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jeremylongshore

analyzing-market-sentiment

by jeremylongshore

Hundreds of Claude Code plugins with embedded AI skills. Learn via interactive Jupyter tutorials.

1,042🍴 135📅 Jan 23, 2026

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:

  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

OptionDescriptionDefault
--coinAnalyze specific coin (BTC, ETH, etc.)All market
--periodTime period (1h, 4h, 24h, 7d)24h
--detailedShow full component breakdownfalse
--formatOutput format (table, json, csv)table
--outputOutput file pathstdout
--weightsCustom weights (e.g., "news:0.5,fng:0.3,momentum:0.2")Default
--verboseEnable verbose outputfalse

Sentiment Classifications

Score RangeClassificationDescription
0-20Extreme FearMarket panic, potential bottom
21-40FearCautious sentiment, bearish
41-60NeutralBalanced, no strong bias
61-80GreedOptimistic, bullish sentiment
81-100Extreme GreedEuphoria, 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.

ErrorCauseSolution
Fear & Greed unavailableAPI downUses cached value with warning
News fetch failedNetwork issueReduces weight of news component
Invalid coinUnknown symbolProceeds 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

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Total Score

85/100

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