daily-ai-news

yyh211/claude-meta-skill · updated Apr 8, 2026

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$npx skills add https://github.com/yyh211/claude-meta-skill --skill daily-ai-news
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summary

Aggregates latest AI news from multiple sources with categorized summaries and direct article links.

  • Fetches content from 3-5 major AI news websites (VentureBeat, TechCrunch, The Verge, MIT Tech Review) and executes web search queries with date filters to capture breaking news
  • Organizes stories into five categories: Major Announcements, Research & Papers, Industry & Business, Tools & Applications, and Policy & Ethics
  • Filters for last 24-48 hours, removes duplicate
skill.md

Daily AI News Briefing

Aggregates the latest AI news from multiple sources and delivers concise summaries with direct links

When to Use This Skill

Activate this skill when the user:

  • Asks for today's AI news or latest AI developments
  • Requests a daily AI briefing or updates
  • Mentions wanting to know what's happening in AI
  • Asks for AI industry news, trends, or breakthroughs
  • Wants a summary of recent AI announcements
  • Says: "给我今天的AI资讯" (Give me today's AI news)
  • Says: "AI有什么新动态" (What's new in AI)

Workflow Overview

This skill uses a 4-phase workflow to gather, filter, categorize, and present AI news:

Phase 1: Information Gathering
  ├─ Direct website fetching (3-5 major AI news sites)
  └─ Web search with date filters
Phase 2: Content Filtering
  ├─ Keep: Last 24-48 hours, major announcements
  └─ Remove: Duplicates, minor updates, old content
Phase 3: Categorization
  └─ Organize into 5 categories
Phase 4: Output Formatting
  └─ Present with links and structure

Phase 1: Information Gathering

Step 1.1: Fetch from Primary AI News Sources

Use mcp__web_reader__webReader to fetch content from 3-5 major AI news websites:

Recommended Primary Sources (choose 3-5 per session):

Parameters:

  • return_format: markdown
  • with_images_summary: false (focus on text content)
  • timeout: 20 seconds per source

Step 1.2: Execute Web Search Queries

Use WebSearch with date-filtered queries to discover additional news:

Query Template (adjust dates dynamically):

General: "AI news today" OR "artificial intelligence breakthrough" after:[2025-12-23]
Research: "AI research paper" OR "machine learning breakthrough" after:[2025-12-23]
Industry: "AI startup funding" OR "AI company news" after:[2025-12-23]
Products: "AI application launch" OR "new AI tool" after:[2025-12-23]

Best Practices:

  • Always use current date or yesterday's date in filters
  • Execute 2-3 queries across different categories
  • Limit to top 10-15 results per query
  • Prioritize sources from last 24-48 hours

Step 1.3: Fetch Full Articles

For the top 10-15 most relevant stories from search results:

  • Extract URLs from search results
  • Use mcp__web_reader__webReader to fetch full article content
  • This ensures accurate summarization vs. just using snippets

Phase 2: Content Filtering

Filter Criteria

Keep:

  • News from last 24-48 hours (preferably today)
  • Major announcements (product launches, model releases, research breakthroughs)
  • Industry developments (funding, partnerships, regulations, acquisitions)
  • Technical advances (new models, techniques, benchmarks)
  • Significant company updates (OpenAI, Google, Anthropic, etc.)

Remove:

  • Duplicate stories (same news across multiple sources)
  • Minor updates or marketing fluff
  • Content older than 3 days unless highly significant
  • Non-AI content or tangentially related articles

Deduplication Strategy

When the same story appears in multiple sources:

  • Keep the most comprehensive version
  • Note alternative sources in the summary
  • Prioritize authoritative sources (company blogs > news aggregators)

Phase 3: Categorization

Organize news into 5 categories:

🔥 Major Announcements

  • Product launches (new AI tools, services, features)
  • Model releases (GPT updates, Claude features, Gemini capabilities)
  • Major company announcements (OpenAI, Google, Anthropic, Microsoft, Meta)

🔬 Research & Papers

  • Academic breakthroughs
  • New research papers from top conferences
  • Novel techniques or methodologies
  • Benchmark achievements

💰 Industry & Business

  • Funding rounds and investments
  • Mergers and acquisitions
  • Partnerships and collaborations
  • Market trends and analysis

🛠️ Tools & Applications

  • New AI tools and frameworks
  • Practical AI applications
  • Open source releases
  • Developer resources

🌍 Policy & Ethics

  • AI regulations and policies
  • Safety and ethics discussions
  • Social impact studies
  • Government initiatives

Phase 4: Output Formatting

Use the following template for consistent output:

# 📰 Daily AI News Briefing

**Date**: [Current Date, e.g., December 24, 2025]
**Sources**: [X] articles from [Y] sources
**Coverage**: Last 24 hours

---

## 🔥 Major Announcements

### [Headline 1]

**Summary**: [One-sentence overview of the news]

**Key Points**:
- [Important detail 1]
- [Important detail 2]
- [Important detail 3]

**Impact**: [Why this matters - 1 sentence]

📅 **Source**: [Publication Name] • [Publication Date]
🔗 **Link**: [URL to original article]

---

### [Headline 2]

[Same format as above]

---

## 🔬 Research & Papers

### [Headline 3]

[Same format as above]

---

## 💰 Industry & Business

### [Headline 4]

[Same format as above]

---

## 🛠️ Tools & Applications

### [Headline 5]

[Same format as above]

---

## 🌍 Policy & Ethics

### [Headline 6]

[Same format as above]

---

## 🎯 Key Takeaways

1. [The biggest news of the day - 1 sentence]
2. [Second most important development - 1 sentence]
3. [An emerging trend worth watching - 1 sentence]

---

**Generated on**: [Timestamp]
**Next update**: Check back tomorrow for the latest AI news

Customization Options

After providing the initial briefing, offer customization:

1. Focus Areas

"Would you like me to focus on specific topics?"

  • Research papers only
  • Product launches and tools
  • Industry news and funding
  • Specific companies (OpenAI/Google/Anthropic)
  • Technical tutorials and guides

2. Depth Level

"How detailed should I go?"

  • Brief: Headlines only (2-3 bullet points per story)
  • Standard: Summaries + key points (default)
  • Deep: Include analysis and implications

3. Time Range

"What timeframe?"

  • Last 24 hours (default)
  • Last 3 days
  • Last week
  • Custom range

4. Format Preference

"How would you like this organized?"

  • By category (default)
  • Chronological
  • By company
  • By significance

Follow-up Interactions

User: "Tell me more about [story X]"

Action: Use mcp__web_reader__webReader to fetch the full article, provide detailed summary + analysis

User: "What are experts saying about [topic Y]?"

Action: Search for expert opinions, Twitter reactions, analysis pieces

User: "Find similar stories to [story Z]"

Action: Search related topics, provide comparative summary

User: "Only show research papers"

Action: Filter and reorganize output, exclude industry news

Quality Standards

Validation Checklist

  • All links are valid and accessible
  • No duplicate stories across categories
  • All items have timestamps (preferably today)
  • Summaries are accurate (not hallucinated)
  • Links lead to original sources, not aggregators
  • Mix of sources (not all from one publication)
  • Balance between hype and substance

Error Handling

  • If webReader fails for a URL → Skip and try next source
  • If search returns no results → Expand date range or try different query
  • If too many results → Increase threshold for significance
  • If content is paywalled → Use available excerpt and note limitation

Examples

Example 1: Basic Request

User: "给我今天的AI资讯"

AI Response: [Executes 4-phase workflow and presents formatted briefing with 5-10 stories across categories]


Example 2: Time-specific Request

User: "What's new in AI this week?"

AI Response: [Adjusts date filters to last 7 days, presents weekly summary]


Example 3: Category-specific Request

User: "Any updates on AI research?"

AI Response: [Focuses on Research & Papers category, includes recent papers and breakthroughs]


Example 4: Follow-up Deep Dive

User: "Tell me more about the GPT-5 announcement"

AI Response: [Fetches full article, provides detailed summary, offers to find expert reactions]

Additional Resources

For comprehensive lists of news sources, search queries, and output templates, refer to:

  • references/news_sources.md - Complete database of AI news sources
  • references/search_queries.md - Search query templates by category
  • references/output_templates.md - Alternative output format templates
how to use daily-ai-news

How to use daily-ai-news on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add daily-ai-news
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/yyh211/claude-meta-skill --skill daily-ai-news

The skills CLI fetches daily-ai-news from GitHub repository yyh211/claude-meta-skill and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/daily-ai-news

Reload or restart Cursor to activate daily-ai-news. Access the skill through slash commands (e.g., /daily-ai-news) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.538 reviews
  • Chaitanya Patil· Dec 28, 2024

    Keeps context tight: daily-ai-news is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Isabella Mehta· Dec 28, 2024

    We added daily-ai-news from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Soo Thomas· Dec 28, 2024

    Keeps context tight: daily-ai-news is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Pratham Ware· Dec 24, 2024

    daily-ai-news fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kwame Anderson· Dec 4, 2024

    daily-ai-news is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Anika Jackson· Nov 23, 2024

    Solid pick for teams standardizing on skills: daily-ai-news is focused, and the summary matches what you get after install.

  • Piyush G· Nov 19, 2024

    daily-ai-news has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Arya Chen· Nov 19, 2024

    daily-ai-news has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Benjamin Anderson· Oct 14, 2024

    daily-ai-news has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Oct 10, 2024

    Solid pick for teams standardizing on skills: daily-ai-news is focused, and the summary matches what you get after install.

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