Analyze cryptocurrency market sentiment using Fear & Greed Index, news analysis, and market momentum. Use when gauging overall market mood, checking if markets are fearful or greedy, or analyzing sentiment for specific coins. Trigger with phrases like "analyze crypto sentiment", "check market mood", "is the market fearful", "sentiment for Bitcoin", or "Fear and Greed index".
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-market-sentiment85
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
This skill provides comprehensive cryptocurrency market sentiment analysis by combining multiple data sources:
Key Capabilities:
Before using this skill, ensure:
pip install requestscrypto-news-aggregator skill for enhanced news analysisDetermine what sentiment analysis the user needs:
Run the sentiment analyzer with appropriate options:
# Quick sentiment check (default)
python {baseDir}/scripts/sentiment_analyzer.py
# Coin-specific sentiment
python {baseDir}/scripts/sentiment_analyzer.py --coin BTC
# Detailed analysis with component breakdown
python {baseDir}/scripts/sentiment_analyzer.py --detailed
# Export to JSON
python {baseDir}/scripts/sentiment_analyzer.py --format json --output sentiment.json
# Custom time period
python {baseDir}/scripts/sentiment_analyzer.py --period 7d --detailedFormat and present the sentiment analysis:
| Option | Description | Default |
|---|---|---|
--coin | Analyze specific coin (BTC, ETH, etc.) | All market |
--period | Time period (1h, 4h, 24h, 7d) | 24h |
--detailed | Show full component breakdown | false |
--format | Output format (table, json, csv) | table |
--output | Output file path | stdout |
--weights | Custom weights (e.g., "news:0.5,fng:0.3,momentum:0.2") | Default |
--verbose | Enable verbose output | false |
| Score Range | Classification | Description |
|---|---|---|
| 0-20 | Extreme Fear | Market panic, potential bottom |
| 21-40 | Fear | Cautious sentiment, bearish |
| 41-60 | Neutral | Balanced, no strong bias |
| 61-80 | Greed | Optimistic, bullish sentiment |
| 81-100 | Extreme Greed | Euphoria, potential top |
==============================================================================
MARKET SENTIMENT ANALYZER Updated: 2026-01-14 15:30
==============================================================================
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.
=============================================================================={
"composite_score": 65.5,
"classification": "Greed",
"components": {
"fear_greed": {
"score": 72,
"classification": "Greed",
"weight": 0.40,
"contribution": 28.8
},
"news_sentiment": {
"score": 58.5,
"articles_analyzed": 25,
"positive": 12,
"negative": 5,
"neutral": 8,
"weight": 0.40,
"contribution": 23.4
},
"market_momentum": {
"score": 66.5,
"btc_change_24h": 3.5,
"weight": 0.20,
"contribution": 13.3
}
},
"meta": {
"timestamp": "2026-01-14T15:30:00Z",
"period": "24h"
}
}See {baseDir}/references/errors.md for comprehensive 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 {baseDir}/references/examples.md for detailed examples.
# Quick market sentiment check
python {baseDir}/scripts/sentiment_analyzer.py
# Bitcoin-specific sentiment
python {baseDir}/scripts/sentiment_analyzer.py --coin BTC
# Detailed analysis
python {baseDir}/scripts/sentiment_analyzer.py --detailed
# Export for trading model
python {baseDir}/scripts/sentiment_analyzer.py --format json --output sentiment.json
# Custom weights (emphasize news)
python {baseDir}/scripts/sentiment_analyzer.py --weights "news:0.5,fng:0.3,momentum:0.2"
# Weekly sentiment comparison
python {baseDir}/scripts/sentiment_analyzer.py --period 7d --detailed{baseDir}/config/settings.yaml for configuration options22fc789
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