Agent skill · marketing growth · kukapay
market-sentiment
Aggregate news from popular cryptocurrency RSS feeds, analyze sentiment of articles, and calculate an overall market sentiment score with detailed explanation. Use when assessing crypto market sentiment for trading decisions, research, or monitoring trends from RSS sources.
Why this skill is useful
Adds a Python script for automated sentiment analysis of cryptocurrency news that the AI wouldn't generate on its own.
What it needs
Requires python installed locally. About 1k tokens when loaded. Last updated 2026-05-04. 31 stars on the source repository.
What this skill does
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: 1. Select RSS Feeds: Choose popular crypto RSS feeds (see references/rssfeeds.md for a curated list). 2. Fetch News: Retrieve recent articles from the selected feeds. 3. Analyze Sentiment: Classify each article's sentiment as positive (+1), negative (-1), or neutral (0) based on content keywords and context. 4. Calculate Score: Compute the average sentiment score across all articles. 5. 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/ sentimentanalyzer.py: Python script to fetch RSS feeds, parse articles, and compute sentiment score. Run with python sentimentanalyzer.py to get automated results. references/ rssfeeds.md: List of popular crypto RSS feeds with URLs and descriptions. sentimentexamples.md: Examples of sentiment classification for common news types.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills kukapay/market-sentiment