npx skills add smithery/kukapay --skill market-sentiment
kukapay/crypto-skills
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.
Installation
$
npx skills add kukapay/crypto-skills --skill market-sentiment
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Other skills from kukapay/crypto-skills.
npx skills add kukapay/crypto-skills
More details
Agent compatibility
Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
Claude Code
Not declared
Cursor
Not declared
Codex
Not declared
GitHub Copilot
Not declared
Windsurf
Not declared
Gemini CLI
Not declared
Cline
Not declared
OpenCode
Not declared
Also listed on
Alternate registries and mirrors of this skill.
Repository health
Stars
36
License
LICENSE
Default branch
main
Open issues
0
Status
Active
Package contents
Files included with this skill beyond the listing page.
-
skill md
SKILL.md2,159 B -
docs
SUMMARY.md2,125 B
History
- First seen on skills.sh
- First recorded snapshot · 575 installs
SKILL.md
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/
sentimentanalyzer.py: Python script to fetch RSS feeds, parse articles, and compute sentiment score. Run withpython sentimentanalyzer.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.