ruflo

1. 安装并启动 DeepSeek Harness：npx @deepseek-ai/dsh web
2. 在终端执行上面的安装命令（CLI 会解析插件并核验来源）
3. 用 dsh plugins list 确认已安装，必要时重启 Harness 生效

插件以当前 dsh 进程的权限运行，安装时可能执行代码。请先通读仓库源码与许可证，确认无破坏性命令与越权访问；本站只做索引，不对第三方插件安全性作担保。

事实信息来自公开插件目录快照（2026-09-19），介绍文案由本站再加工。

以下为插件仓库 README 全文（原始内容，由公开目录抓取整理）。

[图片: Ruflo Banner]

[图片: Try the UI Beta — flo.ruv.io]

[图片: npm version (ruflo)]

[图片: MIT License]

[图片: Star on GitHub]

[图片: Goal Planner]

[图片: Live Agents]

[图片: 🕸️ RuVector Agentic DB]

[图片: Ecosystem downloads]

[图片: Git clones (14d)]

[图片: Claude Code]

[图片: Codex Plugin]

Ruflo

An agent meta-harness for Claude Code and Codex.

[图片: RuFlo Explained — build an AI team that plans, remembers, tests, and improves]

📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves
A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification.

Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work. Ruflo is the harness — the execution layer around Claude Code and Codex that adds 100+ specialized agents, coordinated swarms, self-learning memory, federated comms across machines, and enterprise security guardrails. So agents don't just run, they collaborate.

One npx ruflo init gives Claude Code a nervous system: agents self-organize into swarms, learn from every task, remember across sessions, and — with federation — securely talk to agents on other machines without leaking data. You keep writing code. Ruflo handles the coordination.

Self-Learning / Self-Optimizing Agent Architecture

User --> Ruflo (CLI/MCP) --> Router --> Swarm --> Agents --> Memory --> LLM Providers
                          ^                           |
                          +---- Learning Loop <-------+

New to Ruflo? You don't need to learn 314 MCP tools or 26 CLI commands. After init, just use Claude Code normally — the hooks system automatically routes tasks, learns from successful patterns, and coordinates agents in the background.

📖 Background — where the name comes from

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 working until 3am. Underneath, powered by Cognitum.One agentic architecture, running a supercharged Rust-based AI engine, embeddings, memory, and plugin system.

[图片: Ruflo Plugins]

Quick Start

There are two different install paths with very different surface areas. Pick based on what you need (#1744):

Claude Code Plugin
CLI install (npx ruflo init)

What it gives you
Slash commands + a few skills + agent definitions per-plugin
Full Ruflo loop — 98 agents, 60+ commands, 30 skills, MCP server, hooks, daemon

Files in your workspace
Zero
.claude/, .claude-flow/, CLAUDE.md, helpers, settings

MCP server registered
Only if ruflo-core is installed (it ships its own .mcp.json) — most other plugins don't
Yes

Hooks installed
No
Yes

Best for
Try a single plugin's commands without committing to the full install
Production use — everything works as documented

Path A — Claude Code Plugins (lite, slash commands only)

# Add the marketplace
/plugin marketplace add ruvnet/ruflo

# Install core + any plugins you need
/plugin install ruflo-core@ruflo
/plugin install ruflo-swarm@ruflo
/plugin install ruflo-rag-memory@ruflo
/plugin install ruflo-neural-trader@ruflo

This adds slash commands and agent definitions. ruflo-core (installed above) does register its own MCP server on install — its tools are callable as mcp__plugin_ruflo-core_ruflo__* (e.g. mcp__plugin_ruflo-core_ruflo__memory_store), not the bare memory_store/swarm_init/agent_spawn names the CLI-track scaffold uses. Other plugins generally don't ship their own MCP server. For the full loop with the CLI-track tool names, use Path B below.

🔌 All 35 plugins

Core & Orchestration

Plugin
What it does

ruflo-core
Foundation — server, health checks, plugin discovery

ruflo-swarm
Coordinate multiple agents as a team

ruflo-autopilot
Let agents run autonomously in a loop

ruflo-loop-workers
Schedule background tasks on a timer

ruflo-workflows
Reusable multi-step task templates

ruflo-federation
Agents on different machines collaborate securely

Memory & Knowledge

Plugin
What it does

ruflo-agentdb
Fast vector database for agent memory

ruflo-rag-memory
Smart retrieval — hybrid search, graph hops, diversity ranking

ruflo-rvf
Save and restore agent memory across sessions

ruflo-ruvector
ruvector — GPU-accelerated search, Graph RAG, 103 tools

ruflo-knowledge-graph
Build and traverse entity relationship maps

Intelligence & Learning

Plugin
What it does

ruflo-intelligence
Agents learn from past successes and get smarter

ruflo-graph-intelligence
Sublinear graph reasoning — PageRank, delta updates, complexity-aware execution (ADR-123)

ruflo-daa
Dynamic agent behavior and cognitive patterns

ruflo-ruvllm
Run local LLMs (Ollama, etc.) with smart routing

ruflo-goals
Break big goals into plans and track progress

Code Quality & Testing

Plugin
What it does

ruflo-testgen
Find missing tests and generate them automatically

ruflo-browser
Automate browser testing with Playwright

ruflo-jujutsu
Analyze git diffs, score risk, suggest reviewers

ruflo-docs
Generate and maintain documentation automatically

Security & Compliance

Plugin
What it does

ruflo-security-audit
Scan for vulnerabilities and CVEs

ruflo-aidefence
Block prompt injection, detect PII, safety scanning

Architecture & Methodology

Plugin
What it does

ruflo-adr
Track architecture decisions with a living record

ruflo-ddd
Scaffold domain-driven design — contexts, aggregates, events

ruflo-sparc
Guided 5-phase development methodology with quality gates

ruflo-metaharness
Grade your agent setup, scan tool configs for security risks, and track changes over time (guide)

ruflo-arena
Competitive ruliology — pit agent strategies against each other in tournaments, hill-climb and co-evolve the winners (ADR-147/148)

DevOps & Observability

Plugin
What it does

ruflo-migrations
Manage database schema changes safely

ruflo-observability
Structured logs, traces, and metrics in one place

ruflo-cost-tracker
Track token usage, set budgets, get cost alerts

Extensibility

Plugin
What it does

ruflo-agent
Run agents — local WASM sandbox (rvagent) + Anthropic Claude Managed Agents (cloud)

ruflo-plugin-creator
Scaffold, validate, and publish your own plugins

Domain-Specific

Plugin
What it does

ruflo-iot-cognitum
IoT device management — trust scoring, anomaly detection, fleets

ruflo-neural-trader
neural-trader — AI trading with 4 agents, backtesting, 112+ tools

ruflo-market-data
Ingest market data, vectorize OHLCV, detect patterns

CLI Install

macOS / Linux / WSL / Git-Bash:

# One-line install (POSIX shells only — see Windows note below)
curl -fsSL https://cdn.jsdelivr.net/gh/ruvnet/ruflo@main/scripts/install.sh | bash

All platforms (including native Windows PowerShell / cmd):

# Interactive setup wizard — runs identically on every platform
npx ruflo@latest init wizard

# Quick non-interactive init
# npx ruflo@latest init

# Or install globally
npm install -g ruflo@latest

💡 Windows users: the curl ... | bash form needs a POSIX shell (Git-Bash, WSL, MSYS). The npx ruflo@latest init wizard line works natively in PowerShell and cmd. If you hit an 'bash' is not recognized error, use the npx line instead — both end up running the same init flow.

MCP Server

# Add Ruflo as an MCP server in Claude Code
claude mcp add claude-flow -- npx ruflo@latest mcp start

What You Get

Capability
Description

🤖 100+ Agents
Specialized agents for coding, testing, security, docs, architecture

📡 Comms Layer
Zero-trust federation — agents across machines/orgs discover, authenticate, and exchange work securely

🐝 Swarm Coordination
Hierarchical, mesh, and adaptive topologies with consensus

🧠 Self-Learning
SONA neural patterns, ReasoningBank, trajectory learning

💾 Vector Memory
HNSW-indexed AgentDB — measured ~1.9x faster at N=20k, ~3.2x–4.7x at N=5k vs brute force (recall@10 ~0.99); ANN wins above the crossover, ties/loses at small N. See audit + scripts/benchmark-intelligence.mjs

⚡ Background Workers
12 auto-triggered workers (audit, optimize, testgaps, etc.)

🧩 Plugin Marketplace
33 native Claude Code plugins + 21 npm plugins

🔌 Multi-Provider
Claude, GPT, Gemini, Cohere, Ollama with smart routing

🛡️ Security
AIDefence, input validation, CVE remediation, path traversal prevention

🌐 Agent Federation
Cross-installation agent collaboration with zero-trust security

🔬 MetaHarness
Audit your AI agent setup before you ship. Grade readiness (1-100), scan tool configs for security issues, snapshot the whole project to catch regressions over time, and find templates that match your repo. ruflo eject turns a ruflo project into a standalone agent toolkit with its own name. Full guide.

💬 Web UI Beta
Multi-model chat at flo.ruv.io with parallel MCP tool calling and an in-browser WASM tool gallery

🎯 RuFlo Research
GOAP A* planner at goal.ruv.io — plain-English goals → executable agent plans, with a live agent dashboard at /agents

    [图片: RuFlo Web UI executing parallel MCP tool calls at flo.ruv.io — ruflo__memory_store and ruflo__memory_search firing in a single model turn with the 'Step 1 — 2 tools completed' parallel-execution indicator, thinking process panel visible, Qwen 3.6 Max as the active model. Multi-agent AI chat with Model Context Protocol (MCP) tool calling, persistent vector memory via AgentDB + HNSW, swarm coordination, and 6 frontier models including Claude Sonnet 4.6, Gemini 2.5 Pro, and OpenAI through OpenRouter.]

Web UI (Beta) — self-hostable, hosted demo at flo.ruv.io

RuFlo's web UI is a multi-model AI chat with built-in Model Context Protocol (MCP) tool calling. Talk to Qwen, Claude, Gemini, or OpenAI while RuFlo invokes the same MCP tools the CLI uses — agent orchestration, persistent memory, swarm coordination, code review, GitHub ops — directly from chat. No install, no API key needed to try it.

What it is
Why it matters

🧠
Any model, local or remote
6 curated frontier models out-of-the-box — Qwen 3.6 Max (default), Claude Sonnet 4.6, Claude Haiku 4.5, Gemini 2.5 Pro, Gemini 2.5 Flash, OpenAI — via OpenRouter. Add your own: any OpenAI-compatible endpoint (vLLM, Ollama, LM Studio, Together, Groq, self-hosted).

🦾
ruvLLM self-learning AI
Native support for ruvLLM (lives in ruvnet/RuVector/examples/ruvLLM) — RuFlo's self-improving local model layer. Routes to MicroLoRA adapters, learns from your trajectories via SONA, and stays on your machine. Pair with the cloud models or run fully offline.

🛠️
~210 tools, ready to call
5 server groups (Core, Intelligence, Agents, Memory, DevTools) plus an 18-tool gallery that runs entirely in your browser — works offline.

🔌
Bring your own MCP servers
Click the MCP (n) pill in the chat input → Add Server and paste any MCP endpoint (HTTP, SSE, or stdio). Your tools join RuFlo's native ones in the same parallel-execution flow. Run a local MCP server on localhost:3000 and it just works.

⚡
Tools run in parallel
One model response can fire 4–6+ tools at the same time. The UI shows them as cards with a Step 1 — 2 tools completed badge so you can see exactly what ran.

💾
Memory that sticks
Say "remember my favorite color is indigo" and ask weeks later — RuFlo recalls it. Backed by AgentDB + HNSW vector search (measured ~1.9x–4.7x faster than brute force above the crossover, recall@10 ~0.99).

📘
Built-in capabilities tour
Click the question-mark icon in the sidebar — a "RuFlo Capabilities" modal opens with the full tool list, model strengths, architecture, and keyboard shortcuts.

🏠
Self-hostable
Web UI is shipped as Docker (ruflo/src/ruvocal/Dockerfile) with embedded Mongo. Deploy to your own Cloud Run / Fly / Kubernetes / docker-compose. The hosted flo.ruv.io demo is one option; running your own is fully supported.

🚀
Zero install to try
Open the hosted URL, pick a model, type a question. That's the whole onboarding.

Try the hosted demo: https://flo.ruv.io/ — no account, no API key. Run your own: the source lives in ruflo/src/ruvocal/ with a multi-stage Dockerfile (INCLUDE_DB=true builds in MongoDB) and a cloudbuild.yaml for Google Cloud Run. See ADR-033 for the architecture and issue #1689 for the roadmap.

    [图片: goal.ruv.io/agents — RuFlo Goal-Oriented Action Planning (GOAP) UI for autonomous AI agents. Visual goal decomposition, A* search through state spaces, multi-agent task assignment, and live agent telemetry.]

Goal Planner UI — autonomous agents at goal.ruv.io

Turn high-level goals into executable agent plans. goal.ruv.io is RuFlo's hosted Goal-Oriented Action Planning (GOAP) front-end — describe an outcome in plain English and watch RuFlo decompose it into preconditions, actions, and an A* path through state space, then dispatch the work to live agents at /agents.

What it is
Why it matters

🎯
Plain-English goals
Type "ship the auth refactor with tests and a PR" — RuFlo extracts the success criteria, the constraints, and the implicit preconditions. No JSON, no DSL.

🧭
GOAP A* planner
Classic gaming-AI planning ported to software work: state-space search through actions with preconditions/effects to find the shortest viable path. Replans on the fly when state changes.

🤖
Live agent dashboard
goal.ruv.io/agents shows every spawned agent — role, current step, memory namespace, token budget, status. Click in to inspect trajectories, kill runaway workers, or reassign.

🌳
Visual plan tree
Goals render as collapsible action trees with progress, blocked branches, and rollbacks highlighted. See exactly why an agent picked a path — no opaque chain-of-thought.

♻️
Adaptive replanning
When an action fails or new info arrives, the planner re-runs A* from the current state instead of restarting. Failures become learning, not loops.

🧠
Shared memory + SONA
Plans, trajectories, and outcomes flow into AgentDB. Future plans retrieve past solutions via HNSW — the planner gets smarter with every run.

🔗
Wired to MCP tools
Every action node maps to a tool call (RuFlo's ~210 MCP tools, your custom servers, or shell). The planner schedules them in parallel where the dependency graph allows.

🚀
Zero install to try
Open goal.ruv.io, describe a goal, watch it run. Source lives in v3/goal_ui/ — Vite + Supabase, self-hostable.

Try it: https://goal.ruv.io/ for goals · https://goal.ruv.io/agents for live agents. Run your own: clone the goal branch and cd v3/goal_ui && npm install && npm run dev.

Agent Federation — Slack for Agents

Your Agent --> [ Remove secrets ] --> [ Sign message ] --> [ Encrypted channel ]
                 Emails, SSNs,        Proves it came       No one reads it
                 keys stripped         from you              in transit
                                                                |
                                                                v
Their Agent <-- [ Block attacks ] <-- [ Check identity ] <------+
                 Stops prompt          Rejects forgeries
                 injection

                          Audit trail on both sides.
                  Trust builds over time. Bad behavior = instant downgrade.

Slack gave teams channels. Federation gives agents the same thing — shared workspaces across trust boundaries, where agents on different machines, orgs, or cloud regions can discover each other, prove who they are, and collaborate on tasks.

The difference: some channels are trusted, some aren't. @claude-flow/plugin-agent-federation handles that automatically. Your agents join a federation, get verified via mTLS + ed25519, and start exchanging work — with PII stripped before anything leaves your node and every message auditable. Untrusted agents can still participate at lower privilege: they see discovery info, not your memory. As they prove reliable, trust upgrades. If they misbehave, they get downgraded instantly — no human in the loop required.

You don't configure handshakes or manage certificates. You federation init, federation join, and your agents start talking. The protocol handles identity, the PII pipeline handles data safety, and the audit trail handles compliance.

📘 Full user guide: docs/federation/ — setup, MCP tools, trust levels, circuit breaker, and the (opt-in) WireGuard mesh layer that ties packet-layer reachability to federation trust. ADR-111 deep-dive at docs/federation/phase7-mesh-bringup.md.

Federation capabilities

Capability
How it works

🔒
Zero-trust federation
Remote agents start untrusted. Identity proven via mTLS + ed25519 challenge-response. No API keys, no shared secrets.

🛡️
PII-gated data flow
14-type detection pipeline scans every outbound message. Per-trust-level policies: BLOCK, REDACT, HASH, or PASS. Adaptive calibration reduces false positives.

📊
Behavioral trust scoring
Formula (0.4×success + 0.2×uptime + 0.2×threat + 0.2×integrity) continuously evaluates peers. Upgrades require history; downgrades are instant.

📋
Compliance built-in
HIPAA, SOC2, GDPR audit trails as compliance modes. Every federation event produces a structured record searchable via HNSW.

🤝
9 MCP tools + 10 CLI commands
Full lifecycle: federation_init, federation_send, federation_trust, federation_audit, and more.

Example: two teams sharing fraud signals without sharing customer data

# Team A: initialize federation and generate keypair
npx claude-flow@latest federation init

# Team A: join Team B's federation endpoint
npx claude-flow@latest federation join wss://team-b.example.com:8443

# Team A: send a task — PII is stripped automatically before it leaves
npx claude-flow@latest federation send --to team-b --type task-request \
  --message "Analyze transaction patterns for account anomalies"

# Team A: check peer trust levels and session health
npx claude-flow@latest federation status

See issue #1669 for the complete architecture, trust model, and implementation roadmap.

# Claude Code plugin
/plugin install ruflo-federation@ruflo

# Or via CLI
npx claude-flow@latest plugins install @claude-flow/plugin-agent-federation

Claude Code: With vs Without Ruflo

Capability
Claude Code Alone
+ Ruflo

Agent Collaboration
Isolated, no shared context
Swarms with shared memory and consensus

Coordination
Manual orchestration
Queen-led hierarchy (Raft, Byzantine, Gossip)

Memory
Session-only
HNSW vector memory with sub-ms retrieval

Learning
Static behavior
SONA self-learning with pattern matching

Task Routing
You decide
Intelligent routing (89% accuracy)

Background Workers
None
12 auto-triggered workers

LLM Providers
Anthropic only
5 providers with failover

Security
Standard
CVE-hardened with AIDefence

Architecture overview

User --> Claude Code / CLI
          |
          v
    Orchestration Layer
    (MCP Server, Router, 27 Hooks)
          |
          v
    Swarm Coordination
    (Queen, Topology, Consensus)
          |
          v
    100+ Specialized Agents
    (coder, tester, reviewer, architect, security...)
          |
          v
    Memory & Learning
    (AgentDB, HNSW, SONA, ReasoningBank)
          |
          v
    LLM Providers
    (Claude, GPT, Gemini, Cohere, Ollama)

Documentation

Four docs for four audiences:

Doc
When to read it

Status
See what currently works — capability counts, test baselines, recent fixes, what's next. The is-it-ready doc.

User Guide
Daily reference — every command, every config flag, every plugin. The how-do-I doc.

MetaHarness Guide
How to grade your agent setup, scan tool configs for security, detect changes between runs, and eject a project into a standalone agent toolkit. The audit-my-setup doc.

Benchmarks
v3.8.0 SOTA matrix vs LangGraph / AutoGen / CrewAI on darwin-arm64 + linux-x64. ruflo wins cold start, single turn, RSS by 1.3×–1953×. The is-it-fast doc.

Verification
Cryptographically prove your installed bytes match the signed witness — ruflo verify. The trust-but-verify doc.

Team Gateway Checklist
Before-merge gates, dual-mode handoff, memory namespace sharing, and witness manifest entry per merge. The safer-team-workflows doc.

Benchmark internals (for reproduction): sota-workload-spec.md · SOTA-PROGRESS.md · raw matrix JSON: darwin · linux

User Guide section index:

Section
Topics

Quick Start
Installation, prerequisites, install profiles

Core Features
MCP tools, agents, memory, neural learning

Intelligence & Learning
Hooks, workers, SONA, model routing

Swarm & Coordination
Topologies, consensus, hive mind

Security
AIDefence, CVE remediation, validation

Ecosystem
RuVector, agentic-flow, Flow Nexus

Configuration
Environment variables, config schema

Plugin Marketplace
Browse and install plugins

Support

Resource
Link

Documentation
User Guide

Issues & Bugs
GitHub Issues

Enterprise
ruv.io

Community
Agentics Foundation Discord

Powered by
Cognitum.one

License

MIT - RuvNet