ruvnet

CLAUDE.md CI/CD Wiki

Name: CLAUDE.md CI/CD Wiki
Author: ruvnet

DevOps community intermediate

SOURCE https://github.com/ruvnet/ruflo

Description

[](https://github.com/ruvnet/claude-flow)

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

Repository README

This is the README for ruvnet/ruflo, shared by 2 entries in this directory. It describes the repository, not this entry specifically.

🌊 RuFlo v3.5: Enterprise AI Orchestration Platform

[](https://github.com/ruvnet/claude-flow)

[](https://github.com/ruvnet/claude-flow) [](https://www.npmjs.com/package/claude-flow) [](https://www.npmjs.com/package/claude-flow) [](https://ruv.io) [](https://discord.com/invite/dfxmpwkG2D) [](https://github.com/ruvnet/claude-flow) [](https://opensource.org/licenses/MIT)

[](https://x.com/ruv) [](https://www.linkedin.com/in/reuvencohen/) [](https://www.youtube.com/@ReuvenCohen)

Production-ready multi-agent AI orchestration for Claude Code

*Deploy 100+ specialized agents in coordinated swarms with self-learning capabilities, fault-tolerant consensus, and enterprise-grade security.*

**Why Ruflo?** Claude Flow is now Ruflo — named by Ruv, who loves Rust, flow states, and building things that feel inevitable. The "Ru" is the Ruv. The "flo" is the flow. Underneath, WASM kernels written in Rust power the policy engine, embeddings, and proof system. 6,000+ commits later, this is v3.5.

Getting into the Flow

Ruflo is a comprehensive AI agent orchestration framework that transforms Claude Code into a powerful multi-agent development platform. It enables teams to deploy, coordinate, and optimize specialized AI agents working together on complex software engineering tasks.

Self-Learning/Self-Optimizing Agent Architecture

User → Ruflo (CLI/MCP) → Router → Swarm → Agents → Memory → LLM Providers
                       ↑                          ↓
                       └──── Learning Loop ←──────┘

📐 Expanded Architecture — Full system diagram with RuVector intelligence

flowchart TB
    subgraph USER["👤 User Layer"]
        U[User]
    end

    subgraph ENTRY["🚪 Entry Layer"]
        CLI[CLI / MCP Server]
        AID[AIDefence Security]
    end

    subgraph ROUTING["🧭 Routing Layer"]
        QL[Q-Learning Router]
        MOE[MoE - 8 Experts]
        SK[Skills - 130+]
        HK[Hooks - 27]
    end


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