Market Sentiment

Pulls recent articles from crypto RSS feeds, runs sentiment analysis on each one, and spits out a score from -1 to +1 with an explanation of what's driving the market mood. It classifies news as positive (partnerships, ETF approvals, rallies), negative (hacks, crashes, regulatory crackdowns), or neutral based on keywords and context. The workflow is straightforward: select feeds, fetch articles, analyze sentiment, average the scores, and generate evidence-based reasoning. Useful when you need a quick read on crypto market sentiment for trading calls or research without manually skimming dozens of headlines. The Python script automates the whole process, though sentiment accuracy will depend heavily on keyword matching rather than deep NLP.

skills.sh installs: 662
GitHub stars: 37
last updated: Aug 21, 2026

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Install

$ npx -y skills add kukapay/crypto-skills --skill market-sentiment --agent claude-code

Installs into .claude/skills of the current project.

Files

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.