market-sentiment — Claude Code skill: what it does, how to install
Aggregates crypto news from RSS feeds, scores article sentiment, and calculates an overall market index from -1 to +1.
npx skills add kukapay/crypto-skills --skill market-sentiment -a claude-codeWhat market-sentiment does
This skill evaluates crypto news coverage across curated feeds. It retrieves recent articles and assigns a sentiment score to each story. Reports on product launches or market rallies count as positive (+1). Stories about security exploits or regulatory crackdowns count as negative (-1). Factual updates without bias receive a neutral zero.
The tool averages all values into a single score between -1 and +1, pairing the number with key market drivers. For automated processing via sentiment_analyzer.py, a local Python setup is mandatory. Custom feed URLs and classification benchmarks are organized in references/rss_feeds.md and references/sentiment_examples.md.
What it helps with
- compute an aggregate crypto sentiment score from -1 to +1
- fetch recent news across selected crypto RSS sources
- identify positive and negative market catalysts before trading
- review evidence-based breakdowns of current market news
Example prompts for the agent
- Check current crypto market sentiment from RSS feeds
- Run
python sentiment_analyzer.pyto calculate the latest sentiment score - Break down positive and negative news drivers using
references/rss_feeds.md
How to install market-sentiment
1Skills CLI (Vercel)
npx skills add kukapay/crypto-skills --skill market-sentiment -a claude-code2Manually: put the files in place
~/.claude/skills/market-sentiment/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/market-sentiment/
1Skills CLI (Vercel)
npx skills add kukapay/crypto-skills --skill market-sentiment -a codex2Manually: put the files in place
.agents/skills/market-sentiment/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add kukapay/crypto-skills --skill market-sentiment -a cursor2Manually: put the files in place
.cursor/skills/market-sentiment/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install kukapay/crypto-skills market-sentiment2Manually: put the files in place
.github/skills/market-sentiment/SKILL.md1Skills CLI (Vercel)
npx skills add kukapay/crypto-skills --skill market-sentiment -a gemini-cli2Platform CLI
gemini skills install https://github.com/kukapay/crypto-skills --path skills/market-sentimentManually: put the files in place
.devin/skills/market-sentiment/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add kukapay/crypto-skills --skill market-sentiment -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about market-sentiment
How to install market-sentiment in Claude Code?
Run npx skills add kukapay/crypto-skills --skill market-sentiment -a claude-code. The skill file is placed at ~/.claude/skills/market-sentiment/SKILL.md.
What does market-sentiment do?
It gathers articles from cryptocurrency RSS feeds, grades article tone, and produces an average score from -1 to +1 with explanatory evidence.
What files come with the skill?
The package includes scripts/sentiment_analyzer.py for automated analysis, alongside references/rss_feeds.md for feed URLs and references/sentiment_examples.md for classification samples.
Source text
SKILL.md · MIT
--- name: market-sentiment description: 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. --- # 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/rss_feeds.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/ - `sentiment_analyzer.py`: Python script to fetch RSS feeds, parse articles, and compute sentiment score. Run with `python sentiment_analyzer.py` to 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.
© kukapay · MIT · kukapay/crypto-skills
