daily-ai-news

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):

VentureBeat AI: https://venturebeat.com/category/ai/

TechCrunch AI: https://techcrunch.com/category/artificial-intelligence/

The Verge AI: https://www.theverge.com/ai-artificial-intelligence

MIT Technology Review AI: https://www.technologyreview.com/topic/artificial-intelligence/

AI News: https://artificialintelligence-news.com/

AI Hub Today: https://ai.hubtoday.app/

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