🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, distributed swarm intelligence, RAG integration, and native Claude Code support via MCP protocol. Ranked #1 in agent-based frameworks.
git clone https://github.com/ruvnet/claude-flow.gitclaude-flow is a leading agent orchestration platform designed specifically for Claude, enabling users to deploy intelligent multi-agent swarms that coordinate autonomous workflows and build sophisticated conversational AI systems. With its enterprise-grade architecture and native Claude Code support via the MCP protocol, claude-flow stands out as the top choice in agent-based frameworks. Its advanced features, including distributed swarm intelligence and RAG integration, empower teams to automate complex tasks seamlessly. One of the key benefits of using claude-flow is its ability to significantly enhance workflow automation efficiency. By implementing this skill, teams can save valuable time through the automation of various processes. For instance, code reviews can be automated by deploying specialized agents that assess code quality and suggest improvements, leading to faster turnaround times and higher quality outputs. Additionally, coordinating testing workflows across multiple agents ensures comprehensive coverage and accelerates feedback loops, which is crucial for maintaining software integrity. This skill is particularly beneficial for developers, product managers, and AI practitioners who are looking to optimize their workflows and enhance productivity. It is ideal for teams involved in software development, DevOps, and AI system design. By utilizing claude-flow, organizations can implement security audits through dedicated agents that scan for vulnerabilities, facilitate documentation generation, and optimize deployment pipelines, thereby streamlining their entire development process. While the implementation of claude-flow is classified as advanced, it can typically be set up in about 30 minutes. Users should have a foundational understanding of AI automation and workflow management to maximize the skill's potential. As organizations increasingly adopt AI-first strategies, claude-flow integrates seamlessly into these workflows, allowing teams to harness the power of automation and focus on higher-value tasks.
1. Define the process you want to automate and identify the key roles involved. 2. Create a claude-flow account and navigate to the workflow builder. 3. Add agents to your workflow, specifying their roles and access to resources. 4. Use the visual editor to design the workflow, connecting agents and defining their interactions. 5. Test your workflow with sample inputs and refine as needed. Tip: Start with simple workflows and gradually add complexity.
Automate code reviews by deploying specialized agents that assess code quality and suggest improvements.
Coordinate testing workflows across multiple agents to ensure comprehensive coverage and faster feedback loops.
Implement security audits using dedicated agents that scan for vulnerabilities and compliance issues in software projects.
Facilitate documentation generation by utilizing agents that extract information from codebases and create user-friendly guides.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/ruvnet/claude-flowCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create a claude-flow workflow to automate [PROCESS]. The workflow should include [NUMBER] agents with the following roles: [ROLES]. Each agent should have access to [RESOURCES] and follow these guidelines: [GUIDELINES]. Ensure the workflow can handle [SPECIFIC_SCENARIOS] and provide a summary report at the end.
Workflow Name: Customer Support Automation Agents: 1. Triage Agent: Classifies incoming support tickets based on urgency and topic. 2. Research Agent: Gathers relevant information from knowledge base and previous cases. 3. Resolution Agent: Provides solutions or escalates to human support when necessary. 4. Follow-up Agent: Sends follow-up emails and checks customer satisfaction. Workflow Steps: 1. Triage Agent receives a new ticket: "Issue with payment processing on order #12345". 2. Research Agent finds relevant articles and past cases about payment processing issues. 3. Resolution Agent suggests checking the payment gateway connection and provides step-by-step troubleshooting. 4. Follow-up Agent sends an email to the customer: "We've identified the issue and our team is working on a fix. We'll keep you updated." Summary Report: - Total tickets processed: 5 - Average resolution time: 2 hours 15 minutes - Escalations to human support: 1 - Customer satisfaction rate: 92%
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