FrancoStino/news-sentiment-engine
bundled-skills/news-sentiment-engine/SKILL.md
Multi-source RSS news aggregation with Claude-powered sentiment analysis and structured briefing output
$ install --global
skillsauthnpx skillsauth add FrancoStino/opencode-skills-antigravity news-sentiment-engineInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
95%
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SemgrepStatic code analysis for vulnerabilities
95%
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mcp-scan (Snyk)Model Context Protocol security validation
95%
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Snyk (dep)Open source security scanning
50%
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OWASP Dep-Check
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Last scanned: May 22, 2026, 2:59 AM144.6s1 file scanned
SKILL.md
- name:
- news-sentiment-engine
- description:
- Multi-source RSS news aggregation with Claude-powered sentiment analysis and structured briefing output
- category:
- research
- risk:
- critical
- source:
- community
- source_repo:
- tellmefrankie/news-engine
- source_type:
- community
- date_added:
- 2026-05-13
- author:
- tellmefrankie
- tags:
- [news, rss, sentiment-analysis, briefing, research]
- tools:
- [claude, websearch]
- codex:
- blocked
- claude:
- blocked
News Sentiment Engine (Free)
Collect and analyze AI/tech news from multiple sources with Claude-powered sentiment analysis. Open source lite version.
When to Use
- Use when preparing a concise AI or technology news briefing from multiple RSS sources.
- Use when you need ranked article summaries with sentiment, tags, and impact scoring.
- Use when monitoring industry changes across product launches, policy moves, and infrastructure shifts.
- Use when deduplicating overlapping coverage before writing a daily or weekly briefing.
What it does
- Collects news from 4+ RSS feeds (TechCrunch, The Verge, Ars Technica, Hacker News)
- Deduplicates articles across sources
- Ranks by importance (industry impact, technology trends, policy changes)
- Generates structured briefing with sentiment tags
- Outputs formatted briefing card
Usage
Collect latest AI/tech news from RSS feeds.
Rank top 5 by importance to the tech industry.
For each: summary (2-3 sentences), sentiment (positive/negative/neutral),
impact score (1-5), industry tags, one-sentence commentary.
Output as a structured briefing card.
Example Output
AI/Tech News Briefing — 2026-05-13
1. OpenAI announces GPT-5 with 2M context window
Source: TechCrunch | Impact: 5/5
Tags: #AI #LLM #OpenAI
Sentiment: Positive
Summary: OpenAI unveiled GPT-5 with a 2M token context window and
improved reasoning. Enterprise pricing starts at $0.03/1k tokens.
Commentary: Direct competitive pressure on Anthropic Claude 3.5.
Enterprise deals may shift in H2 2026.
2. EU AI Act enforcement begins for high-risk systems
Source: The Verge | Impact: 4/5
Tags: #Regulation #EU #Compliance
Sentiment: Neutral
Output Format
For each article:
- Title + source + publish date
- Summary (2-3 sentences)
- Industry tags: [AI, Semiconductor, Cloud, etc.]
- Sentiment: Positive/Negative/Neutral
- Impact score: 1-5
- Commentary: 1-sentence industry perspective
Setup
The optional setup below clones and runs a third-party Node project from
tellmefrankie/news-engine. Review and pin that repository yourself before
running it, and do not expose API keys to an unreviewed checkout.
git clone https://github.com/tellmefrankie/news-engine
cd news-engine
pnpm install
cp .env.example .env
# Requires: ANTHROPIC_API_KEY
pnpm dev -- --collect-only
No paid APIs required for free tier. Anthropic API key only.
Limitations
- RSS feeds can lag, disappear, throttle, or duplicate syndicated coverage.
- Sentiment and impact scores are briefing aids, not authoritative market or policy analysis.
- The example setup runs third-party code; review the repository and environment variables before use.
- Outputs should be cross-checked against original article sources before publication or investment use.
Pro Version
Free tier covers news collection and basic analysis.
Full bundle — $29 one-time: Investment-grade analysis (portfolio impact scoring, options flow correlation, earnings catalyst detection), Telegram auto-delivery. → https://jaehyunpark.gumroad.com/l/tcyahy
Author
Core module from a production news analysis engine processing 50+ articles daily since 2026.
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