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