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: markdownwith_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__webReaderto 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:
markdown# 📰 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
webReaderfails 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 sourcesreferences/search_queries.md- Search query templates by categoryreferences/output_templates.md- Alternative output format templates
