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
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 sources
- references/search_queries.md - Search query templates by category
- references/output_templates.md - Alternative output format templates