Analyzing Market Sentiment

Overview

Cryptocurrency market sentiment analysis combining Fear & Greed Index, news keyword analysis, and price/volume momentum into a composite 0-100 score.

Prerequisites

1. Python 3.8+ installed
2. Dependencies: pip install requests
3. Internet connectivity for API access (Alternative.me, CoinGecko)
4. Optional: crypto-news-aggregator skill for enhanced news analysis

Instructions

1. Assess user intent - determine what analysis is needed:

   • Overall market: no specific coin, general sentiment
   • Coin-specific: extract symbol (BTC, ETH, etc.)
   • Quick vs detailed: quick score or full component breakdown

2. 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
   

3. Export results for trading models or analysis:

   python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --format json --output sentiment.json
   

4. Present results to the user:

   • Show composite score and classification prominently
   • Explain what the sentiment reading means
   • Highlight extreme readings (potential contrarian signals)
   • For detailed mode, show component breakdown with weights

Output

Composite sentiment score (0-100) with classification and weighted component breakdown. Extreme readings serve as contrarian indicators: