-workflows/(项目级)。重启 AI 客户端后,用 /openserv-multi-agent-workflows 主动调用,或让 AI 根据上下文自动发现并使用。
OpenServ Multi Agent Workflows 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
OpenServ Multi Agent Workflows 可免费安装使用。请查阅仓库了解许可证信息。
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orch...
Automate my ai agent & automation tasks using OpenServ Multi Agent Workflows
Identifies repetitive steps in your workflow and sets up OpenServ Multi Agent Workflows to handle them automatically
OpenServ Multi Agent Workflows 属于「AI Agent & Automation」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。