eh-multi-agent多 agent 协调设计模式。当需要选择 coordinator/fork/swarm 模式或设计跨 agent 协作时使用。
Install via ClawdBot CLI:
clawdbot install lanyasheng/eh-multi-agentGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Apr 21, 2026
A team uses the coordinator pattern to manage multiple AI agents working on different modules of a codebase, with file claim and lock preventing conflicts when editing shared files like configuration scripts. Workspace isolation ensures each agent operates in a dedicated environment, while the synthesis gate allows a lead agent to compile results into a unified deployment plan.
In a marketing agency, a swarm of AI agents collaboratively drafts and refines content for a campaign, using shared task lists to assign sections like social media posts and blog articles. File claim and lock mechanisms prevent overwrites during concurrent edits, with workspace isolation maintaining version control for each agent's contributions.
Researchers employ the fork pattern to delegate data processing tasks to multiple AI agents analyzing different datasets simultaneously, with workspace isolation ensuring clean separation of results. The synthesis gate is used by a coordinator agent to aggregate findings into a comprehensive report, avoiding file conflicts through claim protocols.
A support team uses the coordinator pattern to assign AI agents to handle various ticket types, such as technical issues or billing inquiries, with shared task lists for prioritization. Workspace isolation allows each agent to access relevant databases without interference, and the synthesis gate helps compile resolution summaries for quality assurance.
Offer a cloud-based service that integrates multi-agent coordination patterns, providing tools for task delegation, file locking, and workspace isolation to enterprises. Revenue is generated through subscription tiers based on the number of agents and advanced features like synthesis gate analytics.
Provide expert consulting to help organizations design and deploy multi-agent systems using patterns like coordinator/fork/swarm selection and review-execution separation. Revenue comes from project-based fees for setup, training, and ongoing support to optimize agent workflows.
Distribute the multi-agent skill as open-source software under MIT license, with premium add-ons for enhanced features such as automated synthesis gate tools and advanced conflict resolution. Revenue is earned from sales of these add-ons and enterprise support packages.
💬 Integration Tip
Start by defining clear delegation modes and implementing file claim protocols to avoid conflicts; use workspace isolation to maintain agent independence and simplify debugging.
Scored Apr 19, 2026
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Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.