Cryptocurrency market sentiment analysis combining Fear & Greed Index, news keyword analysis, and price/volume momentum into a composite 0-100 score.
pip install requests
crypto-news-aggregator skill for enhanced news analysisAssess user intent - determine what analysis is needed:
Run sentiment analysis with appropriate options:
# Quick market sentiment check
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py
# Coin-specific sentiment
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --coin BTC
# Detailed breakdown with all components
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --detailed
# Custom time period
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed
Export results for trading models or analysis:
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --format json --output sentiment.json
Present results to the user:
Composite sentiment score (0-100) with classification and weighted component breakdown. Extreme readings serve as contrarian indicators:
==============================================================================
MARKET SENTIMENT ANALYZER Updated: 2026-01-14 15:30 # 2026 - current year timestamp
==============================================================================
COMPOSITE SENTIMENT
------------------------------------------------------------------------------
Score: 65.5 / 100 Classification: GREED
Component Breakdown:
- Fear & Greed Index: 72.0 (weight: 40%) -> 28.8 pts
- News Sentiment: 58.5 (weight: 40%) -> 23.4 pts
- Market Momentum: 66.5 (weight: 20%) -> 13.3 pts
Interpretation: Market is moderately greedy. Consider taking profits or
reducing position sizes. Watch for reversal signals.
==============================================================================
| Error | Cause | Solution |
|---|---|---|
| Fear & Greed unavailable | API down | Uses cached value with warning |
| News fetch failed | Network issue | Reduces weight of news component |
| Invalid coin | Unknown symbol | Proceeds with market-wide analysis |
See ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error handling.
Sentiment analysis patterns from quick checks to custom-weighted deep analysis:
# Quick market sentiment
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py
# Bitcoin-specific sentiment
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --coin BTC
# Detailed analysis with component breakdown
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --detailed
# Custom weights emphasizing news
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --weights "news:0.5,fng:0.3,momentum:0.2"
# Weekly sentiment trend
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed
${CLAUDE_SKILL_DIR}/references/implementation.md - CLI options, classifications, JSON format, contrarian theory${CLAUDE_SKILL_DIR}/references/errors.md - Comprehensive error handling${CLAUDE_SKILL_DIR}/references/examples.md - Detailed usage examples${CLAUDE_SKILL_DIR}/config/settings.yaml - Configuration options