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Get Started Free →Multi-source RSS news aggregation with Claude-powered sentiment analysis and structured briefing output
.claude/skills/news-sentiment-engine/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-13 | ✗→✓ | ▲ Improved | — | — |
| case-09 | ✗→✓ | ▲ Improved | — | — |
| case-18 | ✗→✓ | ▲ Improved | — | — |
| case-10 | ✗→✓ | ▲ Improved | — | — |
| case-03 | ✗→✓ | ▲ Improved | — | — |
Collect and analyze AI/tech news from multiple sources with Claude-powered sentiment analysis. Open source lite version.
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.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: NeutralFor each article:
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.
bashgit 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.
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
Core module from a production news analysis engine processing 50+ articles daily since 2026.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-07 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-09 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +36 percentage points is the difference between those two pass rates over the 22 comparable cases.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.