AI News Digest Plugin

Automatically aggregates latest AI news from multiple sources and generates a curated Top 5 digest on-demand.

Table of Contents

Automatically aggregates latest AI news from multiple sources and generates a curated Top 5 digest on-demand.

Process Flow

flowchart TD
    A([User Trigger]) -->|"latest AI news / AI news digest"| B[Load feeds.yaml Config]
    B --> C[Fetch RSS Feeds in Parallel]

    subgraph Sources["12+ RSS Sources"]
        direction LR
        S1["Official Blogs<br/>Anthropic/OpenAI/Google<br/>(weight: 10)"]
        S2["Research Papers<br/>ArXiv ML/AI/CL<br/>(weight: 8)"]
        S3["Community<br/>HN / Reddit<br/>(weight: 6)"]
        S4["Tech News<br/>Verge / TechCrunch<br/>(weight: 5)"]
    end

    C --> Sources
    Sources --> D[Collect All Articles]
    D --> E[Score Each Article]

    subgraph Scoring["Scoring Formula"]
        SC1[Base Source Weight]
        SC2["+ Keyword Boost<br/>high +5 / medium +3 / low +1"]
        SC3["+ Recency Boost<br/>24h +10 / 48h +5 / week +2"]
    end

    E --> Scoring
    Scoring --> F[Sort by Score]
    F --> G[Select Top 5 Stories]
    G --> H[Generate Digest Markdown]
    H --> I[Save ai-news-digest-YYYY-MM-DD.md]
    I --> J([Done ✅ ~15-20 seconds total])

Features

  • Multi-Source Aggregation: Fetches from 12+ RSS feeds (Anthropic, OpenAI, Google, ArXiv, Hacker News, Reddit, etc.)
  • Smart Scoring: Ranks news by relevance, recency, and source authority
  • Top 5 Curation: Automatically selects the most important stories
  • Configurable Sources: Easily add/remove RSS feeds via YAML config
  • Fast Execution: Results in ~15-20 seconds
  • Markdown Output: Clean, readable digest documents

Installation

/plugin marketplace add JayKim88/claude-ai-engineering
/plugin install ai-news-digest

Via npx

npx github:JayKim88/claude-ai-engineering ai-news-digest

Local Development

cd ~/Documents/Projects/claude-ai-engineering
npm run link

Requirements

  • Claude Code CLI
  • Python 3.7+
  • feedparser and pyyaml packages (auto-installed)
pip3 install feedparser pyyaml

Usage

Trigger Phrases

English:

  • “latest AI news”
  • “AI news digest”
  • “what’s new in AI”
  • “fetch AI news”

Korean:

  • “최신 AI 뉴스”
  • “AI 뉴스 정리”
  • “AI 소식”

Example

User: "최신 AI 뉴스 가져와줘"

Claude: Fetching latest AI news from the past 7 days...

[15 seconds later]

✅ AI News Digest saved to: ./ai-news-digest-2026-02-03.md

📊 Summary:
- 12 sources checked
- 47 articles found
- Top 5 selected

🔥 Top Stories:
1. Claude 3.5 Opus Released - Anthropic Blog (score: 45)
2. GPT-5 Training Details - OpenAI Blog (score: 42)
3. Breakthrough in Multimodal Reasoning - ArXiv (score: 38)
4. New Open-Source LLM Benchmarks - Hacker News (score: 35)
5. Fine-tuning Best Practices - Reddit (score: 32)

Want me to analyze any of these in detail?

RSS Feed Sources

Official Blogs (High Priority)

  • Anthropic Blog
  • OpenAI Blog
  • Google AI Blog
  • DeepMind Blog

Research Papers (High Priority)

  • ArXiv Machine Learning (cs.LG)
  • ArXiv Artificial Intelligence (cs.AI)
  • ArXiv Computation and Language (cs.CL)

Community (Medium Priority)

  • Hacker News (AI filter)
  • Reddit r/MachineLearning
  • Reddit r/LocalLLaMA

Tech News (Medium Priority)

  • The Verge - AI
  • TechCrunch - AI

Scoring System

Each news item gets a score based on:

  1. Source Weight:

    • Official blogs: 10 points
    • Research papers: 8 points
    • Community: 6 points
    • Tech news: 5 points
  2. Keyword Boost:

    • High priority keywords (+5): GPT-5, Claude 4, Gemini, breakthrough, SOTA
    • Medium priority (+3): LLM, transformer, fine-tuning, RLHF
    • Low priority (+1): AI, machine learning, deep learning
  3. Recency Boost:

    • Last 24 hours: +10
    • Last 48 hours: +5
    • Last week: +2

Final Score = Base Weight + Keyword Boost + Recency Boost

Configuration

Edit config/feeds.yaml to customize sources:

feeds:
  official_blogs:
    - name: "Your Custom Blog"
      url: "https://your-blog.com/rss"
      weight: 10
      category: "official"

Edit scoring section to adjust keyword priorities:

scoring:
  keyword_boost:
    high_priority:
      - "your_important_term"

Output Format

Generated digest includes:

# AI News Digest - Last 7 Days

## Top 5 AI News

### 1. [Title] 🔥
**Source**: ... | **Published**: ... | **Score**: ...

[Summary]

**Key Points**:
- ...

**Why It Matters**: ...

**Read More**: [Link]

Advanced Usage

Filter by Time Range

"AI news from last 24 hours"
"지난 48시간 AI 소식"

Filter by Category

"Latest AI research papers only"
"Official blog posts only"

Custom Keywords

"Latest AI news, focus on 'agents' and 'reasoning'"

Tips

  1. Daily Routine: Run every morning to catch up on overnight news
  2. Filter Noise: Use “official + research only” for high-quality content
  3. Trend Detection: Run weekly to identify emerging topics
  4. Combine Skills: Use with ai-digest for deep dives into Top 5 articles
  5. Save for Later: All links preserved for future reference

Troubleshooting

Issue: “Python dependencies missing”

  • Solution: Run pip3 install feedparser pyyaml

Issue: “No results found”

  • Solution: Expand time range (“last 14 days”) or check internet connection

Issue: “RSS feed timeout”

  • Solution: Plugin automatically skips failed feeds and continues

Issue: “ModuleNotFoundError: feedparser”

  • Solution: Ensure Python 3 is installed and run pip3 install feedparser pyyaml

Integration

With ai-digest

1. "Get latest AI news"
2. "Analyze the #1 article in detail"
   → Uses ai-digest on top article URL

With learning-summary

After reading digest:
"Summarize what I learned"
→ Extracts key trends and insights

Future Enhancements

  • Email delivery integration
  • Slack/Discord webhooks
  • Scheduled daily/weekly digests (cron)
  • Trending topics detection
  • Sentiment analysis
  • Visual charts and graphs
  • Export to Notion/Obsidian
  • Personalized feeds based on interests

Performance

  • RSS Fetching: 5-15 seconds (parallel)
  • Scoring: <1 second
  • Total: ~15-20 seconds

Contributing

Found a bug or have a feature request? Open an issue at: https://github.com/JayKim88/claude-ai-engineering/issues

License

MIT License - See LICENSE file for details

Author

Jay Kim


Inspired by: QuantumExecBrief and existing RSS aggregators in the Claude Code ecosystem.