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analyzing-market-sentiment

'Analyze cryptocurrency market sentiment using Fear & Greed Index, news

Install / Use

npx skills add jeremylongshore/tons-of-skills-marketplace --skill analyzing-market-sentiment

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

85/100

Supported Platforms

Universal

Tags

Our assessment of analyzing-market-sentiment

analyzing-market-sentiment scores 85/100 on our quality scale, 1761st of 3,845 Development & Engineering skills we index (top 46%).

Its SKILL.md is 4.7 KB long, well organised into 13 sections with 2 code examples: a solid amount of guidance for an agent.

With 2,785 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
12/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 6 days ago, so analyzing-market-sentiment is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

analyzing-market-sentiment compared with similar skills

All 4 of these similar skills score higher than analyzing-market-sentiment; compare them before choosing.

SkillScoreStarsUpdatedFormat
analyzing-market-sentiment (this skill)by jeremylongshore852.8k6d agoSKILL.md
ai-job-searchby MadsLorentzen10044.5ktodayCLAUDE.md
claude-howtoby luongnv8910041.7k4d agoCLAUDE.md
algorithmic-artby anthropics100177.9k7d agoSKILL.md
pptxby anthropics100177.9k7d agoSKILL.md

Frequently asked questions

How do I install analyzing-market-sentiment?
Run npx skills add jeremylongshore/tons-of-skills-marketplace --skill analyzing-market-sentiment. The install tabs above show the steps for each supported agent.
Which AI agents does analyzing-market-sentiment work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is analyzing-market-sentiment safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is analyzing-market-sentiment still maintained?
The repository was last updated 6 days ago, so analyzing-market-sentiment is actively maintained.

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: 1.24.0 author: Jeremy Longshore jeremy@intentsolutions.io license: MIT tags:

  • crypto
  • analyzing-market compatibility: Designed for Claude Code

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

| 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 ${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

Related Skills

View on GitHub
GitHub Stars2.8k
CategoryDevelopment
Updated6d ago
Forks404

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions