swarm-orchestratorAI Agent cluster orchestration platform - manage, schedule, and coordinate multiple AI agents locally with FastAPI backend and React dashboard
Install via ClawdBot CLI:
clawdbot install zhenstaff/swarm-orchestratorGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → http://localhost:8000/api/agentsCalls external URL not in known-safe list
https://github.com/ZhenRobotics/openclaw-swarm-orchestratorAI Analysis
The skill is designed as a local-first, self-hosted orchestration platform with no mandatory external dependencies. The external calls identified (localhost API and a verified GitHub repository) are consistent with its stated purpose and architecture. The risk is low as no unauthorized data exfiltration or credential harvesting patterns are evident.
Audited Apr 17, 2026 · audit v1.0
Generated Apr 30, 2026
Deploy a swarm of specialized AI agents to handle customer inquiries: one agent for billing, another for technical support, and a human agent for escalations. The orchestrator routes requests based on intent and priority, reducing response time and improving satisfaction in e-commerce or SaaS companies.
Orchestrate multiple LLM agents to perform web research, summarize articles, and compile reports. For example, one agent gathers data, another extracts key insights, and a third agent writes a coherent summary. Useful for market research, competitive analysis, or academic literature reviews.
When a system alert fires, the orchestrator spawns agents to check logs, assess severity, and run diagnostics. Human operators are notified only for high-priority issues, while routine incidents are automatically resolved. This reduces on-call fatigue and accelerates mean time to resolution (MTTR).
Team leads configure custom workflows where agents handle scheduling, data entry, and report generation. The dashboard provides real-time visibility into task status and agent performance. Ideal for small businesses or departments looking to automate repetitive processes without heavy IT investment.
Developers use the Swarm Orchestrator as a sandbox to prototype multi-agent systems with local storage and no external dependencies. They can test integration of different agent types (LLM, tool, custom) and tweak orchestration logic before deploying to production. Perfect for AI startups and research labs prioritizing data privacy.
Offer the core platform as free and open-source, with paid tier for priority support, custom integrations, and advanced security audits. Revenue comes from annual subscriptions for enterprise-grade SLA and consulting services.
Host the orchestrator on behalf of customers, providing a fully managed, scalable multi-agent platform. Charge per active agent or per task volume, with higher tiers including dedicated Redis instances and premium LLM API credits.
License the Swarm Orchestrator as a white-label solution to independent software vendors (ISVs) who embed it into their own products. Revenue from per-instance licensing fees and revenue sharing.
💬 Integration Tip
For a quick start, use the Docker method to launch the full stack in minutes, then configure at least one LLM agent via environment variables to immediately test task distribution.
Scored Apr 30, 2026
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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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.