Assess crypto market mood with the Fear & Greed Index, news keywords, and price and volume momentum. Get a 0–100 composite score and component breakdown for the overall market or a selected coin, with options to view trends or export JSON.
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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".
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Cryptocurrency market sentiment analysis combining Fear & Greed Index, news keyword analysis, and price/volume momentum into a composite 0-100 score.
pip install requestscrypto-news-aggregator skill for enhanced news analysisAssess user intent - determine what analysis is needed:
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
Export results for trading models or analysis:
python ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --format json --output sentiment.json
Present results to the user:
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 | 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 references/errors.md for comprehensive error handling.
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 ${CLAUDE_SKILL_DIR}/scripts/sentiment_analyzer.py --period 7d --detailed
references/implementation.md - CLI options, classifications, JSON format, contrarian theoryreferences/errors.md - Comprehensive error handlingreferences/examples.md - Detailed usage examples${CLAUDE_SKILL_DIR}/config/settings.yaml - Configuration options还没有评价。欢迎分享你的使用感受。
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Add a synthetic-data CI gate for customer-owned Abridge integration code. Test consent handling, note-review handoffs, redaction, and rollback behavior with mocked vendor boundaries, without connecting CI to a live Abridge or EHR tenant.
中文简介正在准备中。当前显示英语简介。
Triage Abridge recording, note review, Epic handoff, and access problems using observed symptoms and approved guidance. Identify the affected workflow stage, organize a minimal timeline, and prepare a redacted escalation record for the responsible team.
中文简介正在准备中。当前显示英语简介。
Map and review an Abridge clinical documentation workflow from consent and recording through draft review, evidence checks, edits, and final disposition. Keep clinician approval explicit, identify failure exits, and separate verified facts from tenant-specific details and pending approvals.
中文简介正在准备中。当前显示英语简介。
Audit how clinician-reviewed Abridge note sections map into Epic templates and downstream workflows. Use approved test records to document destinations, exceptions, evidence, rollback steps, and a go or no-go decision for a specific environment.
中文简介正在准备中。当前显示英语简介。
Review Abridge adoption and workflow value using local usage records, clinician feedback, and verified contract costs. Build an evidence based decision table covering adoption, quality, support burden, and options to expand, hold, or improve the rollout.
中文简介正在准备中。当前显示英语简介。
Prepare a bounded support bundle for an Abridge issue using allowlisted operational details such as versions, coarse timestamps, and correlation references. Exclude recordings, transcripts, patient identifiers, credentials, and unrestricted logs, then document redactions and review details.
中文简介正在准备中。当前显示英语简介。