
analyzing-market-sentiment
by jeremylongshore
Hundreds of Claude Code plugins with embedded AI skills. Learn via interactive Jupyter tutorials.
SKILL.md
name: analyzing-market-sentiment description: | 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".
allowed-tools: Read, Bash(crypto:sentiment-*) version: 2.0.0 author: Jeremy Longshore jeremy@intentsolutions.io license: MIT
Analyzing Market Sentiment
Overview
This skill provides comprehensive cryptocurrency market sentiment analysis by combining multiple data sources:
- Fear & Greed Index: Market-wide sentiment from Alternative.me
- News Sentiment: Keyword-based analysis of recent crypto news
- Market Momentum: Price and volume trends from CoinGecko
Key Capabilities:
- Composite sentiment score (0-100) with classification
- Coin-specific sentiment analysis
- Detailed breakdown of sentiment components
- Multiple output formats (table, JSON, CSV)
Prerequisites
Before using this skill, ensure:
- Python 3.8+ is installed
- requests library is available:
pip install requests - Internet connectivity for API access (Alternative.me, CoinGecko)
- Optional:
crypto-news-aggregatorskill for enhanced news analysis
Instructions
Step 1: Assess User Intent
Determine what sentiment analysis the user needs:
- Overall market: No specific coin, general sentiment
- Coin-specific: Extract coin symbol (BTC, ETH, etc.)
- Quick vs detailed: Quick score or full breakdown
Step 2: Execute Sentiment Analysis
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 --detailed
Step 3: Present Results
Format and present the sentiment analysis:
- Show composite score and classification
- Explain what the sentiment means
- Highlight any extreme readings
- For detailed mode, show component breakdown
Command-Line Options
| 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 |
Sentiment Classifications
| 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 |
Output
Table Format (Default)
==============================================================================
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.
==============================================================================
JSON Format
{
"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"
}
}
Error Handling
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 |
Examples
See {baseDir}/references/examples.md for detailed examples.
Quick 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
Resources
- Alternative.me Fear & Greed Index: https://alternative.me/crypto/fear-and-greed-index/
- CoinGecko API: https://www.coingecko.com/en/api
- Sentiment Analysis Theory: Contrarian indicator - extreme readings often precede reversals
- See
{baseDir}/config/settings.yamlfor configuration options
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 1000以上
1ヶ月以内に更新
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
Reviews coming soon

