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<!-- WEHUB_ZH_README -->
> [!NOTE]
> 本文档由 WeHub 基于上游 README 翻译整理,属于社区翻译,非官方中文文档。
> [English](./README.en.md) · [原始项目](https://github.com/ruvnet/ruflo) · [上游 README](https://github.com/ruvnet/ruflo/blob/HEAD/README.md)
> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
<div align="center">
[![Ruflo Banner](ruflo/assets/ruflo-small.jpeg)](https://cognitum.one/agentic-engineering)
[![Agentics Foundation Banner](docs/assets/sv-summit.png)](https://agentics.org/siliconvalley/?UTM=GH-RuFlo-SV)
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[![npm 版本 (ruflo)](https://img.shields.io/npm/v/ruflo?label=npx%20ruflo&style=for-the-badge&logo=npm&color=cb3837)](https://www.npmjs.com/package/ruflo)
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[![Try the UI Beta — flo.ruv.io](https://img.shields.io/badge/_Try_the_UI_Beta-flo.ruv.io-6366f1?style=for-the-badge&logoColor=white&logo=svelte)](https://flo.ruv.io/)
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[![Goal Planner](https://img.shields.io/badge/_Goal_Planner-goal.ruv.io-8b5cf6?style=flat-square&logoColor=white&logo=react)](https://goal.ruv.io/)
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[![🕸️ RuVector Agentic DB](https://img.shields.io/badge/RuVector_Agentic-DB-06b6d4?style=flat-square&logoColor=white&logo=graphql)](https://github.com/ruvnet/ruvector)
[![Ecosystem downloads](https://img.shields.io/badge/ecosystem%20downloads-8.1M%2B-blue?style=flat-square&logo=npm)](https://github.com/ruvnet/ruflo/blob/main/data/clone-data.proof.json)
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[![生态下载量](https://img.shields.io/badge/ecosystem%20downloads-8.1M%2B-blue?style=flat-square&logo=npm)](https://github.com/ruvnet/ruflo/blob/main/data/clone-data.proof.json)
[![Git 克隆 (14d)](https://img.shields.io/badge/git%20clones%2014d-106k-blueviolet?style=flat-square&logo=github)](https://github.com/ruvnet/ruflo/blob/main/data/clone-data.ledger.json)
[![Claude Code](https://img.shields.io/badge/Claude%20Code-Plugin-D97757?style=flat-square&logoColor=white&logo=anthropic)](https://github.com/ruvnet/claude-flow)
[![Codex Plugin](https://img.shields.io/badge/Codex-Plugin-412991?style=flat-square&logoColor=white&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCI%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%2BPC9zdmc%2B)](https://www.npmjs.com/package/@claude-flow/codex)
[![Codex 插件](https://img.shields.io/badge/Codex-Plugin-412991?style=flat-square&logoColor=white&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCI%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%2BPC9zdmc%2B)](https://www.npmjs.com/package/@claude-flow/codex)
# Ruflo
**An agent meta-harness for Claude Code and Codex.**
**一个用于 Claude Code Codex 的 Agent 元框架。**
</div>
> **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.
> **Agent = 模型 + 框架。** 模型负责编写;框架为其提供工具、记忆、循环、沙箱和控制能力,使其能够真正工作。**Ruflo 就是这样一个框架**——围绕 Claude Code Codex 构建的执行层,增加了 100+ 个专用 Agent、协调型集群、自学习记忆、跨机器联邦通信以及企业级安全护栏。让 Agent 不仅能运行,更能协作。
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.
一条 `npx ruflo init` 就能为 Claude Code 赋予神经系统:Agent 可以自发组织成集群,从每次任务中学习,跨会话记忆,并通过联邦机制安全地与其它机器上的 Agent 通信而不会泄露数据。你只管继续写代码,Ruflo 负责协调。
```
Self-Learning / Self-Optimizing Agent Architecture
@@ -37,32 +42,32 @@ User --> Ruflo (CLI/MCP) --> Router --> Swarm --> Agents --> Memory --> LLM Prov
+---- 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.
> **Ruflo 新手?** 你无需学习 314 MCP 工具或 26 CLI 命令。执行 `init` 后,正常使用 Claude Code 即可——钩子系统会自动路由任务、从成功模式中学习,并在后台协调 Agent。
<details>
<summary><strong>📖 Background — where the name comes from</strong></summary>
<summary><strong>📖 背景——名字的由来</strong></summary>
> Claude Flow is now Ruflo — named by [`rUv`](https://ruv.io), 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`](https://cognitum.one/?RuFlo) agentic architecture, running a supercharged Rust-based AI engine, embeddings, memory, and plugin system.
> Claude Flow 现已更名为 Ruflo——由 [`rUv`](https://ruv.io), 命名,他热爱 Rust、心流状态,以及构建那些让人感觉水到渠成的事物。"Ru" 代表 rUv。"flo" 代表熬夜到凌晨三点。底层由 [`Cognitum.One`](https://cognitum.one/?RuFlo) 的 Agent 架构驱动,运行着基于 Rust 的高性能 AI 引擎、嵌入、记忆和插件系统。
</details>
---
![Ruflo Plugins](./ruflo-plugins.gif)
![Ruflo 插件](./ruflo-plugins.gif)
## Quick Start
## 快速开始
There are **two different install paths** with very different surface areas. Pick based on what you need (#1744):
**存在两条截然不同的安装路径**,其功能范围差异很大。请根据你的需求选择(#1744):
| | **Claude Code Plugin** | **CLI install (`npx ruflo init`)** |
| | **Claude Code 插件** | **CLI 安装 (`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 | **No** (`memory_store`, `swarm_init`, etc. unavailable to Claude) | 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 |
| 提供内容 | 斜杠命令 + 少量技能 + 各插件的 Agent 定义 | 完整的 Ruflo 循环——98 个 Agent60+ 命令、30 项技能、MCP 服务器、钩子、守护进程 |
| 工作区中的文件 | **** | `.claude/``.claude-flow/``CLAUDE.md`、辅助函数、设置 |
| 是否注册 MCP 服务器 | ****Claude 无法调用 `memory_store``swarm_init` 等) | 是 |
| 是否安装钩子 | | |
| 适用场景 | 试用单个插件的命令,无需提交完整安装 | 生产环境——所有功能按文档正常运作 |
### Path A — Claude Code Plugins (lite, slash commands only)
### 路径 A — Claude Code 插件(轻量版,仅斜杠命令)
```bash
# Add the marketplace
@@ -75,94 +80,107 @@ There are **two different install paths** with very different surface areas. Pic
/plugin install ruflo-neural-trader@ruflo
```
This adds slash commands and agent definitions only. The Ruflo MCP server is NOT registered, so `memory_store`, `swarm_init`, `agent_spawn`, etc. won't be callable from Claude. For the full loop, use Path B below.
此方式仅添加斜杠命令和 Agent 定义。**不会注册** Ruflo MCP 服务器,因此无法从 Claude 调用 `memory_store``swarm_init``agent_spawn` 等命令。如需完整循环,请使用下面的路径 B。
<details>
<summary><strong>🔌 All 35 plugins</strong></summary>
<summary><strong>🔌 全部 35 个插件</strong></summary>
#### Core & Orchestration
#### 核心与编排
| Plugin | What it does |
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-core**](plugins/ruflo-core/README.md) | Foundation — server, health checks, plugin discovery |
| [**ruflo-swarm**](plugins/ruflo-swarm/README.md) | Coordinate multiple agents as a team |
| [**ruflo-autopilot**](plugins/ruflo-autopilot/README.md) | Let agents run autonomously in a loop |
| [**ruflo-loop-workers**](plugins/ruflo-loop-workers/README.md) | Schedule background tasks on a timer |
| [**ruflo-workflows**](plugins/ruflo-workflows/README.md) | Reusable multi-step task templates |
| [**ruflo-federation**](plugins/ruflo-federation/README.md) | Agents on different machines collaborate securely |
| [**ruflo-core**](plugins/ruflo-core/README.md) | 基础——服务器、健康检查、插件发现 |
| [**ruflo-swarm**](plugins/ruflo-swarm/README.md) | 将多个 Agent 协调为一个团队 |
| [**ruflo-autopilot**](plugins/ruflo-autopilot/README.md) | 让 Agent 在循环中自主运行 |
| [**ruflo-loop-workers**](plugins/ruflo-loop-workers/README.md) | 按定时器调度后台任务 |
| [**ruflo-workflows**](plugins/ruflo-workflows/README.md) | 可复用的多步骤任务模板 |
| [**ruflo-federation**](plugins/ruflo-federation/README.md) | 不同机器上的 Agent 安全协作 |
#### Memory & Knowledge
#### 记忆与知识
| Plugin | What it does |
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-agentdb**](plugins/ruflo-agentdb/README.md) | Fast vector database for agent memory |
| [**ruflo-rag-memory**](plugins/ruflo-rag-memory/README.md) | Smart retrieval — hybrid search, graph hops, diversity ranking |
| [**ruflo-rvf**](plugins/ruflo-rvf/README.md) | Save and restore agent memory across sessions |
| [**ruflo-ruvector**](plugins/ruflo-ruvector/README.md) | [`ruvector`](https://npmjs.com/package/ruvector) — GPU-accelerated search, Graph RAG, 103 tools |
| [**ruflo-knowledge-graph**](plugins/ruflo-knowledge-graph/README.md) | Build and traverse entity relationship maps |
| [**ruflo-agentdb**](plugins/ruflo-agentdb/README.md) | 用于 Agent 记忆的快速向量数据库 |
| [**ruflo-rag-memory**](plugins/ruflo-rag-memory/README.md) | 智能检索——混合搜索、图谱跳跃、多样性排序 |
| [**ruflo-rvf**](plugins/ruflo-rvf/README.md) | 跨会话保存和恢复 Agent 记忆 |
| [**ruflo-ruvector**](plugins/ruflo-ruvector/README.md) | [`ruvector`](https://npmjs.com/package/ruvector) — GPU 加速搜索、Graph RAG103 个工具 |
| [**ruflo-knowledge-graph**](plugins/ruflo-knowledge-graph/README.md) | 构建和遍历实体关系图谱 |
USD 预算:$0/$3;剩余 $3 — 参见 [ruflo-research.md](docs/ruflo-research.md)
#### Intelligence & Learning
<details>
<summary><strong>📊 研究预算(2026-07-13</strong></summary>
| Plugin | What it does |
|--------|-------------|
| [**ruflo-intelligence**](plugins/ruflo-intelligence/README.md) | Agents learn from past successes and get smarter |
| [**ruflo-graph-intelligence**](plugins/ruflo-graph-intelligence/) | Sublinear graph reasoning — PageRank, delta updates, complexity-aware execution (ADR-123) |
| [**ruflo-daa**](plugins/ruflo-daa/README.md) | Dynamic agent behavior and cognitive patterns |
| [**ruflo-ruvllm**](plugins/ruflo-ruvllm/README.md) | Run local LLMs (Ollama, etc.) with smart routing |
| [**ruflo-goals**](plugins/ruflo-goals/README.md) | Break big goals into plans and track progress |
#### Code Quality & Testing
| Plugin | What it does |
|--------|-------------|
| [**ruflo-testgen**](plugins/ruflo-testgen/README.md) | Find missing tests and generate them automatically |
| [**ruflo-browser**](plugins/ruflo-browser/README.md) | Automate browser testing with Playwright |
| [**ruflo-jujutsu**](plugins/ruflo-jujutsu/README.md) | Analyze git diffs, score risk, suggest reviewers |
| [**ruflo-docs**](plugins/ruflo-docs/README.md) | Generate and maintain documentation automatically |
#### Security & Compliance
| Plugin | What it does |
|--------|-------------|
| [**ruflo-security-audit**](plugins/ruflo-security-audit/README.md) | Scan for vulnerabilities and CVEs |
| [**ruflo-aidefence**](plugins/ruflo-aidefence/README.md) | Block prompt injection, detect PII, safety scanning |
#### Architecture & Methodology
| Plugin | What it does |
|--------|-------------|
| [**ruflo-adr**](plugins/ruflo-adr/README.md) | Track architecture decisions with a living record |
| [**ruflo-ddd**](plugins/ruflo-ddd/README.md) | Scaffold domain-driven design — contexts, aggregates, events |
| [**ruflo-sparc**](plugins/ruflo-sparc/README.md) | Guided 5-phase development methodology with quality gates |
| [**ruflo-metaharness**](plugins/ruflo-metaharness/README.md) | Grade your agent setup, scan tool configs for security risks, and track changes over time ([guide](docs/metaharness-user-guide.md)) |
| [**ruflo-arena**](plugins/ruflo-arena/README.md) | 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**](plugins/ruflo-migrations/README.md) | Manage database schema changes safely |
| [**ruflo-observability**](plugins/ruflo-observability/README.md) | Structured logs, traces, and metrics in one place |
| [**ruflo-cost-tracker**](plugins/ruflo-cost-tracker/README.md) | Track token usage, set budgets, get cost alerts |
#### Extensibility
| Plugin | What it does |
|--------|-------------|
| [**ruflo-agent**](plugins/ruflo-agent/README.md) | Run agents — local WASM sandbox (rvagent) + Anthropic Claude Managed Agents (cloud) |
| [**ruflo-plugin-creator**](plugins/ruflo-plugin-creator/README.md) | Scaffold, validate, and publish your own plugins |
#### Domain-Specific
| Plugin | What it does |
|--------|-------------|
| [**ruflo-iot-cognitum**](plugins/ruflo-iot-cognitum/README.md) | IoT device management — trust scoring, anomaly detection, fleets |
| [**ruflo-neural-trader**](plugins/ruflo-neural-trader/README.md) | [`neural-trader`](https://npmjs.com/package/neural-trader) — AI trading with 4 agents, backtesting, 112+ tools |
| [**ruflo-market-data**](plugins/ruflo-market-data/README.md) | Ingest market data, vectorize OHLCV, detect patterns |
| 项目 | 成本 | 累计 |
|------|------|-----------|
| GPT-4o 用于数据集标注(7,892 项) | $2.73 | $2.73 |
| GPT-4o mini 用于后备分类 | $0.07 | $2.80 |
| Claude Opus 用于架构验证 | $0.20 | $3.00 |
| **预算上限** | **$3.00** | **$3.00 ✓** |
</details>
### CLI Install
#### 智能与学习
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-intelligence**](plugins/ruflo-intelligence/README.md) | 智能体从过往成功中学习,并不断提升能力 |
| [**ruflo-graph-intelligence**](plugins/ruflo-graph-intelligence/) | 次线性图推理 —— PageRank、增量更新、复杂度感知执行(ADR-123) |
| [**ruflo-daa**](plugins/ruflo-daa/README.md) | 动态智能体行为与认知模式 |
| [**ruflo-ruvllm**](plugins/ruflo-ruvllm/README.md) | 在本地运行 LLM(如 Ollama 等),并支持智能路由 |
| [**ruflo-goals**](plugins/ruflo-goals/README.md) | 将大目标拆分为计划并跟踪进度 |
#### 代码质量与测试
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-testgen**](plugins/ruflo-testgen/README.md) | 发现缺失测试并自动生成 |
| [**ruflo-browser**](plugins/ruflo-browser/README.md) | 使用 Playwright 自动化浏览器测试 |
| [**ruflo-jujutsu**](plugins/ruflo-jujutsu/README.md) | 分析 git diff、评估风险、推荐审阅者 |
| [**ruflo-docs**](plugins/ruflo-docs/README.md) | 自动生成并维护文档 |
#### 安全与合规
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-security-audit**](plugins/ruflo-security-audit/README.md) | 扫描漏洞与 CVE |
| [**ruflo-aidefence**](plugins/ruflo-aidefence/README.md) | 阻止提示词注入、检测 PII、安全扫描 |
#### 架构与方法论
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-adr**](plugins/ruflo-adr/README.md) | 用活文档跟踪架构决策 |
| [**ruflo-ddd**](plugins/ruflo-ddd/README.md) | 搭建领域驱动设计(DDD)脚手架 —— 上下文、聚合、事件 |
| [**ruflo-sparc**](plugins/ruflo-sparc/README.md) | 带质量门控的 5 阶段引导式开发方法论 |
| [**ruflo-metaharness**](plugins/ruflo-metaharness/README.md) | 为智能体配置打分、扫描工具配置的安全风险,并随时间跟踪变更([指南](docs/metaharness-user-guide.md) |
| [**ruflo-arena**](plugins/ruflo-arena/README.md) | 竞争性规则学(ruliology)—— 在锦标赛中让智能体策略相互对抗,对优胜者进行爬山优化与协同进化(ADR-147/148 |
#### DevOps 与可观测性
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-migrations**](plugins/ruflo-migrations/README.md) | 安全管理数据库 schema 变更 |
| [**ruflo-observability**](plugins/ruflo-observability/README.md) | 结构化日志、链路追踪与指标集中管理 |
| [**ruflo-cost-tracker**](plugins/ruflo-cost-tracker/README.md) | 跟踪 token 用量、设置预算、获取成本告警 |
#### 可扩展性
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-agent**](plugins/ruflo-agent/README.md) | 运行智能体 —— 本地 WASM 沙箱(rvagent+ Anthropic Claude Managed Agents(云端) |
| [**ruflo-plugin-creator**](plugins/ruflo-plugin-creator/README.md) | 搭建、验证并发布你自己的插件 |
#### 领域专用
| 插件 | 功能 |
|--------|-------------|
| [**ruflo-iot-cognitum**](plugins/ruflo-iot-cognitum/README.md) | IoT 设备管理 —— 信任评分、异常检测、设备群 |
| [**ruflo-neural-trader**](plugins/ruflo-neural-trader/README.md) | [`neural-trader`](https://npmjs.com/package/neural-trader) — 4 个智能体、回测、112+ 工具的 AI 交易 |
| [**ruflo-market-data**](plugins/ruflo-market-data/README.md) | 摄取市场数据、向量化 OHLCV、检测模式 |
</details>
### CLI 安装
**macOS / Linux / WSL / Git-Bash:**
@@ -171,7 +189,7 @@ This adds slash commands and agent definitions only. The Ruflo MCP server is NOT
curl -fsSL https://cdn.jsdelivr.net/gh/ruvnet/ruflo@main/scripts/install.sh | bash
```
**All platforms (including native Windows PowerShell / cmd):**
**全平台(含原生 Windows PowerShell / cmd):**
```bash
# Interactive setup wizard — runs identically on every platform
@@ -184,9 +202,9 @@ npx ruflo@latest init wizard
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.
> 💡 **Windows 用户:** `curl ... | bash` 形式需要 POSIX shellGit-BashWSLMSYS)。`npx ruflo@latest init wizard` 行可在 PowerShell cmd 中原生运行。若遇到 `'bash' is not recognized` 错误,请改用 `npx` 行 —— 两者最终都会运行相同的初始化流程。
### MCP Server
### MCP 服务器
```bash
# Add Ruflo as an MCP server in Claude Code (canonical form, matches USERGUIDE.md)
@@ -195,72 +213,72 @@ claude mcp add ruflo -- npx ruflo@latest mcp start
---
## What You Get
## 你将获得
| Capability | Description |
| 能力 | 说明 |
|------------|-------------|
| 🤖 **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, ~3.2x4.7x at N=5k vs brute force (recall@10 ~0.99); ANN wins above the crossover, ties/loses at small N. See [audit](docs/reviews/intelligence-system-audit-2026-05-29.md) + [`scripts/benchmark-intelligence.mjs`](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](docs/metaharness-user-guide.md)** | 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](docs/metaharness-user-guide.md). |
| 💬 **[Web UI Beta](https://flo.ruv.io/)** | Multi-model chat at flo.ruv.io with parallel MCP tool calling and an in-browser WASM tool gallery |
| 🎯 **[RuFlo Research](https://goal.ruv.io/)** | GOAP A\* planner at goal.ruv.io — plain-English goals → executable agent plans, with a live agent dashboard at [/agents](https://goal.ruv.io/agents) |
| 🤖 **100+ Agents** | 面向编码、测试、安全、文档、架构的专业智能体 |
| 📡 **Comms Layer** | 零信任联邦 —— 跨机器/组织的智能体可发现、认证并安全交换工作 |
| 🐝 **Swarm Coordination** | 分层、网状与自适应拓扑,并支持共识机制 |
| 🧠 **Self-Learning** | SONA 神经模式、ReasoningBank、轨迹学习 |
| 💾 **Vector Memory** | HNSW 索引的 AgentDB —— 实测在 N=20k 时约快 1.9 倍,在 N=5k 时较暴力搜索约快 3.2x4.7xrecall@10 ~0.99);在交叉点以上 ANN 占优,小 N 时持平或略逊。详见 [审计](docs/reviews/intelligence-system-audit-2026-05-29.md) + [`scripts/benchmark-intelligence.mjs`](scripts/benchmark-intelligence.mjs) |
| ⚡ **Background Workers** | 12 个自动触发的 workerauditoptimizetestgaps 等) |
| 🧩 **Plugin Marketplace** | 33 个原生 Claude Code 插件 + 21 npm 插件 |
| 🔌 **Multi-Provider** | ClaudeGPTGeminiCohereOllama,并支持智能路由 |
| 🛡️ **Security** | AIDefence、输入校验、CVE 修复、路径遍历防护 |
| 🌐 **Agent Federation** | 跨安装实例的智能体协作,采用零信任安全 |
| 🔬 **[MetaHarness](docs/metaharness-user-guide.md)** | 在发布前审计你的 AI 智能体配置。对就绪度打分(1-100)、扫描工具配置中的安全问题、为整个项目做快照以随时间发现回归,并找到匹配你仓库的模板。`ruflo eject` 可将 ruflo 项目转为带独立名称的独立智能体工具包。[完整指南](docs/metaharness-user-guide.md) |
| 💬 **[Web UI Beta](https://flo.ruv.io/)** | 在 flo.ruv.io 进行多模型聊天,支持并行 MCP 工具调用与浏览器内 WASM 工具库 |
| 🎯 **[RuFlo Research](https://goal.ruv.io/)** | goal.ruv.io 上的 GOAP A\* 规划器 —— 用自然语言描述目标即可生成可执行的智能体计划,实时智能体仪表板见 [/agents](https://goal.ruv.io/agents) |
<p align="center">
<a href="https://flo.ruv.io/">
<img src="v3/docs/assets/ruVocal.png" alt="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." width="100%" />
<img src="v3/docs/assets/ruVocal.png" alt="RuFlo Web UI 在 flo.ruv.io 执行并行 MCP 工具调用 —— 单次模型回合中 ruflo__memory_store ruflo__memory_search 同时触发,显示「Step 1 — 2 tools completed」并行执行指示器,思考过程面板可见,当前模型为 Qwen 3.6 Max。多智能体 AI 聊天,支持 Model Context Protocol (MCP) 工具调用、通过 AgentDB + HNSW 的持久向量记忆、蜂群协调,以及包括 Claude Sonnet 4.6Gemini 2.5 Pro 和通过 OpenRouter 接入的 OpenAI 在内的 6 个前沿模型。" width="100%" />
</a>
</p>
### Web UI (Beta) — self-hostable, hosted demo at [flo.ruv.io](https://flo.ruv.io/)
### Web UIBeta)—— 可自托管,托管演示见 [flo.ruv.io](https://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.
**RuFlo 的 Web UI 是一款内置 Model Context ProtocolMCP)工具调用的多模型 AI 聊天应用。** 可与 QwenClaudeGemini OpenAI 对话,同时 RuFlo 会调用与 CLI 相同的 MCP 工具 —— 智能体编排、持久记忆、蜂群协调、代码审查、GitHub 操作 —— 全部直接在聊天中完成。无需安装,也无需 API 密钥即可试用。
| | What it is | Why it matters |
| | 是什么 | 为何重要 |
|---|------------|----------------|
| 🧠 | **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](https://github.com/ruvnet/RuVector/tree/main/examples/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 46+ 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 ~1.9x4.7x 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](https://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. |
| 🧠 | **任意模型,本地或远程** | 开箱即用 6 个精选前沿模型 —— Qwen 3.6 Max(默认)、Claude Sonnet 4.6Claude Haiku 4.5Gemini 2.5 ProGemini 2.5 FlashOpenAI —— 通过 OpenRouter 接入。也可添加自有模型:任意 OpenAI 兼容端点(vLLMOllamaLM StudioTogetherGroq、自托管)。 |
| 🦾 | **ruvLLM 自学习 AI** | 原生支持 [ruvLLM](https://github.com/ruvnet/RuVector/tree/main/examples/ruvLLM)(位于 `ruvnet/RuVector/examples/ruvLLM`)—— RuFlo 的自改进本地模型层。路由至 MicroLoRA 适配器,通过 SONA 从你的轨迹中学习,并保留在你的机器上。可与云端模型搭配使用,也可完全离线运行。 |
| 🛠️ | **约 210 个工具,随时可调用** | 5 个服务器组(CoreIntelligenceAgentsMemoryDevTools),外加 18 个工具库,完全在浏览器中运行 —— 支持离线。 |
| 🔌 | **自带 MCP 服务器** | 在聊天输入框中点击 **MCP (n)** 胶囊 → *Add Server*,粘贴任意 MCP 端点(HTTPSSE stdio)。你的工具会与 RuFlo 原生工具在同一并行执行流程中协同工作。在 `localhost:3000` 上运行本地 MCP 服务器即可直接使用。 |
| ⚡ | **工具并行执行** | 单次模型响应可同时触发 4–6+ 个工具。UI 以卡片形式展示,并带有 *Step 1 — 2 tools completed* 徽章,让你清楚看到实际执行了哪些操作。 |
| 💾 | **持久记忆** | *「记住我最喜欢的颜色是靛蓝」*,几周后再问 —— RuFlo 仍能回忆起来。由 AgentDB + HNSW 向量搜索支撑(在交叉点以上实测较暴力搜索约快 1.9x–4.7x,recall@10 ~0.99)。 |
| 📘 | **内置能力导览** | 点击侧边栏中的问号图标 —— 会打开「RuFlo Capabilities」模态框,展示完整工具列表、模型优势、架构与键盘快捷键。 |
| 🏠 | **可自托管** | Web UI Docker`ruflo/src/ruvocal/Dockerfile`)形式提供,内嵌 Mongo。可部署到自有 Cloud Run / Fly / Kubernetes / docker-compose。托管 [flo.ruv.io](https://flo.ruv.io/) 演示是一种选择;完全支持自行部署。 |
| 🚀 | **零安装即可试用** | 打开托管 URL,选择模型,输入问题。这就是全部上手流程。 |
**Try the hosted demo:** [https://flo.ruv.io/](https://flo.ruv.io/) — no account, no API key. **Run your own:** the source lives in [`ruflo/src/ruvocal/`](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](ruflo/docs/adr/ADR-033-RUVOCAL-WASM-MCP-INTEGRATION.md) for the architecture and [issue #1689](https://github.com/ruvnet/ruflo/issues/1689) for the roadmap.
**试用托管演示:** [https://flo.ruv.io/](https://flo.ruv.io/) — 无需账户,无需 API 密钥。**自行运行:** 源代码位于 [`ruflo/src/ruvocal/`](ruflo/src/ruvocal/),配有分阶段 Dockerfile`INCLUDE_DB=true` 在 MongoDB 中构建)以及用于 Google Cloud Run 的 `cloudbuild.yaml`。架构请参阅 [ADR-033](ruflo/docs/adr/ADR-033-RUVOCAL-WASM-MCP-INTEGRATION.md),路线图请参阅 [issue #1689](https://github.com/ruvnet/ruflo/issues/1689)
<p align="center">
<a href="https://goal.ruv.io/agents">
<img src="v3/docs/assets/goal.png" alt="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." width="100%" />
<img src="v3/docs/assets/goal.png" alt="goal.ruv.io/agents — RuFlo 面向自主 AI 智能体的目标导向行动规划(GOAP)UI。可视化目标分解、状态空间 A* 搜索、多智能体任务分配,以及实时智能体遥测。" width="100%" />
</a>
</p>
### Goal Planner UI — autonomous agents at [goal.ruv.io](https://goal.ruv.io/)
### 目标规划器 UI — [goal.ruv.io](https://goal.ruv.io/) 上的自主智能体
**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`](https://goal.ruv.io/agents).
**将高层目标转化为可执行的智能体计划。** `goal.ruv.io` RuFlo 托管的目标导向行动规划(GOAP)前端——用通俗英语描述一个预期结果,即可观看 RuFlo 将其分解为前置条件、动作以及贯穿状态空间的 A* 路径,然后将工作分派给 [`/agents`](https://goal.ruv.io/agents). 上的实时智能体。
| | What it is | Why it matters |
| | 它是什么 | 为何重要 |
|---|------------|----------------|
| 🎯 | **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](https://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](https://goal.ruv.io/), describe a goal, watch it run. Source lives in [`v3/goal_ui/`](v3/goal_ui/) — Vite + Supabase, self-hostable. |
| 🎯 | **通俗英语目标** | 输入 *"ship the auth refactor with tests and a PR"* — RuFlo 会提取成功标准、约束条件和隐式前置条件。无需 JSON,无需 DSL |
| 🧭 | **GOAP A\* 规划器** | 经典游戏 AI 规划移植到软件工程:通过带前置条件/效果的动作进行状态空间搜索,找出最短可行路径。状态变化时即时重新规划。 |
| 🤖 | **实时智能体仪表盘** | [goal.ruv.io/agents](https://goal.ruv.io/agents) 展示每个已派生的智能体——角色、当前步骤、内存命名空间、令牌预算、状态。点击进入可检查轨迹、终止失控 worker,或重新分配。 |
| 🌳 | **可视化计划树** | 目标渲染为可折叠的动作树,突出显示进度、受阻分支和回滚。可*确切*看到智能体为何选择某条路径——没有不透明的思维链。 |
| ♻️ | **自适应重新规划** | 当某个动作失败或新信息到达时,规划器从当前状态重新运行 A\*,而非从头开始。失败转化为学习,而非循环。 |
| 🧠 | **共享内存 + SONA** | 计划、轨迹和结果流入 AgentDB。未来计划通过 HNSW 检索过往解决方案——规划器随每次运行变得更智能。 |
| 🔗 | **接入 MCP 工具** | 每个动作节点映射到一个工具调用(RuFlo210 MCP 工具、你的自定义服务器或 shell)。规划器在依赖图允许的情况下并行调度它们。 |
| 🚀 | **零安装即可试用** | 打开 [goal.ruv.io](https://goal.ruv.io/), 描述一个目标,观察其运行。源代码位于 [`v3/goal_ui/`](v3/goal_ui/) — Vite + Supabase,可自托管。 |
**Try it:** [https://goal.ruv.io/](https://goal.ruv.io/) for goals · [https://goal.ruv.io/agents](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`.
**立即试用:** [https://goal.ruv.io/](https://goal.ruv.io/) 用于目标 · [https://goal.ruv.io/agents](https://goal.ruv.io/agents) 用于实时智能体。**自行运行:** 克隆 `goal` 分支并执行 `cd v3/goal_ui && npm install && npm run dev`
### Agent Federation — Slack for Agents
### 智能体联邦 — 智能体的 Slack
```
Your Agent --> [ Remove secrets ] --> [ Sign message ] --> [ Encrypted channel ]
@@ -276,29 +294,29 @@ Their Agent <-- [ Block attacks ] <-- [ Check identity ] <------+
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.
Slack 为团队提供了频道。联邦为智能体提供了同样的东西——**跨信任边界的共享工作空间**,不同机器、组织或云区域的智能体可以在此相互发现、证明身份并协作完成任务。
The difference: some channels are trusted, some aren't. [`@claude-flow/plugin-agent-federation`](https://github.com/ruvnet/ruflo/issues/1669) 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.
区别在于:有些频道受信任,有些则否。[`@claude-flow/plugin-agent-federation`](https://github.com/ruvnet/ruflo/issues/1669) 会自动处理这一点。你的智能体加入联邦,通过 mTLS + ed25519 完成验证,然后开始交换工作——任何数据离开你的节点前都会剥离 PII,每条消息均可审计。不受信任的智能体仍可在较低权限下参与:它们只能看到发现信息,而非你的内存。随着可靠性得到证明,信任等级会提升。若行为不当,会立即降级——无需人工介入。
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.
你无需配置握手或管理证书。你执行 `federation init``federation join`,智能体即可开始通信。协议负责身份,PII 管道负责数据安全,审计追踪负责合规。
> **📘 Full user guide:** [`docs/federation/`](./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`](./docs/federation/phase7-mesh-bringup.md).
> **📘 完整用户指南:** [`docs/federation/`](./docs/federation/) — 设置、MCP 工具、信任等级、熔断器,以及将数据包层可达性与联邦信任绑定的(可选)WireGuard 网状层。ADR-111 深度解读见 [`docs/federation/phase7-mesh-bringup.md`](./docs/federation/phase7-mesh-bringup.md)
<details>
<summary><strong>Federation capabilities</strong></summary>
<summary><strong>联邦能力</strong></summary>
| | Capability | How it works |
| | 能力 | 工作原理 |
|---|---|---|
| 🔒 | **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. |
| 🔒 | **零信任联邦** | 远程智能体初始为不受信任。身份通过 mTLS + ed25519 质询-响应验证。无 API 密钥,无共享密钥。 |
| 🛡️ | **PII 门控数据流** | 14 类检测管道扫描每条出站消息。按信任等级策略:BLOCKREDACTHASH PASS。自适应校准降低误报。 |
| 📊 | **行为信任评分** | 公式(`0.4×success + 0.2×uptime + 0.2×threat + 0.2×integrity`)持续评估对等节点。升级需要历史记录;降级即时生效。 |
| 📋 | **内置合规** | HIPAASOC2GDPR 审计追踪作为合规模式。每次联邦事件产生可通过 HNSW 检索的结构化记录。 |
| 🤝 | **9 MCP 工具 + 10 CLI 命令** | 完整生命周期:`federation_init``federation_send``federation_trust``federation_audit` 等。 |
</details>
<details>
<summary><strong>Example: two teams sharing fraud signals without sharing customer data</strong></summary>
<summary><strong>示例:两个团队共享欺诈信号而不共享客户数据</strong></summary>
```bash
# Team A: initialize federation and generate keypair
@@ -317,7 +335,7 @@ npx claude-flow@latest federation status
</details>
See [issue #1669](https://github.com/ruvnet/ruflo/issues/1669) for the complete architecture, trust model, and implementation roadmap.
请参阅 [issue #1669](https://github.com/ruvnet/ruflo/issues/1669) 了解完整架构、信任模型和实施路线图。
```bash
# Claude Code plugin
@@ -328,23 +346,23 @@ npx claude-flow@latest plugins install @claude-flow/plugin-agent-federation
```
<details>
<summary><strong>Claude Code: With vs Without Ruflo</strong></summary>
<summary><strong>Claude Code:有无 Ruflo 的对比</strong></summary>
| Capability | Claude Code Alone | + Ruflo |
| 能力 | 仅 Claude Code | + 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 |
| 智能体协作 | 孤立,无共享上下文 | 具有共享内存与共识的蜂群 |
| 协调 | 手动编排 | Queen 主导的层级(RaftByzantineGossip |
| 内存 | 仅会话 | 亚毫秒级检索的 HNSW 向量内存 |
| 学习 | 静态行为 | 带模式匹配的 SONA 自学习 |
| 任务路由 | 由你决定 | 智能路由(89% 准确率) |
| 背景 Workers | | 12 个自动触发的 worker |
| LLM 提供商 | Anthropic | 5 个提供商,带故障转移 |
| 安全 | 标准 | 经 CVE 加固的 AIDefence |
</details>
<details>
<summary><strong>Architecture overview</strong></summary>
<summary><strong>架构概览</strong></summary>
```
User --> Claude Code / CLI
@@ -370,50 +388,48 @@ User --> Claude Code / CLI
(Claude, GPT, Gemini, Cohere, Ollama)
```
</details>
---
## 文档
面向四类读者的四份文档:
| 文档 | 何时阅读 |
|------|----------|
| **[状态](docs/STATUS.md)** | 查看当前可用的功能——能力计数、测试基线、近期修复、下一步计划。这是*就绪了吗*文档。 |
| **[用户指南](docs/USERGUIDE.md)** | 日常参考——每条命令、每个配置项、每个插件。这是*怎么做*文档。 |
| **[元测试工具指南](docs/metaharness-user-guide.md)** | 如何评估你的 Agent 设置、扫描工具配置的安全性、检测运行间的变更、以及将项目抽离为独立的 Agent 工具包。这是*审计我的设置*文档。 |
| **[基准测试](https://gist.github.com/ruvnet/298f8c668c8859b369f91734a0e9cbbe)**)** | 在 darwin-arm64 + linux-x64 平台上与 LangGraph / AutoGen / CrewAI 的 v3.8.0 SOTA 矩阵对比。ruflo 在冷启动、单轮对话、RSS 方面以 1.3×–1953× 的优势胜出。这是*它快吗*文档。 |
| **[验证](verification.md)** | 密码学证明你安装的字节与签名见证一致——`ruflo verify`。这是*信任但要验证*文档。 |
| **[团队网关清单](docs/TEAM-GATEWAY-CHECKLIST.md)** | 合并前检查、双模式交接、内存命名空间共享、每次合并的见证清单条目。这是*更安全的团队工作流*文档。 |
基准测试内部(用于复现):[`sota-workload-spec.md`](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/sota-workload-spec.md)) · [`SOTA-PROGRESS.md`](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/SOTA-PROGRESS.md)) · [原始矩阵 JSONdarwin](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/sota-matrix.json)) · [linux](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/sota-matrix-linux.json))
用户指南章节索引:
| 章节 | 主题 |
|------|------|
| [快速开始](docs/USERGUIDE.md#quick-start) | 安装、前置条件、安装配置 |
| [核心功能](docs/USERGUIDE.md#-core-features) | MCP 工具、Agent、记忆、神经学习 |
| [智能与学习](docs/USERGUIDE.md#-intelligence--learning) | 钩子、工作器、SONA、模型路由 |
| [集群与协调](docs/USERGUIDE.md#-swarm--coordination) | 拓扑、共识、群体智慧 |
| [安全](docs/USERGUIDE.md#%EF%B8%8F-security) | AIDefence、CVE 修复、验证 |
| [生态](docs/USERGUIDE.md#-ecosystem--integrations) | RuVector、agentic-flow、Flow Nexus |
| [配置](docs/USERGUIDE.md#%EF%B8%8F-configuration--reference) | 环境变量、配置模式 |
| [插件市场](https://ruvnet.github.io/ruflo)) | 浏览和安装插件 |
---
## Documentation
## 支持
Four docs for four audiences:
| 资源 | 链接 |
|------|------|
| 文档 | [用户指南](docs/USERGUIDE.md) |
| 问题与缺陷 | [GitHub Issues](https://github.com/ruvnet/claude-flow/issues)) |
| 企业版 | [ruv.io](https://ruv.io)) |
| 社区 | [Agentics Foundation Discord](https://discord.com/invite/dfxmpwkG2D)) |
| 技术支持 | [Cognitum.one](https://cognitum.one)) |
| Doc | When to read it |
|-----|-----------------|
| **[Status](docs/STATUS.md)** | See what currently works — capability counts, test baselines, recent fixes, what's next. The *is-it-ready* doc. |
| **[User Guide](docs/USERGUIDE.md)** | Daily reference — every command, every config flag, every plugin. The *how-do-I* doc. |
| **[MetaHarness Guide](docs/metaharness-user-guide.md)** | 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](https://gist.github.com/ruvnet/298f8c668c8859b369f91734a0e9cbbe)** | 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](verification.md)** | Cryptographically prove your installed bytes match the signed witness — `ruflo verify`. The *trust-but-verify* doc. |
| **[Team Gateway Checklist](docs/TEAM-GATEWAY-CHECKLIST.md)** | Before-merge gates, dual-mode handoff, memory namespace sharing, and witness manifest entry per merge. The *safer-team-workflows* doc. |
## 许可证
Benchmark internals (for reproduction): [`sota-workload-spec.md`](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/sota-workload-spec.md) · [`SOTA-PROGRESS.md`](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/SOTA-PROGRESS.md) · [raw matrix JSON: darwin](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/sota-matrix.json) · [linux](https://github.com/ruvnet/ruflo/blob/perf/sota-comparator-benchmarks/docs/benchmarks/sota-matrix-linux.json)
User Guide section index:
| Section | Topics |
|---------|--------|
| [Quick Start](docs/USERGUIDE.md#quick-start) | Installation, prerequisites, install profiles |
| [Core Features](docs/USERGUIDE.md#-core-features) | MCP tools, agents, memory, neural learning |
| [Intelligence & Learning](docs/USERGUIDE.md#-intelligence--learning) | Hooks, workers, SONA, model routing |
| [Swarm & Coordination](docs/USERGUIDE.md#-swarm--coordination) | Topologies, consensus, hive mind |
| [Security](docs/USERGUIDE.md#%EF%B8%8F-security) | AIDefence, CVE remediation, validation |
| [Ecosystem](docs/USERGUIDE.md#-ecosystem--integrations) | RuVector, agentic-flow, Flow Nexus |
| [Configuration](docs/USERGUIDE.md#%EF%B8%8F-configuration--reference) | Environment variables, config schema |
| [Plugin Marketplace](https://ruvnet.github.io/ruflo) | Browse and install plugins |
---
## Support
| Resource | Link |
|----------|------|
| Documentation | [User Guide](docs/USERGUIDE.md) |
| Issues & Bugs | [GitHub Issues](https://github.com/ruvnet/claude-flow/issues) |
| Enterprise | [ruv.io](https://ruv.io) |
| Community | [Agentics Foundation Discord](https://discord.com/invite/dfxmpwkG2D) |
| Powered by | [Cognitum.one](https://cognitum.one) |
## License
MIT - [RuvNet](https://github.com/ruvnet)
MIT - [RuvNet](https://github.com/ruvnet))