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marl-middleware马尔中间件

Agent Skill

marl-middleware 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

11,478

周安装

488

GitHub Stars

6

下载量

4,021
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:marl-middleware(马尔中间件)
来源仓库:https://github.com/cutechicken99/marl-middleware
安装命令:
openclaw skills install marl-middleware
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install marl-middleware

简介

MARL Middleware 是多阶段多代理推理中间件,可减少 LLM 幻觉达70%以上。

  • 适用于科研、制药、基因组等高风险领域,提升结论可信度与决策安全性。
  • 通过 clawhub 安装后,在 OpenClaw 中调用,需配置多个涌现引擎协同工作。
  • 使用前应验证各引擎适用场景,避免误用导致推理偏差放大。
  • 适合研究检索类 Agent 嵌入至复杂问题求解系统,增强事实核查与逻辑一致性。

SKILL.md

name
marl-middleware
description
Multi-stage multi-agent reasoning middleware that reduces LLM hallucination by 70%+. 9 specialized emergence engines for invention, creative, pharma, genomics, chemistry, ecology, law, recipe, and document generation.
tags
[reasoning, hallucination, multi-agent, metacognition, emergence, middleware]
metadata
clawdbot
config
requiredEnv
[]
example
|
llm
baseURL
http://localhost:8080/v1
model
gpt-5.4::create

MARL Enhance — Brain Upgrade for Your Agent

The 3rd approach after fine-tuning & RAG. MARL restructures how LLMs reason at runtime — not their weights. One line to integrate, 70%+ hallucination reduction, 9 domain-specific emergence engines.

![PyPI](https://pypi.org/project/marl-middleware/) ![GitHub](https://github.com/Vidraft/MARL) ![Demo](https://huggingface.co/spaces/VIDraft/MARL) ![FINAL Bench](https://huggingface.co/spaces/FINAL-Bench/Leaderboard)

What It Does

Before MARL: Your agent calls the LLM once → gets an answer (might hallucinate).

After MARL: Your agent calls MARL → MARL runs a multi-stage expert pipeline → hypothesis, solving, auditing, adversarial verification, synthesis → returns a deeply verified answer.

Your Agent → MARL → Multi-stage Pipeline → Any LLM → Verified Answer

Results: 70%+ hallucination reduction · 94.8% of improvement from self-correction · Verified on FINAL Bench (HuggingFace Global Top 5 dataset).

Setup

Option A: Docker (Recommended — all platforms)

docker run -p 8080:8080 vidraft/marl

Option B: pip (Linux x86_64)

pip install marl-middleware
python -m marl serve --port 8080

Option C: HuggingFace Space (No install — try instantly)

Use https://huggingface.co/spaces/VIDraft/MARL directly in your browser.

Connect to OpenClaw

Set your config.json:

{
  "llm": {
    "baseURL": "http://localhost:8080/v1",
    "model": "gpt-5.4"
  }
}

That's it. Every LLM call now passes through MARL's multi-stage reasoning pipeline.

9 Emergence Modes

Switch modes by appending ::mode to any model name:

model valueEngineWhat it does
gpt-5.4🔬 InsightDefault — fact-check, strategy, deep analysis
gpt-5.4::invent🔧 InventPatent-level invention via TRIZ + bio-inspired + contradiction resolution
gpt-5.4::create✨ CreateCliché inversion, paradox, genre fusion, sensory collision
gpt-5.4::recipe🍳 RecipeCulinary emergence with taste chemistry validation
gpt-5.4::pharma💊 PharmaDrug repositioning, mechanism crossing, multi-target design
gpt-5.4::genomics🧬 GenomicsPathway crosstalk, synthetic lethality, phenotype bridging
gpt-5.4::chemistry🧪 ChemistryContradictory properties, biomimicry, waste-to-value
gpt-5.4::ecology🌍 EcologyConservation transfer, threat inversion, service stacking
gpt-5.4::law⚖️ LawCross-jurisdiction transplant, tech-law collision resolution
gpt-5.4::document📄 DocumentMetacognitive report and document generation

Replace gpt-5.4 with any model — Claude, Gemini, DeepSeek, Llama, etc.

Example: Switch to Pharma mode

{
  "llm": {
    "baseURL": "http://localhost:8080/v1",
    "model": "gpt-5.4::pharma"
  }
}

Then chat: *"Find drug repositioning candidates for Alzheimer's using immune checkpoint mechanisms"*

Example: Creative ideation

{
  "llm": {
    "model": "claude-sonnet::create"
  }
}

Then chat: *"Generate 10 movie loglines that have never existed before"*

How It Works

┌─ OpenClaw ────────────────────────────────────┐
│  "Analyze this complex question"               │
└──────────────┬─────────────────────────────────┘
               │ HTTP (OpenAI API format)
               ▼
┌─ MARL Middleware ─────────────────────────────┐
│  Multi-stage Multi-agent Reasoning Pipeline    │
│  9 Emergence Engines · 70%+ Hallucination ↓   │
└──────────────┬─────────────────────────────────┘
               │ API calls to your chosen LLM
               ▼
┌─ Any LLM ─────────────────────────────────────┐
│  GPT-5.4 · Claude · Gemini · DeepSeek · Llama │
└────────────────────────────────────────────────┘

MARL works with every LLM that supports OpenAI API format. It runs locally on your machine — your data never leaves your infrastructure.

Works With Any LLM

  • OpenAI (GPT-5.4, GPT-5.2, GPT-4.1, o4-mini)
  • Anthropic (Claude Opus 4.6, Sonnet 4.6)
  • Google (Gemini 3.1 Pro, Gemini 3 Flash)
  • DeepSeek (V3, R1, R2)
  • xAI (Grok-4, Grok-3)
  • Groq (gpt-oss-120b, Llama 4 — free)
  • Ollama (any local model)
  • Any OpenAI-compatible endpoint

Links

About

Built by VIDRAFT (Seoul AI Hub). MARL's core engine is delivered as compiled binaries to protect proprietary technology. Interface code is open for integration.

Apache 2.0 · Contact: arxivgpt@gmail.com

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

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按下载量换算2,848

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

操作浏览器

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安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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