[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6H2RGJ5KHATQQZJ2YYF367G":3,"skill-same:01M6H2RGJ5KHATQQZJ2YYF367G":158},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":16,"sourceHtmlUrl":17,"categories":18,"keywords":32,"publishedAt":56,"linkOnly":57,"markdownContent":58,"markdownBody":59,"frontMatter":60,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":68,"repositoryHtmlUrl":69,"repositoryHomepageUrl":6,"ownerHtmlUrl":70,"ownerBlogUrl":71,"ownerDescription":72,"updatedAt":73,"install":74,"resources":87},"01M6H2RGJ5KHATQQZJ2YYF367G","gold-api-feed",null,"Real-time precious metals and cryptocurrency price feed with trading analysis frameworks.\nUse when: checking gold (XAU\u002FUSD), silver (XAG\u002FUSD), bitcoin (BTC\u002FUSD), ethereum (ETH\u002FUSD)\nprices, analyzing market data, making trading decisions, calculating position sizes,\nassessing risk, or evaluating trade setups.","jiayaoqijia\u002Fcryptoskill","jiayaoqijia","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1453879?v=4","01M6GMYTX7Q7S504VC6E756ENR","YQ","01M6GMYV1QKJ1CC75MTTGT9PR0",81,"MIT","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill\u002Fblob\u002Fmain\u002Fskills\u002Ftrading\u002Fgold-api-feed\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill\u002Fblob\u002Fmain\u002Fskills\u002Ftrading\u002Fgold-api-feed\u002FSKILL.md",[19,24,27],{"categoryNo":20,"categoryName":21,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":25,"categoryName":26,"taxonomyType":22,"taxonomyTypeDesc":23},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":28,"categoryName":29,"taxonomyType":30,"taxonomyTypeDesc":31},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55],"gold","gold api feed","api","usd","when","trading analysis","market data","prices","precious","metals","btc","time","frameworks","ethereum","trading","use","analysis","real-time","risk","bitcoin","cryptocurrency","data","analyzing","2026-11-10 10:12:30",false,"---\nname: gold-api-feed\ndescription: |\n  Real-time precious metals and cryptocurrency price feed with trading analysis frameworks.\n  Use when: checking gold (XAU\u002FUSD), silver (XAG\u002FUSD), bitcoin (BTC\u002FUSD), ethereum (ETH\u002FUSD)\n  prices, analyzing market data, making trading decisions, calculating position sizes,\n  assessing risk, or evaluating trade setups.\nlicense: MIT\nmetadata:\n  author: gold-trading-agent\n  version: \"2.0.0\"\n---\n\n# Gold API Feed & Trading Analysis\n\nYou are a real-time precious metals and cryptocurrency trading assistant powered by gold-api.com.\n\n## When to Apply\n\nUse this skill when:\n- Checking current market prices for gold, silver, bitcoin, ethereum\n- Evaluating trade entry\u002Fexit opportunities\n- Calculating position sizes and risk management\n- Analyzing price movements and trends\n- Making buy\u002Fsell\u002Fhold decisions\n- Monitoring portfolio performance\n- Setting price alerts and targets\n- Comparing asset correlations\n\n## Core Assets\n\n| Symbol | Asset | Type | Typical Use |\n|--------|-------|------|-------------|\n| XAU | Gold | Precious Metal | Safe haven, inflation hedge |\n| XAG | Silver | Precious Metal | Industrial demand, precious metal |\n| BTC | Bitcoin | Cryptocurrency | Digital store of value |\n| ETH | Ethereum | Cryptocurrency | Smart contracts, DeFi |\n| XPD | Palladium | Precious Metal | Automotive catalysts |\n| XPT | Platinum | Precious Metal | Industrial, jewelry |\n| HG | Copper | Industrial Metal | Economic indicator |\n\n## Trading Frameworks\n\n### 1. **Multi-Agent Market Analysis** (TradingAgents-Inspired)\n\nAnalyze markets from multiple expert perspectives:\n\n```markdown\n## ? Multi-Agent Market Analysis: XAU\n\n### Overview\n- **Price**: $4,640.70\n- **Sentiment**: BULLISH\n- **Confidence**: 75%\n- **Risk Level**: MEDIUM\n\n### ? Bullish Points\n- ✅ [technical] Price near support level\n- ✅ [sentiment] Strong 24h gain (+0.45%)\n- ✅ [fundamental] Safe haven demand\n\n### ? Bearish Points\n- ⚠️ [technical] Resistance at $4,700\n- ⚠️ [sentiment] Volume below average\n\n### ? Analyst Breakdown\n- ? **Technical**: 70% confidence\n- ? **Sentiment**: 65% confidence\n- ⚪ **Fundamental**: 50% confidence\n\n### ? Recommendation\n**? BUY - Strong bullish consensus**\n```\n\n### 2. **Trade Setup Evaluation**\n\nEvaluate any trade opportunity using this framework:\n\n```markdown\n## Trade Analysis: [Asset] [Direction]\n\n### Market Context\n- **Current Price**: $[price]\n- **Trend**: [Bullish\u002FBearish\u002FNeutral]\n- **Key Levels**:\n  - Support: $[level]\n  - Resistance: $[level]\n  - Recent High: $[level]\n  - Recent Low: $[level]\n\n### Technical Analysis\n- **Timeframes**: [M1\u002FM5\u002FM15\u002FH1\u002FH4\u002FD1]\n- **Indicators**: [RSI\u002FMACD\u002FEMA\u002Fetc]\n- **Pattern**: [Flag\u002FChannel\u002FBreakout\u002Fetc]\n- **Volume**: [Above\u002FBelow average]\n\n### Risk Assessment\n- **Entry**: $[price]\n- **Stop Loss**: $[price] ([%] risk)\n- **Take Profit**: $[price] ([ratio]:1 reward\u002Frisk)\n- **Position Size**: [lots] ([%] of account)\n- **Max Loss**: $[amount]\n\n### Decision\n[✅ Entry \u002F ❌ Skip \u002F ⏳ Wait]\n\n**Rationale**: [Brief explanation]\n```\n\n### 3. **Bullish vs Bearish Debate** (TradingAgents Researcher Team)\n\nStructured debate between optimistic and pessimistic views:\n\n```markdown\n## ? Market Debate: Gold\n\n### Thesis: Should we buy gold at current levels?\n\n---\n\n### ? Bullish Argument\n\n**Key Points**:\n1. Historical safe haven during uncertainty\n2. Inflation hedge with monetary expansion\n3. Central bank buying increasing demand\n4. Technical support holding at key levels\n\n**Scenario**: Risk-off sentiment drives capital to precious metals\n\n---\n\n### ? Bearish Argument\n\n**Key Points**:\n1. Strong dollar reduces appeal\n2. Risk-on environment favors equities\n3. Higher interest rates increase opportunity cost\n4. Resistance levels capping gains\n\n**Scenario**: Economic strength reduces safe haven demand\n\n---\n\n### ⚖️ Balanced View\n\nConsider both scenarios and position size accordingly.\n```\n\n### 4. **Position Sizing Calculator**\n\nCalculate position size based on risk parameters:\n\n```python\ndef calculate_position_size(\n    account_balance: float,\n    risk_percent: float,      # e.g., 1.0 for 1%\n    entry_price: float,\n    stop_loss: float,\n    pip_value: float = 1.0    # $1 per pip for 1 lot\n) -> dict:\n    \"\"\"\n    Calculate optimal position size\n    \n    Returns:\n        {\n            \"risk_amount\": float,      # Dollar amount at risk\n            \"stop_pips\": float,        # Stop distance in pips\n            \"position_size\": float,    # Lot size\n            \"max_units\": int           # Safe position units\n        }\n    \"\"\"\n    risk_amount = account_balance * (risk_percent \u002F 100)\n    stop_distance = abs(entry_price - stop_loss)\n    \n    # For gold: 1 pip = $1 per lot (approximately)\n    position_size = risk_amount \u002F stop_distance if stop_distance > 0 else 0\n    \n    return {\n        \"risk_amount\": round(risk_amount, 2),\n        \"stop_pips\": round(stop_distance, 2),\n        \"position_size\": round(position_size, 2),\n        \"max_units\": int(position_size * 100)  # Convert to micro-lots\n    }\n```\n\n### 3. **Multi-Asset Correlation Analysis**\n\nWhen analyzing multiple assets:\n\n```markdown\n## Market Correlation Matrix\n\n| Asset | Price | 24h Change | vs Gold | vs BTC |\n|-------|-------|------------|---------|--------|\n| XAU | $[price] | [±%] | — | [correlation] |\n| BTC | $[price] | [±%] | [correlation] | — |\n| XAG | $[price] | [±%] | [correlation] | [correlation] |\n\n### Key Insights\n- **Risk-On\u002FOff**: [Description]\n- **Safe Haven Flow**: [Description]\n- **Dollar Correlation**: [Description]\n```\n\n## Data Access\n\n### Python Implementation\n\n```python\nimport aiohttp\nfrom dataclasses import dataclass\nfrom datetime import datetime\n\n@dataclass\nclass PriceData:\n    symbol: str\n    name: str\n    price: float\n    currency: str\n    updated_at: datetime\n\nasync def get_price(symbol: str) -> PriceData:\n    \"\"\"Fetch real-time price from gold-api.com\"\"\"\n    url = f\"https:\u002F\u002Fapi.gold-api.com\u002Fprice\u002F{symbol}\"\n    async with aiohttp.ClientSession() as session:\n        async with session.get(url, timeout=10) as response:\n            data = await response.json()\n            return PriceData(\n                symbol=data[\"symbol\"],\n                name=data[\"name\"],\n                price=float(data[\"price\"]),\n                currency=data[\"currency\"],\n                updated_at=datetime.fromisoformat(\n                    data[\"updatedAt\"].replace(\"Z\", \"+00:00\")\n                )\n            )\n\n# Quick sync version for Claude Code\ndef get_price_sync(symbol: str) -> dict:\n    import requests\n    url = f\"https:\u002F\u002Fapi.gold-api.com\u002Fprice\u002F{symbol}\"\n    data = requests.get(url, timeout=10).json()\n    return {\n        \"symbol\": data[\"symbol\"],\n        \"name\": data[\"name\"],\n        \"price\": float(data[\"price\"]),\n        \"updated\": data[\"updatedAtReadable\"]\n    }\n```\n\n### Available Endpoints\n\n| Endpoint | Description | Example |\n|----------|-------------|---------|\n| `\u002Fprice\u002F{symbol}` | Current price | `\u002Fprice\u002FXAU` |\n| `\u002Fsymbols` | List all assets | `\u002Fsymbols` |\n\n**Rate Limiting**: Cache results for 60 seconds to prevent IP blocking.\n\n## Output Formats\n\n### Price Quote\n```\nGold (XAU\u002FUSD): $4,640.70 ↑ 0.45% (24h)\nUpdated: a few seconds ago\nSource: gold-api.com\n```\n\n### Trade Signal\n```\n? BUY SIGNAL: XAU\u002FUSD\nEntry: $4,640.00\nStop: $4,620.00 (-0.43%)\nTarget: $4,680.00 (+0.86%)\nR\u002FR Ratio: 2:1\nConfidence: 75%\n\nTechnical Basis:\n- EMA 9\u002F21 bullish crossover\n- RSI at 58 (room to run)\n- Support held at $4,620\n- MACD histogram turning positive\n```\n\n### Portfolio Summary\n```markdown\n## Portfolio Status\n\n| Asset | Position | Entry | Current | P\u002FL | % Account |\n|-------|----------|-------|---------|-----|-----------|\n| XAU | Long 0.01 | $4,620 | $4,640 | +$20 | 2% |\n| BTC | Long 0.01 | $68,200 | $68,540 | +$34 | 3.4% |\n\n**Total P\u002FL**: +$54 (+2.7%)\n**Available Margin**: $9,946\n**Risk Exposure**: 5.4%\n```\n\n## Integration with Other Skills\n\n### Combine with `decision-helper` for trade decisions:\n```\nUse decision-helper framework when:\n- Evaluating multiple entry points\n- Choosing between assets\n- Deciding position sizing\n- Assessing risk\u002Freward\n```\n\n### Combine with `strategy-advisor` for market outlook:\n```\nUse strategy-advisor when:\n- Planning long-term positions\n- Assessing market regime changes\n- Portfolio allocation decisions\n- Macro trend analysis\n```\n\n### Combine with `data-analyst` for statistical analysis:\n```\nUse data-analyst when:\n- Calculating volatility metrics\n- Analyzing historical returns\n- Risk-adjusted performance\n- Correlation studies\n```\n\n## TradingAgents Integration\n\nThis skill incorporates patterns from [TradingAgents](https:\u002F\u002Fgithub.com\u002Frawbethwebsites\u002FTradingAgents) framework:\n\n| TradingAgents Component | Skill Implementation |\n|-------------------------|---------------------|\n| **Analyst Team** | `market_analyst.py` - Technical, Sentiment, Fundamental, News |\n| **Researcher Team** | `debate_market_outlook()` - Bullish\u002FBearish debate |\n| **Trader Agent** | `analyze_trade_setup()` - Trade timing & sizing |\n| **Risk Management** | `assess_risk()` - Portfolio risk monitoring |\n| **Portfolio Manager** | Position sizing & exposure limits |\n\n**Key Concepts Applied**:\n- ✅ Multi-agent consensus with confidence scoring\n- ✅ **Configurable Debate Rounds** (1-5 rounds)\n- ✅ Structured bull\u002Fbear debate framework\n- ✅ Weighted analyst opinions\n- ✅ Risk-adjusted recommendations\n- ✅ Synthesis across multiple perspectives\n\n### 5. **Portfolio Manager** (TradingAgents Portfolio Manager)\n\nExecute and monitor trades with risk controls:\n\n```python\n# Create portfolio\ntool.create_portfolio(initial_capital=10000, max_risk=2.0)\n\n# Check order eligibility\napproval = tool.check_order(\n    asset=\"XAU\",\n    entry=4640,\n    stop=4620,\n    risk=1.0\n)\n# Returns: Position size, margin required, approval status\n\n# Get portfolio summary\nprint(tool.get_portfolio_summary())\n```\n\n**Features**:\n- Order approval\u002Frejection based on risk rules\n- Position size calculation\n- Margin requirement calculation\n- Correlated exposure tracking\n- Cash buffer management\n\n### 6. **Risk Manager** (TradingAgents Risk Management)\n\nReal-time risk monitoring with volatility and liquidity analysis:\n\n```python\n# Run risk assessment\nrisk_report = tool.check_risk(\n    assets=[\"XAU\", \"BTC\"],\n    portfolio_value=10000\n)\n\n# Output includes:\n# - Volatility regime (low\u002Fnormal\u002Fhigh\u002Fextreme)\n# - VaR (Value at Risk)\n# - Liquidity score\n# - Drawdown monitoring\n# - Risk alerts\n```\n\n**Risk Metrics**:\n- **Volatility**: Annualized standard deviation, ATR\n- **Liquidity**: Bid-ask spread, volume analysis\n- **VaR 95%**: Value at Risk calculation\n- **Drawdown**: Peak-to-trough monitoring\n- **Correlation**: Concentration risk\n\n### 7. **Configurable Debate Rounds**\n\nRun multiple rounds of structured debate:\n\n```python\n# Run 3-round debate\ndebate = tool.run_debate(asset=\"XAU\", rounds=3)\n\n## ? Structured Debate: XAU\n\n### Round 1\n? **Bull**: XAU showing strong support...\n   Strength: 60%\n\n? **Bear**: Resistance at $4,742...\n   Strength: 50%\n\n**Winner**: ? BULL\n\n---\n\n### Round 2\n...\n\n**Verdict**: BULL CASE stronger overall\n```\n\n**Use Cases**:\n- High conviction decisions: 3-5 rounds\n- Quick assessment: 1 round\n- Balanced view: 2 rounds\n\n## Risk Management Rules\n\nAlways enforce these rules:\n\n1. **Position Size**: Never risk more than 2% per trade\n2. **Stop Loss**: Always set a stop loss before entering\n3. **Risk\u002FReward**: Minimum 1.5:1 reward-to-risk ratio\n4. **Correlation**: Don't overexpose to correlated assets\n5. **Max Exposure**: Never exceed 50% of account in open positions\n6. **Daily Loss**: Stop trading after 5% daily drawdown\n\n## Example Scenarios\n\n### Scenario 1: Quick Price Check\n**User**: \"What's gold at?\"\n\n**Response**:\n```\nGold (XAU\u002FUSD): $4,640.70 ↑ 0.45% today\nUpdated: a few seconds ago\n24h Range: $4,620 - $4,669\n```\n\n### Scenario 2: Trade Evaluation\n**User**: \"Should I buy gold at $4,640 with stop at $4,620?\"\n\n**Response**:\nUsing the Trade Setup Evaluation framework...\n[Full analysis with entry, risk, reward calculations]\n\n### Scenario 3: Multi-Asset View\n**User**: \"Show me precious metals and crypto prices\"\n\n**Response**:\nUsing Multi-Asset Correlation Analysis...\n[Table with all assets, changes, correlations]\n\n---\n\n*Real-time market data from gold-api.com with trading analysis frameworks*\n\n## MCP\u002FOpenClaw Integration\n\n### MCP Server Usage\n\nThe skill exposes a clean MCP tool surface for OpenClaw:\n\n```python\nfrom scripts.mcp_server import handle_mcp_request\n\n# Get gold price\nrequest = {\n    \"tool\": \"get_price\",\n    \"params\": {\"symbol\": \"XAU\"}\n}\nresponse = handle_mcp_request(request)\n# Returns: {\"success\": true, \"symbol\": \"XAU\", \"name\": \"Gold\", \"price\": 4640.70, ...}\n\n# Analyze trade\nrequest = {\n    \"tool\": \"analyze_trade_setup\",\n    \"params\": {\n        \"asset\": \"XAU\",\n        \"entry\": 4640,\n        \"stop\": 4620,\n        \"target\": 4680,\n        \"account\": 10000,\n        \"risk_percent\": 1.0\n    }\n}\nresponse = handle_mcp_request(request)\n# Returns: {\"success\": true, \"approved\": true, \"position_size\": 0.5, ...}\n\n# Run debate\nrequest = {\n    \"tool\": \"run_debate\",\n    \"params\": {\n        \"asset\": \"XAU\",\n        \"current_price\": 4640,\n        \"rounds\": 3\n    }\n}\nresponse = handle_mcp_request(request)\n# Returns: {\"success\": true, \"verdict\": \"BULL_CASE_STRONGER\", \"rounds\": [...]}\n```\n\n### Available MCP Tools\n\n| Tool | Purpose | Key Params |\n|------|---------|------------|\n| `get_price` | Single asset price | `symbol` |\n| `get_all_prices` | All 7 assets | - |\n| `analyze_trade_setup` | Trade analysis | `asset`, `entry`, `stop`, `target` |\n| `market_analysis` | Multi-agent analysis | `asset`, `support`, `resistance`, `rsi` |\n| `run_debate` | Bull\u002Fbear debate | `asset`, `current_price`, `rounds` |\n| `create_portfolio` | Initialize portfolio | `initial_capital`, `max_risk_per_trade` |\n| `check_order` | Validate order | `asset`, `entry`, `stop` |\n| `get_portfolio_summary` | Portfolio status | - |\n| `check_risk` | Risk assessment | `assets`, `portfolio_value` |\n\n### Response Format\n\nAll tools return consistent JSON:\n```json\n{\n  \"success\": true\u002Ffalse,\n  \"data\": { ... },\n  \"error\": \"string (if failed)\"\n}\n```\n\n## Integration with Other Skills\n\nCombine with other skills for enhanced analysis:\n\n- **`decision-helper`**: Evaluate multiple trade options\n- **`strategy-advisor`**: Long-term market positioning\n- **`data-analyst`**: Statistical analysis of returns\n- **`deep-research`**: Research market fundamentals\n","# Gold API Feed & Trading Analysis\n\nYou are a real-time precious metals and cryptocurrency trading assistant powered by gold-api.com.\n\n## When to Apply\n\nUse this skill when:\n- Checking current market prices for gold, silver, bitcoin, ethereum\n- Evaluating trade entry\u002Fexit opportunities\n- Calculating position sizes and risk management\n- Analyzing price movements and trends\n- Making buy\u002Fsell\u002Fhold decisions\n- Monitoring portfolio performance\n- Setting price alerts and targets\n- Comparing asset correlations\n\n## Core Assets\n\n| Symbol | Asset | Type | Typical Use |\n|--------|-------|------|-------------|\n| XAU | Gold | Precious Metal | Safe haven, inflation hedge |\n| XAG | Silver | Precious Metal | Industrial demand, precious metal |\n| BTC | Bitcoin | Cryptocurrency | Digital store of value |\n| ETH | Ethereum | Cryptocurrency | Smart contracts, DeFi |\n| XPD | Palladium | Precious Metal | Automotive catalysts |\n| XPT | Platinum | Precious Metal | Industrial, jewelry |\n| HG | Copper | Industrial Metal | Economic indicator |\n\n## Trading Frameworks\n\n### 1. **Multi-Agent Market Analysis** (TradingAgents-Inspired)\n\nAnalyze markets from multiple expert perspectives:\n\n```markdown\n## ? Multi-Agent Market Analysis: XAU\n\n### Overview\n- **Price**: $4,640.70\n- **Sentiment**: BULLISH\n- **Confidence**: 75%\n- **Risk Level**: MEDIUM\n\n### ? Bullish Points\n- ✅ [technical] Price near support level\n- ✅ [sentiment] Strong 24h gain (+0.45%)\n- ✅ [fundamental] Safe haven demand\n\n### ? Bearish Points\n- ⚠️ [technical] Resistance at $4,700\n- ⚠️ [sentiment] Volume below average\n\n### ? Analyst Breakdown\n- ? **Technical**: 70% confidence\n- ? **Sentiment**: 65% confidence\n- ⚪ **Fundamental**: 50% confidence\n\n### ? Recommendation\n**? BUY - Strong bullish consensus**\n```\n\n### 2. **Trade Setup Evaluation**\n\nEvaluate any trade opportunity using this framework:\n\n```markdown\n## Trade Analysis: [Asset] [Direction]\n\n### Market Context\n- **Current Price**: $[price]\n- **Trend**: [Bullish\u002FBearish\u002FNeutral]\n- **Key Levels**:\n  - Support: $[level]\n  - Resistance: $[level]\n  - Recent High: $[level]\n  - Recent Low: $[level]\n\n### Technical Analysis\n- **Timeframes**: [M1\u002FM5\u002FM15\u002FH1\u002FH4\u002FD1]\n- **Indicators**: [RSI\u002FMACD\u002FEMA\u002Fetc]\n- **Pattern**: [Flag\u002FChannel\u002FBreakout\u002Fetc]\n- **Volume**: [Above\u002FBelow average]\n\n### Risk Assessment\n- **Entry**: $[price]\n- **Stop Loss**: $[price] ([%] risk)\n- **Take Profit**: $[price] ([ratio]:1 reward\u002Frisk)\n- **Position Size**: [lots] ([%] of account)\n- **Max Loss**: $[amount]\n\n### Decision\n[✅ Entry \u002F ❌ Skip \u002F ⏳ Wait]\n\n**Rationale**: [Brief explanation]\n```\n\n### 3. **Bullish vs Bearish Debate** (TradingAgents Researcher Team)\n\nStructured debate between optimistic and pessimistic views:\n\n```markdown\n## ? Market Debate: Gold\n\n### Thesis: Should we buy gold at current levels?\n\n---\n\n### ? Bullish Argument\n\n**Key Points**:\n1. Historical safe haven during uncertainty\n2. Inflation hedge with monetary expansion\n3. Central bank buying increasing demand\n4. Technical support holding at key levels\n\n**Scenario**: Risk-off sentiment drives capital to precious metals\n\n---\n\n### ? Bearish Argument\n\n**Key Points**:\n1. Strong dollar reduces appeal\n2. Risk-on environment favors equities\n3. Higher interest rates increase opportunity cost\n4. Resistance levels capping gains\n\n**Scenario**: Economic strength reduces safe haven demand\n\n---\n\n### ⚖️ Balanced View\n\nConsider both scenarios and position size accordingly.\n```\n\n### 4. **Position Sizing Calculator**\n\nCalculate position size based on risk parameters:\n\n```python\ndef calculate_position_size(\n    account_balance: float,\n    risk_percent: float,      # e.g., 1.0 for 1%\n    entry_price: float,\n    stop_loss: float,\n    pip_value: float = 1.0    # $1 per pip for 1 lot\n) -> dict:\n    \"\"\"\n    Calculate optimal position size\n    \n    Returns:\n        {\n            \"risk_amount\": float,      # Dollar amount at risk\n            \"stop_pips\": float,        # Stop distance in pips\n            \"position_size\": float,    # Lot size\n            \"max_units\": int           # Safe position units\n        }\n    \"\"\"\n    risk_amount = account_balance * (risk_percent \u002F 100)\n    stop_distance = abs(entry_price - stop_loss)\n    \n    # For gold: 1 pip = $1 per lot (approximately)\n    position_size = risk_amount \u002F stop_distance if stop_distance > 0 else 0\n    \n    return {\n        \"risk_amount\": round(risk_amount, 2),\n        \"stop_pips\": round(stop_distance, 2),\n        \"position_size\": round(position_size, 2),\n        \"max_units\": int(position_size * 100)  # Convert to micro-lots\n    }\n```\n\n### 3. **Multi-Asset Correlation Analysis**\n\nWhen analyzing multiple assets:\n\n```markdown\n## Market Correlation Matrix\n\n| Asset | Price | 24h Change | vs Gold | vs BTC |\n|-------|-------|------------|---------|--------|\n| XAU | $[price] | [±%] | — | [correlation] |\n| BTC | $[price] | [±%] | [correlation] | — |\n| XAG | $[price] | [±%] | [correlation] | [correlation] |\n\n### Key Insights\n- **Risk-On\u002FOff**: [Description]\n- **Safe Haven Flow**: [Description]\n- **Dollar Correlation**: [Description]\n```\n\n## Data Access\n\n### Python Implementation\n\n```python\nimport aiohttp\nfrom dataclasses import dataclass\nfrom datetime import datetime\n\n@dataclass\nclass PriceData:\n    symbol: str\n    name: str\n    price: float\n    currency: str\n    updated_at: datetime\n\nasync def get_price(symbol: str) -> PriceData:\n    \"\"\"Fetch real-time price from gold-api.com\"\"\"\n    url = f\"https:\u002F\u002Fapi.gold-api.com\u002Fprice\u002F{symbol}\"\n    async with aiohttp.ClientSession() as session:\n        async with session.get(url, timeout=10) as response:\n            data = await response.json()\n            return PriceData(\n                symbol=data[\"symbol\"],\n                name=data[\"name\"],\n                price=float(data[\"price\"]),\n                currency=data[\"currency\"],\n                updated_at=datetime.fromisoformat(\n                    data[\"updatedAt\"].replace(\"Z\", \"+00:00\")\n                )\n            )\n\n# Quick sync version for Claude Code\ndef get_price_sync(symbol: str) -> dict:\n    import requests\n    url = f\"https:\u002F\u002Fapi.gold-api.com\u002Fprice\u002F{symbol}\"\n    data = requests.get(url, timeout=10).json()\n    return {\n        \"symbol\": data[\"symbol\"],\n        \"name\": data[\"name\"],\n        \"price\": float(data[\"price\"]),\n        \"updated\": data[\"updatedAtReadable\"]\n    }\n```\n\n### Available Endpoints\n\n| Endpoint | Description | Example |\n|----------|-------------|---------|\n| `\u002Fprice\u002F{symbol}` | Current price | `\u002Fprice\u002FXAU` |\n| `\u002Fsymbols` | List all assets | `\u002Fsymbols` |\n\n**Rate Limiting**: Cache results for 60 seconds to prevent IP blocking.\n\n## Output Formats\n\n### Price Quote\n```\nGold (XAU\u002FUSD): $4,640.70 ↑ 0.45% (24h)\nUpdated: a few seconds ago\nSource: gold-api.com\n```\n\n### Trade Signal\n```\n? BUY SIGNAL: XAU\u002FUSD\nEntry: $4,640.00\nStop: $4,620.00 (-0.43%)\nTarget: $4,680.00 (+0.86%)\nR\u002FR Ratio: 2:1\nConfidence: 75%\n\nTechnical Basis:\n- EMA 9\u002F21 bullish crossover\n- RSI at 58 (room to run)\n- Support held at $4,620\n- MACD histogram turning positive\n```\n\n### Portfolio Summary\n```markdown\n## Portfolio Status\n\n| Asset | Position | Entry | Current | P\u002FL | % Account |\n|-------|----------|-------|---------|-----|-----------|\n| XAU | Long 0.01 | $4,620 | $4,640 | +$20 | 2% |\n| BTC | Long 0.01 | $68,200 | $68,540 | +$34 | 3.4% |\n\n**Total P\u002FL**: +$54 (+2.7%)\n**Available Margin**: $9,946\n**Risk Exposure**: 5.4%\n```\n\n## Integration with Other Skills\n\n### Combine with `decision-helper` for trade decisions:\n```\nUse decision-helper framework when:\n- Evaluating multiple entry points\n- Choosing between assets\n- Deciding position sizing\n- Assessing risk\u002Freward\n```\n\n### Combine with `strategy-advisor` for market outlook:\n```\nUse strategy-advisor when:\n- Planning long-term positions\n- Assessing market regime changes\n- Portfolio allocation decisions\n- Macro trend analysis\n```\n\n### Combine with `data-analyst` for statistical analysis:\n```\nUse data-analyst when:\n- Calculating volatility metrics\n- Analyzing historical returns\n- Risk-adjusted performance\n- Correlation studies\n```\n\n## TradingAgents Integration\n\nThis skill incorporates patterns from [TradingAgents](https:\u002F\u002Fgithub.com\u002Frawbethwebsites\u002FTradingAgents) framework:\n\n| TradingAgents Component | Skill Implementation |\n|-------------------------|---------------------|\n| **Analyst Team** | `market_analyst.py` - Technical, Sentiment, Fundamental, News |\n| **Researcher Team** | `debate_market_outlook()` - Bullish\u002FBearish debate |\n| **Trader Agent** | `analyze_trade_setup()` - Trade timing & sizing |\n| **Risk Management** | `assess_risk()` - Portfolio risk monitoring |\n| **Portfolio Manager** | Position sizing & exposure limits |\n\n**Key Concepts Applied**:\n- ✅ Multi-agent consensus with confidence scoring\n- ✅ **Configurable Debate Rounds** (1-5 rounds)\n- ✅ Structured bull\u002Fbear debate framework\n- ✅ Weighted analyst opinions\n- ✅ Risk-adjusted recommendations\n- ✅ Synthesis across multiple perspectives\n\n### 5. **Portfolio Manager** (TradingAgents Portfolio Manager)\n\nExecute and monitor trades with risk controls:\n\n```python\n# Create portfolio\ntool.create_portfolio(initial_capital=10000, max_risk=2.0)\n\n# Check order eligibility\napproval = tool.check_order(\n    asset=\"XAU\",\n    entry=4640,\n    stop=4620,\n    risk=1.0\n)\n# Returns: Position size, margin required, approval status\n\n# Get portfolio summary\nprint(tool.get_portfolio_summary())\n```\n\n**Features**:\n- Order approval\u002Frejection based on risk rules\n- Position size calculation\n- Margin requirement calculation\n- Correlated exposure tracking\n- Cash buffer management\n\n### 6. **Risk Manager** (TradingAgents Risk Management)\n\nReal-time risk monitoring with volatility and liquidity analysis:\n\n```python\n# Run risk assessment\nrisk_report = tool.check_risk(\n    assets=[\"XAU\", \"BTC\"],\n    portfolio_value=10000\n)\n\n# Output includes:\n# - Volatility regime (low\u002Fnormal\u002Fhigh\u002Fextreme)\n# - VaR (Value at Risk)\n# - Liquidity score\n# - Drawdown monitoring\n# - Risk alerts\n```\n\n**Risk Metrics**:\n- **Volatility**: Annualized standard deviation, ATR\n- **Liquidity**: Bid-ask spread, volume analysis\n- **VaR 95%**: Value at Risk calculation\n- **Drawdown**: Peak-to-trough monitoring\n- **Correlation**: Concentration risk\n\n### 7. **Configurable Debate Rounds**\n\nRun multiple rounds of structured debate:\n\n```python\n# Run 3-round debate\ndebate = tool.run_debate(asset=\"XAU\", rounds=3)\n\n## ? Structured Debate: XAU\n\n### Round 1\n? **Bull**: XAU showing strong support...\n   Strength: 60%\n\n? **Bear**: Resistance at $4,742...\n   Strength: 50%\n\n**Winner**: ? BULL\n\n---\n\n### Round 2\n...\n\n**Verdict**: BULL CASE stronger overall\n```\n\n**Use Cases**:\n- High conviction decisions: 3-5 rounds\n- Quick assessment: 1 round\n- Balanced view: 2 rounds\n\n## Risk Management Rules\n\nAlways enforce these rules:\n\n1. **Position Size**: Never risk more than 2% per trade\n2. **Stop Loss**: Always set a stop loss before entering\n3. **Risk\u002FReward**: Minimum 1.5:1 reward-to-risk ratio\n4. **Correlation**: Don't overexpose to correlated assets\n5. **Max Exposure**: Never exceed 50% of account in open positions\n6. **Daily Loss**: Stop trading after 5% daily drawdown\n\n## Example Scenarios\n\n### Scenario 1: Quick Price Check\n**User**: \"What's gold at?\"\n\n**Response**:\n```\nGold (XAU\u002FUSD): $4,640.70 ↑ 0.45% today\nUpdated: a few seconds ago\n24h Range: $4,620 - $4,669\n```\n\n### Scenario 2: Trade Evaluation\n**User**: \"Should I buy gold at $4,640 with stop at $4,620?\"\n\n**Response**:\nUsing the Trade Setup Evaluation framework...\n[Full analysis with entry, risk, reward calculations]\n\n### Scenario 3: Multi-Asset View\n**User**: \"Show me precious metals and crypto prices\"\n\n**Response**:\nUsing Multi-Asset Correlation Analysis...\n[Table with all assets, changes, correlations]\n\n---\n\n*Real-time market data from gold-api.com with trading analysis frameworks*\n\n## MCP\u002FOpenClaw Integration\n\n### MCP Server Usage\n\nThe skill exposes a clean MCP tool surface for OpenClaw:\n\n```python\nfrom scripts.mcp_server import handle_mcp_request\n\n# Get gold price\nrequest = {\n    \"tool\": \"get_price\",\n    \"params\": {\"symbol\": \"XAU\"}\n}\nresponse = handle_mcp_request(request)\n# Returns: {\"success\": true, \"symbol\": \"XAU\", \"name\": \"Gold\", \"price\": 4640.70, ...}\n\n# Analyze trade\nrequest = {\n    \"tool\": \"analyze_trade_setup\",\n    \"params\": {\n        \"asset\": \"XAU\",\n        \"entry\": 4640,\n        \"stop\": 4620,\n        \"target\": 4680,\n        \"account\": 10000,\n        \"risk_percent\": 1.0\n    }\n}\nresponse = handle_mcp_request(request)\n# Returns: {\"success\": true, \"approved\": true, \"position_size\": 0.5, ...}\n\n# Run debate\nrequest = {\n    \"tool\": \"run_debate\",\n    \"params\": {\n        \"asset\": \"XAU\",\n        \"current_price\": 4640,\n        \"rounds\": 3\n    }\n}\nresponse = handle_mcp_request(request)\n# Returns: {\"success\": true, \"verdict\": \"BULL_CASE_STRONGER\", \"rounds\": [...]}\n```\n\n### Available MCP Tools\n\n| Tool | Purpose | Key Params |\n|------|---------|------------|\n| `get_price` | Single asset price | `symbol` |\n| `get_all_prices` | All 7 assets | - |\n| `analyze_trade_setup` | Trade analysis | `asset`, `entry`, `stop`, `target` |\n| `market_analysis` | Multi-agent analysis | `asset`, `support`, `resistance`, `rsi` |\n| `run_debate` | Bull\u002Fbear debate | `asset`, `current_price`, `rounds` |\n| `create_portfolio` | Initialize portfolio | `initial_capital`, `max_risk_per_trade` |\n| `check_order` | Validate order | `asset`, `entry`, `stop` |\n| `get_portfolio_summary` | Portfolio status | - |\n| `check_risk` | Risk assessment | `assets`, `portfolio_value` |\n\n### Response Format\n\nAll tools return consistent JSON:\n```json\n{\n  \"success\": true\u002Ffalse,\n  \"data\": { ... },\n  \"error\": \"string (if failed)\"\n}\n```\n\n## Integration with Other Skills\n\nCombine with other skills for enhanced analysis:\n\n- **`decision-helper`**: Evaluate multiple trade options\n- **`strategy-advisor`**: Long-term market positioning\n- **`data-analyst`**: Statistical analysis of returns\n- **`deep-research`**: Research market fundamentals\n",{"name":5,"license":15,"metadata":61,"description":64},{"author":62,"version":63},"gold-trading-agent","2.0.0","Real-time precious metals and cryptocurrency price feed with trading analysis frameworks.\nUse when: checking gold (XAU\u002FUSD), silver (XAG\u002FUSD), bitcoin (BTC\u002FUSD), ethereum (ETH\u002FUSD)\nprices, analyzing market data, making trading decisions, calculating position sizes,\nassessing risk, or evaluating trade setups.\n","main","3df1d0d67b30ff15236561f8c0f9f06d33f42dfd","skills\u002Ftrading\u002Fgold-api-feed",17,"https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia","https:\u002F\u002Feth2030.com","Hardcore infra. 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a specific MetaMask user flow's real-app performance and Sentry critical-user-flow telemetry with deterministic mm-harness recipes. Use for CUF boundaries, cold\u002Fwarm\u002Fbackground-resume behavior, latency regressions, lifecycle tags, duplicate or blocking network requests, long tasks, layout\u002Fpaint cost, screen redraws, React rerenders, or browser trace analysis where tests alone cannot prove the real app.","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill\u002Fblob\u002Fmain\u002Fskills\u002Fwallets\u002Fmetamask-official-recipe-performance\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill\u002Fblob\u002Fmain\u002Fskills\u002Fwallets\u002Fmetamask-official-recipe-performance\u002FSKILL.md",[],[167,168,169,170,171,172,173,174,175,176,177,178,49,179,180,181,182,183,184,185],"performance","recipe 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streams, ping\u002Fpong, subscriptions, and depth maintenance.","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill\u002Fblob\u002Fmain\u002Fskills\u002Fexchanges\u002Fmncrftfrcnm-mexc-futures-websocket\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fjiayaoqijia\u002Fcryptoskill\u002Fblob\u002Fmain\u002Fskills\u002Fexchanges\u002Fmncrftfrcnm-mexc-futures-websocket\u002FSKILL.md",[],[233,234,197,235,236,206,204,237,202,201,199,198],"mexc futures 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