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Agent Skill · 研究检索

metals-desk-os(金属办公桌操作系统)

metals-desk-os 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。

metals-desk-os 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 3,683。

总安装 41,136周安装 1,767GitHub Stars 2下载 14,419核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:metals-desk-os(金属办公桌操作系统)
来源仓库:https://github.com/cfilipemt/metals-desk-os
安装命令:
openclaw skills install metals-desk-os
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 metals-desk-os

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

XAU/USD 和 XAG/USD 机构桌面级全自动交易操作系统。事件驱动、风险优先的多引擎架构,在 OpenClaw 的交易代理内部作为连续分析和执行管道运行。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install metals-desk-os;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

metals-desk-os 怎么安装?

在终端执行 openclaw skills install metals-desk-os。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

metals-desk-os 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

metals-desk-os 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

metals-desk-os 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

metals-desk-os 用的人多吗?

公开数据是累计安装 41,136 次,近一周安装 1,767 次,下载 14,419 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

metals-desk-os 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
metals-desk-os

金属办公桌操作系统 · 本页

41,1362调用外部服务MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
metals-desk-os
description
Institutional Desk-Level Fully Automated Trading OS for XAU/USD and XAG/USD. Event-driven, risk-first, multi-engine architecture that runs as a continuous analysis and execution pipeline inside OpenClaw's trader agent.

Metals Desk OS

An institutional-grade metals trading operating system for gold (XAU/USD) and silver (XAG/USD). This skill transforms the OpenClaw trader agent into a full prop-desk assistant with real-time analysis, automated execution, risk management, and performance tracking.

When to Use This Skill

Use this skill when:

  • Analyzing gold or silver market structure (ICT/SMC methodology)
  • Generating trade signals with full entry/SL/TP plans
  • Running automated or semi-automated trade execution via MT5
  • Monitoring real-time risk, drawdown, and position management
  • Tracking trading performance (win rate, expectancy, Sharpe, drawdown)
  • Getting session-aware, macro-aware trading intelligence

Architecture Overview

The system runs as a continuous event-driven pipeline:

PRICE FEED → SESSION ENGINE → STRUCTURE ENGINE → LIQUIDITY ENGINE →
MACRO ENGINE → BIAS ENGINE → VOLATILITY ENGINE → RISK ENGINE →
EXECUTION ENGINE → BROKER → PERFORMANCE ENGINE → DASHBOARD → ALERTS

All engines communicate through a central Event Bus (EventEmitter pattern). Every event is logged and can be monitored in real-time via WebSocket.

Core Engines

EnginePurposeKey Outputs
Structure EngineDetects HH/HL/LH/LL, BOS, CHoCH, FVG, Order BlocksMarket structure, trend direction, structural shifts
Liquidity EngineFinds equal highs/lows, stop clusters, session levels, sweepsLiquidity pools, sweep confirmations
Bias EngineMulti-timeframe directional bias with conviction scoringHTF bias, intraday bias, conviction 0-100, alignment score
Macro EngineTracks DXY, US10Y yields, risk sentiment, news proximitymacro_bias (bullish/bearish/neutral gold), macro_risk level
Volatility EngineATR calculation, spike detection, regime classificationATR, volatility regime (low/normal/high/extreme)
Risk EnginePosition sizing, drawdown monitoring, halt triggersLot size, risk %, pass/fail gate for every trade
Execution EngineCombines all engines to generate trade signalsFull trade plan: entry, SL, TP1/TP2/TP3, position size
Performance EngineWin rate, expectancy, Sharpe, monthly breakdownComprehensive performance metrics and trade log

System Modes

ModeNameBehavior
1AdvisoryFull analysis pipeline runs, signals logged, no execution
2Semi-AutomatedSignals generated + automatic TP/SL/trailing management
3Fully-AutomatedAutonomous execution: signal → order → manage → close
4Risk-OffMonitoring only, no signals generated

Set the mode in data/state.json or via WebSocket command. Always start in Mode 1 for validation.

Risk Rules (Non-Negotiable)

These hard rules are enforced by the Risk Engine and cannot be overridden:

  • Max 2% risk per trade — Position sized via (Balance × Risk%) / StopDistance
  • Max 5% daily exposure — Cumulative open risk capped
  • 3 consecutive losses → halt trading for the session
  • Volatility spike → reduce size 50% (extreme = 75% reduction)
  • Spread widening → block entry (symbol-specific thresholds)
  • High-impact news < 20 minutes → block all entries
  • Equity drawdown > 8% → halt trading until manual resume
  • API error on order → cancel, do NOT retry
  • Broker disconnect → close all positions immediately

Trade Management Protocol

  1. TP1 at 1.5R → Partial close 40% → Move SL to break-even
  2. TP2 at 2.5R → Partial close 30% → Trail SL under structure
  3. TP3 at 4.0R → Close remaining 30% → Log trade to performance

Entry Conditions (All Must Pass)

For the Execution Engine to generate a signal, every condition must be true:

  1. Bias conviction ≥ 65/100
  2. Alignment score ≥ 0.6
  3. Liquidity sweep confirmed (aligned with direction)
  4. BOS or CHoCH confirmed in trade direction
  5. Session = London or New York (kill zones preferred)
  6. Macro risk = low or medium
  7. Spread within threshold
  8. No news block active
  9. Daily loss below 80% of limit
  10. Consecutive losses < 3

File Structure

metals-desk-os/
├── SKILL.md                    # This file
├── index.js                    # Main orchestrator & entry point
├── package.json                # npm dependencies
├── skill.json                  # OpenClaw registration manifest
├── manifest.json               # Runtime configuration
├── core/                       # 8 trading engines
│   ├── structure-engine.js     # HH/HL/LH/LL, BOS, CHoCH, FVG, OB
│   ├── liquidity-engine.js     # Pools, sweeps, equal levels
│   ├── bias-engine.js          # MTF bias, conviction scoring
│   ├── macro-engine.js         # DXY, yields, sentiment, news
│   ├── volatility-engine.js    # ATR, regime, spikes
│   ├── risk-engine.js          # Position sizing, halts
│   ├── execution-engine.js     # Signal generation
│   └── performance-engine.js   # Metrics tracking
├── automation/                 # System automation layer
│   ├── event-bus.js            # Central event system
│   ├── price-feed.js           # MT5/MetaAPI price data
│   ├── session-engine.js       # London/NY/Asian sessions
│   ├── scheduler.js            # Cron tasks
│   └── news-monitor.js         # Economic calendar
├── broker/                     # MT5 broker integration
│   ├── mt5-connector.js        # Order execution via MetaAPI
│   ├── risk-guard.js           # Position monitoring & trailing
│   └── order-manager.js        # Order lifecycle management
├── dashboard/                  # Real-time monitoring
│   ├── websocket-feed.js       # WebSocket broadcaster (port 3078)
│   ├── desk-dashboard.json     # Widget layout config
│   └── metrics.json            # Metrics template
├── alerts/                     # Notification channels
│   ├── whatsapp-alert.js       # WhatsApp Business API
│   ├── telegram-alert.js       # Telegram Bot
│   └── risk-alert.js           # Centralized dispatcher
├── data/                       # Persistent state files
│   ├── state.json              # System mode & connections
│   ├── trade-log.json          # Trade history
│   ├── performance.json        # Performance metrics
│   └── bias-memory.json        # Bias state persistence
└── prompts/                    # AI agent prompts
    ├── system.txt              # Main system prompt
    ├── intraday.txt            # Intraday trading protocol
    ├── swing.txt               # Swing trading protocol
    └── execution.txt           # Execution protocol

Installation

Step 1: Deploy to OpenClaw

cp -r metals-desk-os/ ~/.openclaw/agents/trader/agent/metals-desk-os/
cd ~/.openclaw/agents/trader/agent/metals-desk-os/

Step 2: Install Dependencies

npm install

Step 3: Configure Environment

Create a .env file in the skill root with the following variables:

# MetaAPI / MT5 Connection
METAAPI_TOKEN=your_metaapi_token_here
MT5_ACCOUNT_ID=your_mt5_account_id_here

# WhatsApp Business API (optional)
WHATSAPP_API_URL=https://graph.facebook.com/v18.0/YOUR_PHONE_NUMBER_ID/messages
WHATSAPP_TOKEN=your_whatsapp_token_here
WHATSAPP_PHONE=your_phone_number_with_country_code

# Telegram Bot (optional)
TELEGRAM_BOT_TOKEN=your_telegram_bot_token_here
TELEGRAM_CHAT_ID=your_telegram_chat_id_here

# News API (optional)
NEWS_API_KEY=

# AI Keys (optional, for enhanced analysis)
OPENROUTER_API_KEY=
ANTHROPIC_API_KEY=

MetaAPI: Sign up at https://metaapi.cloud and connect your Fusion Markets MT5 account. Telegram: Create a bot via @BotFather, get chat ID from @userinfobot. WhatsApp: Configure via Meta Business API dashboard.

Step 4: Set Initial Mode

Edit data/state.json and set "mode": 1 (Advisory) to start safely.

Step 5: Start

# Direct
node index.js

# Or with PM2 for production
pm2 start index.js --name metals-desk-os
pm2 save
pm2 startup

Dashboard

Connect any WebSocket client to ws://localhost:3078 to receive real-time JSON payloads containing:

  • Live prices and spread statistics
  • HTF and intraday bias with conviction scores
  • Active positions with live P&L and R:R
  • Liquidity map (equal highs/lows, sweep markers)
  • Macro panel (DXY, yields, news countdown)
  • Performance metrics (win rate, expectancy, drawdown, Sharpe)
  • Risk status (halt state, daily P&L, exposure)
  • Event log (all system events)

Alert Formats

Trade opened:

TRADE OPENED
Pair: XAUUSD
Direction: Long
Entry: 5024.50
SL: 5010.00
TP1: 5046.25
Risk: 1.5%
Session: London
Conviction: 82/100

Risk halt:

RISK HALT ACTIVATED
Reason: 3 consecutive losses
Trading paused for session

Key Events

The Event Bus broadcasts these events that external systems can subscribe to:

  • price.update — New price tick with candle data
  • structure.shift — BOS or CHoCH detected
  • liquidity.sweep — Liquidity pool swept
  • bias.update — Bias recalculated
  • bias.flip — HTF bias direction changed
  • execution.signal — Valid trade signal generated
  • risk.halt / risk.resume — Trading halted or resumed
  • order.filled / order.closed — Order lifecycle events
  • performance.update — New trade recorded to performance
  • macro.news.block — News event blocking execution

Validation Checklist

Before moving beyond Mode 1:

  1. Price feed produces ticks (live or simulated)
  2. Structure engine detects swing points and BOS/CHoCH
  3. Liquidity engine identifies pools and sweeps
  4. Bias engine produces conviction scores > 0
  5. Session engine correctly identifies current session
  6. Risk engine validates and rejects test scenarios
  7. Execution engine generates signals with full entry plans
  8. Alerts arrive on configured channels
  9. WebSocket feed broadcasts state updates

Once all pass, move to Mode 2 (Semi-Auto) to test position management, then Mode 3 (Full-Auto) for live execution.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

OpenClaw

92.98%
按下载量换算13,407

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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