agentsclimarketplace

Analyzing market sentiment

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/crypto/market-sentiment-analyzer/skills/analyzing-market-sentiment

'Analyze cryptocurrency market sentiment using Fear & Greed Index, news analysis, and market momentum.From its SKILL.md

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-market-sentiment

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

4.7 KB, 950 tokens by cl100k_base, as published. Nobody here has run it

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
  2. Run sentiment analysis with appropriate options:

    # 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
    
  3. Export results for trading models or analysis:

    python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --format json --output sentiment.json
    
  4. 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

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

# 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

What ships with it: 11 files

91.5 KB alongside SKILL.md, 5 of them executable

config/

references/

scripts/

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.