luokai0 Crypto Market Sentiment
Overview
This skill enables aggregation of news from popular cryptocurrency RSS feeds, performs sentiment analysis on the articles, and computes a market sentiment score ranging from -1 (highly negative) to +1 (highly positive), along with evidence-based explanations.
Workflow
Follow these steps to analyze crypto market sentiment:
- Select RSS Feeds: Choose popular crypto RSS feeds (see references/rss_feeds.md for a curated list).
- Fetch News: Retrieve recent articles from the selected feeds.
- Analyze Sentiment: Classify each article's sentiment as positive (+1), negative (-1), or neutral (0) based on content keywords and context.
- Calculate Score: Compute the average sentiment score across all articles.
- Generate Explanation: Provide evidence from the news items supporting the score.
Sentiment Classification Guidelines
- Positive (+1): News about adoption, launches, partnerships, ETF approvals, price rallies, regulatory wins, or technological breakthroughs.
- Negative (-1): News about hacks, crashes, regulatory crackdowns, liquidations, delays, or criticisms.
- Neutral (0): Factual updates, mixed outcomes, or speculative content without clear bias.
Output Format
The skill outputs:
- Sentiment Score: Numerical value between -1 and 1.
- Explanation: Breakdown by feed/source, key positive/negative drivers, and overall market implications.
Resources
scripts/
sentiment_analyzer.py: Python script to fetch RSS feeds, parse articles, and compute sentiment score. Run withpython sentiment_analyzer.pyto get automated results.
references/
rss_feeds.md: List of popular crypto RSS feeds with URLs and descriptions.sentiment_examples.md: Examples of sentiment classification for common news types.