analyzing-market-sentiment

name	analyzing-market-sentiment
description	This skill provides comprehensive cryptocurrency market sentiment analysis by combining multiple data sources 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 <[e-mail]>
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:

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

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.yaml for configuration options