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加密货币市场情绪分析工具 - 结合恐惧贪婪指数、新闻与动量生成综合评分

analyzing-market-sentiment by jeremylongshore/claude-code-plugins-plus-skills

70 周安装量

1,900 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-market-sentiment

数据分析区块链金融科技

🇨🇳中文介绍

市场情绪分析

概述

结合恐惧与贪婪指数、新闻关键词分析以及价格/成交量动量，生成一个 0-100 分的综合评分，用于加密货币市场情绪分析。

前提条件

已安装 Python 3.8+
依赖项：pip install requests
用于访问 API（Alternative.me, CoinGecko）的网络连接
可选：crypto-news-aggregator 技能用于增强新闻分析

使用说明

评估用户意图 - 确定需要何种分析： * 整体市场：无特定币种，通用情绪 * 特定币种：提取符号（BTC, ETH 等） * 快速与详细：快速评分或完整的组件细分
使用适当的选项运行情绪分析：

快速市场情绪检查

python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py

# 特定币种情绪
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --coin BTC

# 包含所有组件的详细细分
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --detailed

# 自定义时间段
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed

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3. 导出结果 用于交易模型或分析：

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

4. 向用户展示结果： * 突出显示综合评分和分类 * 解释情绪读数的含义 * 高亮极端读数（潜在的反向信号） * 对于详细模式，显示带权重的组件细分

包含分类和加权组件细分的综合情绪评分（0-100）。极端读数可作为反向指标：

==============================================================================
  市场情绪分析器                         更新时间：2026-01-14 15:30  # 2026 - 当前年份时间戳
==============================================================================

  综合情绪
------------------------------------------------------------------------------
  评分：65.5 / 100                         分类：贪婪

  组件细分：
  - 恐惧与贪婪指数：  72.0  (权重：40%)  -> 28.8 分
  - 新闻情绪：      58.5  (权重：40%)  -> 23.4 分
  - 市场动量：     66.5  (权重：20%)  -> 13.3 分

  解读：市场处于中度贪婪状态。考虑获利了结或减少持仓规模。留意反转信号。

==============================================================================

错误	原因	解决方案
恐惧与贪婪指数不可用	API 宕机	使用缓存值并发出警告
新闻获取失败	网络问题	降低新闻组件的权重
无效币种	未知符号	继续进行市场范围分析

有关全面的错误处理，请参阅 ${CLAUDE_SKILL_DIR}/references/errors.md。

从快速检查到自定义权重的深度分析的情绪分析模式：

# 快速市场情绪
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py

# 比特币特定情绪
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --coin BTC

# 包含组件细分的详细分析
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --detailed

# 强调新闻的自定义权重
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --weights "news:0.5,fng:0.3,momentum:0.2"

# 每周情绪趋势
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed

${CLAUDE_SKILL_DIR}/references/implementation.md - CLI 选项、分类、JSON 格式、反向理论
${CLAUDE_SKILL_DIR}/references/errors.md - 全面的错误处理
${CLAUDE_SKILL_DIR}/references/examples.md - 详细使用示例
Alternative.me 恐惧与贪婪指数：https://alternative.me/crypto/fear-and-greed-index/
CoinGecko API：https://www.coingecko.com/en/api
${CLAUDE_SKILL_DIR}/config/settings.yaml - 配置选项

🇺🇸English

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

Python 3.8+ installed
Dependencies : pip install requests
Internet connectivity for API access (Alternative.me, CoinGecko)
Optional: crypto-news-aggregator skill for enhanced news analysis

Instructions

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
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

Weekly Installs

Repository

jeremylongshore…s-skills

GitHub Stars

1.8K

First Seen

Feb 1, 2026

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