[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6F6RS043CQY7WHHKK39ZAXF":3,"skill-same:01M6F6RS043CQY7WHHKK39ZAXF":73},{"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":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":53,"repositoryHtmlUrl":54,"repositoryHomepageUrl":55,"ownerHtmlUrl":56,"ownerBlogUrl":6,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6F6RS043CQY7WHHKK39ZAXF","analyzing-market-sentiment",null,"Analyze cryptocurrency market sentiment using Fear & Greed Index, news analysis, and market momentum.\nUse when gauging overall market mood, checking if markets are fearful or greedy, or analyzing sentiment for specific coins.\nTrigger with phrases like \"analyze crypto sentiment\", \"check market mood\", \"is the market fearful\", \"sentiment for Bitcoin\", or \"Fear and Greed index\".","ComeOnOliver\u002Fskillshub","ComeOnOliver","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F43215937?v=4","01M6E5JNFECJAAVFE0W7SMWWD2","Haoran Shu","01M6E5JNNDQS7AJZDYFQ8TPZCK",67,"MIT","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fjeremylongshore\u002Fclaude-code-plugins-plus-skills\u002Fanalyzing-market-sentiment\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"sentiment","analyzing","market sentiment","Market","analyzing market sentiment","analyzing-market","codex","markets","with","trigger","io","news","crypto","use","read","check","analyze","Bash","analysis","code","2026-11-10 10:12:30",false,"---\nname: analyzing-market-sentiment\ndescription: |\n  Analyze cryptocurrency market sentiment using Fear & Greed Index, news analysis, and market momentum.\n  Use when gauging overall market mood, checking if markets are fearful or greedy, or analyzing sentiment for specific coins.\n  Trigger with phrases like \"analyze crypto sentiment\", \"check market mood\", \"is the market fearful\", \"sentiment for Bitcoin\", or \"Fear and Greed index\".\n\nallowed-tools: Read, Bash(crypto:sentiment-*)\nversion: 2.0.0\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\nlicense: MIT\ncompatible-with: claude-code, codex, openclaw\ntags: [crypto, analyzing-market]\n\n---\n# Analyzing Market Sentiment\n\n## Overview\n\nCryptocurrency market sentiment analysis combining Fear & Greed Index, news keyword analysis, and price\u002Fvolume momentum into a composite 0-100 score.\n\n## Prerequisites\n\n1. **Python 3.8+** installed\n2. **Dependencies**: `pip install requests`\n3. Internet connectivity for API access (Alternative.me, CoinGecko)\n4. Optional: `crypto-news-aggregator` skill for enhanced news analysis\n\n## Instructions\n\n1. **Assess user intent** - determine what analysis is needed:\n   - Overall market: no specific coin, general sentiment\n   - Coin-specific: extract symbol (BTC, ETH, etc.)\n   - Quick vs detailed: quick score or full component breakdown\n\n2. **Run sentiment analysis** with appropriate options:\n   ```bash\n   # Quick market sentiment check\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py\n\n   # Coin-specific sentiment\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --coin BTC\n\n   # Detailed breakdown with all components\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --detailed\n\n   # Custom time period\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --period 7d --detailed\n   ```\n\n3. **Export results** for trading models or analysis:\n   ```bash\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --format json --output sentiment.json\n   ```\n\n4. **Present results** to the user:\n   - Show composite score and classification prominently\n   - Explain what the sentiment reading means\n   - Highlight extreme readings (potential contrarian signals)\n   - For detailed mode, show component breakdown with weights\n\n## Output\n\nComposite sentiment score (0-100) with classification and weighted component breakdown. Extreme readings serve as contrarian indicators:\n\n```\n==============================================================================\n  MARKET SENTIMENT ANALYZER                         Updated: 2026-01-14 15:30  # 2026 - current year timestamp\n==============================================================================\n\n  COMPOSITE SENTIMENT\n------------------------------------------------------------------------------\n  Score: 65.5 \u002F 100                         Classification: GREED\n\n  Component Breakdown:\n  - Fear & Greed Index:  72.0  (weight: 40%)  -> 28.8 pts\n  - News Sentiment:      58.5  (weight: 40%)  -> 23.4 pts\n  - Market Momentum:     66.5  (weight: 20%)  -> 13.3 pts\n\n  Interpretation: Market is moderately greedy. Consider taking profits or\n  reducing position sizes. Watch for reversal signals.\n\n==============================================================================\n```\n\n## Error Handling\n\n| Error | Cause | Solution |\n|-------|-------|----------|\n| Fear & Greed unavailable | API down | Uses cached value with warning |\n| News fetch failed | Network issue | Reduces weight of news component |\n| Invalid coin | Unknown symbol | Proceeds with market-wide analysis |\n\nSee `${CLAUDE_SKILL_DIR}\u002Freferences\u002Ferrors.md` for comprehensive error handling.\n\n## Examples\n\nSentiment analysis patterns from quick checks to custom-weighted deep analysis:\n\n```bash\n# Quick market sentiment\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py\n\n# Bitcoin-specific sentiment\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --coin BTC\n\n# Detailed analysis with component breakdown\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --detailed\n\n# Custom weights emphasizing news\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --weights \"news:0.5,fng:0.3,momentum:0.2\"\n\n# Weekly sentiment trend\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --period 7d --detailed\n```\n\n## Resources\n\n- `${CLAUDE_SKILL_DIR}\u002Freferences\u002Fimplementation.md` - CLI options, classifications, JSON format, contrarian theory\n- `${CLAUDE_SKILL_DIR}\u002Freferences\u002Ferrors.md` - Comprehensive error handling\n- `${CLAUDE_SKILL_DIR}\u002Freferences\u002Fexamples.md` - Detailed usage examples\n- Alternative.me Fear & Greed: https:\u002F\u002Falternative.me\u002Fcrypto\u002Ffear-and-greed-index\u002F\n- CoinGecko API: https:\u002F\u002Fwww.coingecko.com\u002Fen\u002Fapi\n- `${CLAUDE_SKILL_DIR}\u002Fconfig\u002Fsettings.yaml` - Configuration options\n\n","# Analyzing Market Sentiment\n\n## Overview\n\nCryptocurrency market sentiment analysis combining Fear & Greed Index, news keyword analysis, and price\u002Fvolume momentum into a composite 0-100 score.\n\n## Prerequisites\n\n1. **Python 3.8+** installed\n2. **Dependencies**: `pip install requests`\n3. Internet connectivity for API access (Alternative.me, CoinGecko)\n4. Optional: `crypto-news-aggregator` skill for enhanced news analysis\n\n## Instructions\n\n1. **Assess user intent** - determine what analysis is needed:\n   - Overall market: no specific coin, general sentiment\n   - Coin-specific: extract symbol (BTC, ETH, etc.)\n   - Quick vs detailed: quick score or full component breakdown\n\n2. **Run sentiment analysis** with appropriate options:\n   ```bash\n   # Quick market sentiment check\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py\n\n   # Coin-specific sentiment\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --coin BTC\n\n   # Detailed breakdown with all components\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --detailed\n\n   # Custom time period\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --period 7d --detailed\n   ```\n\n3. **Export results** for trading models or analysis:\n   ```bash\n   python ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --format json --output sentiment.json\n   ```\n\n4. **Present results** to the user:\n   - Show composite score and classification prominently\n   - Explain what the sentiment reading means\n   - Highlight extreme readings (potential contrarian signals)\n   - For detailed mode, show component breakdown with weights\n\n## Output\n\nComposite sentiment score (0-100) with classification and weighted component breakdown. Extreme readings serve as contrarian indicators:\n\n```\n==============================================================================\n  MARKET SENTIMENT ANALYZER                         Updated: 2026-01-14 15:30  # 2026 - current year timestamp\n==============================================================================\n\n  COMPOSITE SENTIMENT\n------------------------------------------------------------------------------\n  Score: 65.5 \u002F 100                         Classification: GREED\n\n  Component Breakdown:\n  - Fear & Greed Index:  72.0  (weight: 40%)  -> 28.8 pts\n  - News Sentiment:      58.5  (weight: 40%)  -> 23.4 pts\n  - Market Momentum:     66.5  (weight: 20%)  -> 13.3 pts\n\n  Interpretation: Market is moderately greedy. Consider taking profits or\n  reducing position sizes. Watch for reversal signals.\n\n==============================================================================\n```\n\n## Error Handling\n\n| Error | Cause | Solution |\n|-------|-------|----------|\n| Fear & Greed unavailable | API down | Uses cached value with warning |\n| News fetch failed | Network issue | Reduces weight of news component |\n| Invalid coin | Unknown symbol | Proceeds with market-wide analysis |\n\nSee `${CLAUDE_SKILL_DIR}\u002Freferences\u002Ferrors.md` for comprehensive error handling.\n\n## Examples\n\nSentiment analysis patterns from quick checks to custom-weighted deep analysis:\n\n```bash\n# Quick market sentiment\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py\n\n# Bitcoin-specific sentiment\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --coin BTC\n\n# Detailed analysis with component breakdown\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --detailed\n\n# Custom weights emphasizing news\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --weights \"news:0.5,fng:0.3,momentum:0.2\"\n\n# Weekly sentiment trend\npython ${CLAUDE_SKILL_DIR}\u002Fscripts\u002Fsentiment_analyzer.py --period 7d --detailed\n```\n\n## Resources\n\n- `${CLAUDE_SKILL_DIR}\u002Freferences\u002Fimplementation.md` - CLI options, classifications, JSON format, contrarian theory\n- `${CLAUDE_SKILL_DIR}\u002Freferences\u002Ferrors.md` - Comprehensive error handling\n- `${CLAUDE_SKILL_DIR}\u002Freferences\u002Fexamples.md` - Detailed usage examples\n- Alternative.me Fear & Greed: https:\u002F\u002Falternative.me\u002Fcrypto\u002Ffear-and-greed-index\u002F\n- CoinGecko API: https:\u002F\u002Fwww.coingecko.com\u002Fen\u002Fapi\n- `${CLAUDE_SKILL_DIR}\u002Fconfig\u002Fsettings.yaml` - Configuration options\n\n",{"name":5,"tags":44,"author":45,"license":15,"version":46,"description":47,"allowed-tools":48,"compatible-with":49},[31,24],"Jeremy Longshore 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