Agent skill · data analytics · aaaaqwq
analyzing-market-sentiment
This skill provides comprehensive cryptocurrency market sentiment analysis by combining multiple data sources
Why this skill is useful
Adds a comprehensive sentiment analysis tool for cryptocurrency markets that combines multiple data sources and provides detailed breakdowns not commonly available.
What it needs
Requires python, requests installed locally. About 3k tokens when loaded. Last updated 2026-08-06. 83 stars on the source repository.
What this skill does
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: 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 Option Description Default -------- ------------- --------- --coin Analyze specific coin (BTC, ETH, etc.) All market --period Time period (1h, 4h, 24h, 7d) 24h --detailed Show full component breakdown false --format Output format (table, json, csv) table --output Output file path stdout --weights Custom weights (e.g., "news:0.5,fng:0.3,momentum:0.2") Default --verbose Enable verbose output false Sentiment Classifications Score Range Classification Description ------------- ---------------- ------------- 0-20 Extreme Fear Market panic, potential bottom 21-40 Fear Cautious sentiment, bearish 41-60 Neutral Balanced, no strong bias 61-80 Greed O …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aaaaqwq/market-sentiment-analyzer