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  "item": {
    "slug": "cryptocurrency-trader-skill",
    "name": "Cryptocurrency Trader",
    "source": "tencent",
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    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/Veeramanikandanr48/cryptocurrency-trader-skill",
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      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
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      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
        "Extract it into a folder your agent can access.",
        "Paste one of the prompts below and point your agent at the extracted folder."
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          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
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        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
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        "Review SKILL.md after the package is downloaded.",
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        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
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    "downloadPageUrl": "https://openagent3.xyz/downloads/cryptocurrency-trader-skill",
    "agentPageUrl": "https://openagent3.xyz/skills/cryptocurrency-trader-skill/agent",
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    "briefUrl": "https://openagent3.xyz/skills/cryptocurrency-trader-skill/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
      }
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Purpose",
        "body": "Provide production-grade cryptocurrency trading analysis with mathematical rigor, multi-layer validation, and comprehensive risk assessment. Designed for real-world trading application with zero-hallucination tolerance through 6-stage validation pipeline."
      },
      {
        "title": "When to Use This Skill",
        "body": "Use this skill when users request:\n\nAnalysis of specific cryptocurrency trading pairs (e.g., BTC/USDT, ETH/USDT)\nMarket scanning to find best trading opportunities\nComprehensive risk assessment with probabilistic modeling\nTrading signals with advanced pattern recognition\nProfessional risk metrics (VaR, CVaR, Sharpe, Sortino)\nMonte Carlo simulations for scenario analysis\nBayesian probability calculations for signal confidence"
      },
      {
        "title": "Validation & Accuracy",
        "body": "6-stage validation pipeline with zero-hallucination tolerance\nStatistical anomaly detection (Z-score, IQR, Benford's Law)\nCross-verification across multiple timeframes\n14 circuit breakers to prevent invalid signals"
      },
      {
        "title": "Analysis Methods",
        "body": "Bayesian inference for probability calculations\nMonte Carlo simulations (10,000 scenarios)\nGARCH volatility forecasting\nAdvanced chart pattern recognition\nMulti-timeframe consensus (15m, 1h, 4h)"
      },
      {
        "title": "Risk Management",
        "body": "Value at Risk (VaR) and Conditional VaR (CVaR)\nRisk-adjusted metrics (Sharpe, Sortino, Calmar)\nKelly Criterion position sizing\nAutomated stop-loss and take-profit calculation\n\nDetailed capabilities: See references/advanced-capabilities.md"
      },
      {
        "title": "Prerequisites",
        "body": "Ensure the following before using this skill:\n\nPython 3.8+ environment available\nInternet connection for real-time market data\nRequired packages installed: pip install -r requirements.txt\nUser's account balance known for position sizing"
      },
      {
        "title": "Quick Start Commands",
        "body": "Analyze a specific cryptocurrency:\n\npython skill.py analyze BTC/USDT --balance 10000\n\nScan market for best opportunities:\n\npython skill.py scan --top 5 --balance 10000\n\nInteractive mode for exploration:\n\npython skill.py interactive --balance 10000"
      },
      {
        "title": "Default Parameters",
        "body": "Balance: If not specified by user, use --balance 10000\nTimeframes: 15m, 1h, 4h (automatically analyzed)\nRisk per trade: 2% of balance (enforced by default)\nMinimum risk/reward: 1.5:1 (validated by circuit breakers)"
      },
      {
        "title": "Common Trading Pairs",
        "body": "Major: BTC/USDT, ETH/USDT, BNB/USDT, SOL/USDT, XRP/USDT\nAI Tokens: RENDER/USDT, FET/USDT, AGIX/USDT\nLayer 1: ADA/USDT, AVAX/USDT, DOT/USDT\nLayer 2: MATIC/USDT, ARB/USDT, OP/USDT\nDeFi: UNI/USDT, AAVE/USDT, LINK/USDT\nMeme: DOGE/USDT, SHIB/USDT, PEPE/USDT"
      },
      {
        "title": "Workflow",
        "body": "Gather Information\n\nAsk user for trading pair (if analyzing specific symbol)\nAsk for account balance (or use default $10,000)\nConfirm user wants production-grade analysis\n\n\n\nExecute Analysis\n\nRun appropriate command (analyze, scan, or interactive)\nWait for comprehensive analysis to complete\nSystem automatically validates through 6 stages\n\n\n\nPresent Results\n\nDisplay trading signal (LONG/SHORT/NO_TRADE)\nShow confidence level and execution readiness\nExplain entry, stop-loss, and take-profit prices\nPresent risk metrics and position sizing\nHighlight validation status (6/6 passed = execution ready)\n\n\n\nInterpret Output\n\nReference references/output-interpretation.md for detailed guidance\nTranslate technical metrics into user-friendly language\nExplain risk/reward in simple terms\nAlways include risk warnings\n\n\n\nHandle Edge Cases\n\nIf execution_ready = NO: Explain validation failures\nIf confidence <40%: Recommend waiting for better opportunity\nIf circuit breakers triggered: Explain specific issue\nIf network errors: Suggest retry with exponential backoff"
      },
      {
        "title": "Output Structure",
        "body": "Trading Signal:\n\nAction: LONG/SHORT/NO_TRADE\nConfidence: 0-95% (integer only, no false precision)\nEntry Price: Recommended entry point\nStop Loss: Risk management exit (always required)\nTake Profit: Profit target\nRisk/Reward: Minimum 1.5:1 ratio\n\nProbabilistic Analysis:\n\nBayesian probabilities (bullish/bearish)\nMonte Carlo profit probability\nSignal strength (WEAK/MODERATE/STRONG)\nPattern bias confirmation\n\nRisk Assessment:\n\nVaR and CVaR (Value at Risk metrics)\nSharpe/Sortino/Calmar ratios\nMax drawdown and win rate\nProfit factor\n\nPosition Sizing:\n\nStandard (2% risk rule) - recommended\nKelly Conservative - mathematically optimal\nKelly Aggressive - higher risk/reward\nTrading fees estimate\n\nValidation Status:\n\nStages passed (must be 6/6 for execution ready)\nCircuit breakers triggered (if any)\nWarnings and critical failures\n\nDetailed interpretation: See references/output-interpretation.md"
      },
      {
        "title": "Language Guidelines",
        "body": "Use beginner-friendly explanations:\n\n\"LONG\" → \"Buy now, sell higher later\"\n\"SHORT\" → \"Sell now, buy back cheaper later\"\n\"Stop Loss\" → \"Automatic exit to limit loss if wrong\"\n\"Confidence %\" → \"How certain we are (higher = better)\"\n\"Risk/Reward\" → \"For every $1 risked, potential $X profit\""
      },
      {
        "title": "Required Risk Warnings",
        "body": "ALWAYS include these reminders:\n\nMarkets are unpredictable - perfect analysis can still be wrong\nStart with small amounts to learn\nNever risk more than 2% per trade (enforced automatically)\nAlways use stop losses\nThis is analysis, NOT financial advice\nPast performance does NOT guarantee future results\nUser is solely responsible for all trading decisions"
      },
      {
        "title": "When NOT to Trade",
        "body": "Advise users to avoid trading when:\n\nValidation status <6/6 passed\nExecution Ready flag = NO\nConfidence <60% for moderate signals, <70% for strong\nUser doesn't understand the analysis\nUser can't afford potential loss\nHigh emotional stress or fatigue"
      },
      {
        "title": "Programmatic Integration",
        "body": "For custom workflows, import directly:\n\nfrom scripts.trading_agent_refactored import TradingAgent\n\nagent = TradingAgent(balance=10000)\nanalysis = agent.comprehensive_analysis('BTC/USDT')\nprint(analysis['final_recommendation'])\n\nSee example_usage.py for 5 comprehensive examples."
      },
      {
        "title": "Configuration",
        "body": "Customize behavior via config.yaml:\n\nValidation strictness (strict vs normal mode)\nRisk parameters (max risk, position limits)\nCircuit breaker thresholds\nTimeframe preferences"
      },
      {
        "title": "Testing",
        "body": "Verify installation and functionality:\n\n# Run compatibility test\n./test_claude_code_compat.sh\n\n# Run comprehensive tests\npython -m pytest tests/"
      },
      {
        "title": "Reference Documentation",
        "body": "references/advanced-capabilities.md - Detailed technical capabilities\nreferences/output-interpretation.md - Comprehensive output guide\nreferences/optimization.md - Trading optimization strategies\nreferences/protocol.md - Usage protocols and best practices\nreferences/psychology.md - Trading psychology principles\nreferences/user-guide.md - End-user documentation\nreferences/technical-docs/ - Implementation details and bug reports"
      },
      {
        "title": "Architecture",
        "body": "Core Modules:\n\nscripts/trading_agent_refactored.py - Main trading agent (production)\nscripts/advanced_validation.py - Multi-layer validation system\nscripts/advanced_analytics.py - Probabilistic modeling engine\nscripts/pattern_recognition_refactored.py - Chart pattern recognition\nscripts/indicators/ - Technical indicator calculations\nscripts/market/ - Data provider and market scanner\nscripts/risk/ - Position sizing and risk management\nscripts/signals/ - Signal generation and recommendation\n\nEntry Points:\n\nskill.py - Command-line interface (recommended)\n__main__.py - Python module invocation\nexample_usage.py - Programmatic usage examples"
      },
      {
        "title": "Version",
        "body": "v2.0.1 - Production Hardened Edition\n\nRecent improvements:\n\nFixed critical bugs (division by zero, import paths, NaN handling)\nEnhanced network retry logic with exponential backoff\nImproved logging infrastructure\nComprehensive input validation\nUTC timezone consistency\nBenford's Law threshold optimization\n\nStatus: 🟢 PRODUCTION READY\n\nSee references/technical-docs/FIXES_APPLIED.md for complete changelog."
      },
      {
        "title": "Troubleshooting",
        "body": "Installation issues:\n\npip install --upgrade pip\npip install -r requirements.txt\n\nImport errors:\nEnsure running from skill directory or using skill.py entry point.\n\nNetwork failures:\nSystem automatically retries with exponential backoff (3 attempts).\n\nValidation failures:\nCheck validation report in output - explains which stage failed and why.\n\nFor detailed debugging:\nEnable logging in config.yaml or check references/technical-docs/BUG_ANALYSIS_REPORT.md"
      }
    ],
    "body": "Cryptocurrency Trading Agent Skill\nPurpose\n\nProvide production-grade cryptocurrency trading analysis with mathematical rigor, multi-layer validation, and comprehensive risk assessment. Designed for real-world trading application with zero-hallucination tolerance through 6-stage validation pipeline.\n\nWhen to Use This Skill\n\nUse this skill when users request:\n\nAnalysis of specific cryptocurrency trading pairs (e.g., BTC/USDT, ETH/USDT)\nMarket scanning to find best trading opportunities\nComprehensive risk assessment with probabilistic modeling\nTrading signals with advanced pattern recognition\nProfessional risk metrics (VaR, CVaR, Sharpe, Sortino)\nMonte Carlo simulations for scenario analysis\nBayesian probability calculations for signal confidence\nCore Capabilities\nValidation & Accuracy\n6-stage validation pipeline with zero-hallucination tolerance\nStatistical anomaly detection (Z-score, IQR, Benford's Law)\nCross-verification across multiple timeframes\n14 circuit breakers to prevent invalid signals\nAnalysis Methods\nBayesian inference for probability calculations\nMonte Carlo simulations (10,000 scenarios)\nGARCH volatility forecasting\nAdvanced chart pattern recognition\nMulti-timeframe consensus (15m, 1h, 4h)\nRisk Management\nValue at Risk (VaR) and Conditional VaR (CVaR)\nRisk-adjusted metrics (Sharpe, Sortino, Calmar)\nKelly Criterion position sizing\nAutomated stop-loss and take-profit calculation\n\nDetailed capabilities: See references/advanced-capabilities.md\n\nPrerequisites\n\nEnsure the following before using this skill:\n\nPython 3.8+ environment available\nInternet connection for real-time market data\nRequired packages installed: pip install -r requirements.txt\nUser's account balance known for position sizing\nHow to Use This Skill\nQuick Start Commands\n\nAnalyze a specific cryptocurrency:\n\npython skill.py analyze BTC/USDT --balance 10000\n\n\nScan market for best opportunities:\n\npython skill.py scan --top 5 --balance 10000\n\n\nInteractive mode for exploration:\n\npython skill.py interactive --balance 10000\n\nDefault Parameters\nBalance: If not specified by user, use --balance 10000\nTimeframes: 15m, 1h, 4h (automatically analyzed)\nRisk per trade: 2% of balance (enforced by default)\nMinimum risk/reward: 1.5:1 (validated by circuit breakers)\nCommon Trading Pairs\n\nMajor: BTC/USDT, ETH/USDT, BNB/USDT, SOL/USDT, XRP/USDT AI Tokens: RENDER/USDT, FET/USDT, AGIX/USDT Layer 1: ADA/USDT, AVAX/USDT, DOT/USDT Layer 2: MATIC/USDT, ARB/USDT, OP/USDT DeFi: UNI/USDT, AAVE/USDT, LINK/USDT Meme: DOGE/USDT, SHIB/USDT, PEPE/USDT\n\nWorkflow\n\nGather Information\n\nAsk user for trading pair (if analyzing specific symbol)\nAsk for account balance (or use default $10,000)\nConfirm user wants production-grade analysis\n\nExecute Analysis\n\nRun appropriate command (analyze, scan, or interactive)\nWait for comprehensive analysis to complete\nSystem automatically validates through 6 stages\n\nPresent Results\n\nDisplay trading signal (LONG/SHORT/NO_TRADE)\nShow confidence level and execution readiness\nExplain entry, stop-loss, and take-profit prices\nPresent risk metrics and position sizing\nHighlight validation status (6/6 passed = execution ready)\n\nInterpret Output\n\nReference references/output-interpretation.md for detailed guidance\nTranslate technical metrics into user-friendly language\nExplain risk/reward in simple terms\nAlways include risk warnings\n\nHandle Edge Cases\n\nIf execution_ready = NO: Explain validation failures\nIf confidence <40%: Recommend waiting for better opportunity\nIf circuit breakers triggered: Explain specific issue\nIf network errors: Suggest retry with exponential backoff\nOutput Structure\n\nTrading Signal:\n\nAction: LONG/SHORT/NO_TRADE\nConfidence: 0-95% (integer only, no false precision)\nEntry Price: Recommended entry point\nStop Loss: Risk management exit (always required)\nTake Profit: Profit target\nRisk/Reward: Minimum 1.5:1 ratio\n\nProbabilistic Analysis:\n\nBayesian probabilities (bullish/bearish)\nMonte Carlo profit probability\nSignal strength (WEAK/MODERATE/STRONG)\nPattern bias confirmation\n\nRisk Assessment:\n\nVaR and CVaR (Value at Risk metrics)\nSharpe/Sortino/Calmar ratios\nMax drawdown and win rate\nProfit factor\n\nPosition Sizing:\n\nStandard (2% risk rule) - recommended\nKelly Conservative - mathematically optimal\nKelly Aggressive - higher risk/reward\nTrading fees estimate\n\nValidation Status:\n\nStages passed (must be 6/6 for execution ready)\nCircuit breakers triggered (if any)\nWarnings and critical failures\n\nDetailed interpretation: See references/output-interpretation.md\n\nPresenting Results to Users\nLanguage Guidelines\n\nUse beginner-friendly explanations:\n\n\"LONG\" → \"Buy now, sell higher later\"\n\"SHORT\" → \"Sell now, buy back cheaper later\"\n\"Stop Loss\" → \"Automatic exit to limit loss if wrong\"\n\"Confidence %\" → \"How certain we are (higher = better)\"\n\"Risk/Reward\" → \"For every $1 risked, potential $X profit\"\nRequired Risk Warnings\n\nALWAYS include these reminders:\n\nMarkets are unpredictable - perfect analysis can still be wrong\nStart with small amounts to learn\nNever risk more than 2% per trade (enforced automatically)\nAlways use stop losses\nThis is analysis, NOT financial advice\nPast performance does NOT guarantee future results\nUser is solely responsible for all trading decisions\nWhen NOT to Trade\n\nAdvise users to avoid trading when:\n\nValidation status <6/6 passed\nExecution Ready flag = NO\nConfidence <60% for moderate signals, <70% for strong\nUser doesn't understand the analysis\nUser can't afford potential loss\nHigh emotional stress or fatigue\nAdvanced Usage\nProgrammatic Integration\n\nFor custom workflows, import directly:\n\nfrom scripts.trading_agent_refactored import TradingAgent\n\nagent = TradingAgent(balance=10000)\nanalysis = agent.comprehensive_analysis('BTC/USDT')\nprint(analysis['final_recommendation'])\n\n\nSee example_usage.py for 5 comprehensive examples.\n\nConfiguration\n\nCustomize behavior via config.yaml:\n\nValidation strictness (strict vs normal mode)\nRisk parameters (max risk, position limits)\nCircuit breaker thresholds\nTimeframe preferences\nTesting\n\nVerify installation and functionality:\n\n# Run compatibility test\n./test_claude_code_compat.sh\n\n# Run comprehensive tests\npython -m pytest tests/\n\nReference Documentation\nreferences/advanced-capabilities.md - Detailed technical capabilities\nreferences/output-interpretation.md - Comprehensive output guide\nreferences/optimization.md - Trading optimization strategies\nreferences/protocol.md - Usage protocols and best practices\nreferences/psychology.md - Trading psychology principles\nreferences/user-guide.md - End-user documentation\nreferences/technical-docs/ - Implementation details and bug reports\nArchitecture\n\nCore Modules:\n\nscripts/trading_agent_refactored.py - Main trading agent (production)\nscripts/advanced_validation.py - Multi-layer validation system\nscripts/advanced_analytics.py - Probabilistic modeling engine\nscripts/pattern_recognition_refactored.py - Chart pattern recognition\nscripts/indicators/ - Technical indicator calculations\nscripts/market/ - Data provider and market scanner\nscripts/risk/ - Position sizing and risk management\nscripts/signals/ - Signal generation and recommendation\n\nEntry Points:\n\nskill.py - Command-line interface (recommended)\n__main__.py - Python module invocation\nexample_usage.py - Programmatic usage examples\nVersion\n\nv2.0.1 - Production Hardened Edition\n\nRecent improvements:\n\nFixed critical bugs (division by zero, import paths, NaN handling)\nEnhanced network retry logic with exponential backoff\nImproved logging infrastructure\nComprehensive input validation\nUTC timezone consistency\nBenford's Law threshold optimization\n\nStatus: 🟢 PRODUCTION READY\n\nSee references/technical-docs/FIXES_APPLIED.md for complete changelog.\n\nTroubleshooting\n\nInstallation issues:\n\npip install --upgrade pip\npip install -r requirements.txt\n\n\nImport errors: Ensure running from skill directory or using skill.py entry point.\n\nNetwork failures: System automatically retries with exponential backoff (3 attempts).\n\nValidation failures: Check validation report in output - explains which stage failed and why.\n\nFor detailed debugging: Enable logging in config.yaml or check references/technical-docs/BUG_ANALYSIS_REPORT.md"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/Veeramanikandanr48/cryptocurrency-trader-skill",
    "publisherUrl": "https://clawhub.ai/Veeramanikandanr48/cryptocurrency-trader-skill",
    "owner": "Veeramanikandanr48",
    "version": "0.1.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
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    "downloadUrl": "https://openagent3.xyz/downloads/cryptocurrency-trader-skill",
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}