An institutional-grade trading operating system for gold and silver, providing automated analysis and execution within the Openclaw agent environment.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install metals-desk-os
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install metals-desk-os using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Metals Desk OS is a sophisticated trading framework designed for institutional-level precious metals trading. It transforms standard agents into professional-grade trading desks by integrating complex ICT/SMC methodologies with real-time risk management and multi-engine analysis. By leveraging the power of Openclaw Skills, developers can deploy a continuous analysis pipeline that handles everything from market structure detection to automated execution via MT5.
This skill operates as an event-driven operating system, ensuring that every trade signal is backed by multi-timeframe conviction and macro-economic alignment. It is specifically optimized for XAU/USD (Gold) and XAG/USD (Silver), providing a specialized toolkit for traders who require high-precision automation and institutional-grade performance tracking within their Openclaw Skills ecosystem.
cp -r metals-desk-os/ ~/.openclaw/agents/trader/agent/metals-desk-os/
cd ~/.openclaw/agents/trader/agent/metals-desk-os/
npm install
Create a .env file in the skill root with your MetaAPI token, MT5 Account ID, and optional notification keys (Telegram/WhatsApp).
Edit data/state.json and set "mode": 1 (Advisory) to begin safe validation.
node index.js
| Component | Storage File | Metadata Description |
|---|---|---|
| System State | data/state.json |
Persists current operational mode and connection status. |
| Trade History | data/trade-log.json |
Stores comprehensive logs of every entry, exit, and R:R outcome. |
| Performance | data/performance.json |
Tracks win rate, Sharpe ratio, and drawdown metrics over time. |
| Bias Memory | data/bias-memory.json |
Maintains multi-timeframe bias and conviction scores to ensure continuity. |
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