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

1. Run sentiment analysis with appropriate options:

bash # 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

1. Export results for trading models or analysis:

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

1. 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:

==============================================================================
  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 Handling

| 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.

Examples

Sentiment analysis patterns from quick checks to custom-weighted deep analysis:

bash
# 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

Resources

• ${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
• Alternative.me Fear & Greed: https://alternative.me/crypto/fear-and-greed-index/
• CoinGecko API: https://www.coingecko.com/en/api
• ${CLAUDE_SKILL_DIR}/config/settings.yaml - Configuration options