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:

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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
• INLINECODE2: false (focus on text content)
• INLINECODE3: 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):
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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:

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Customization Options

After providing the initial briefing, offer customization:

1. Focus Areas

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

2. Depth Level

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

3. Time Range

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

4. Format Preference

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

Follow-up Interactions

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

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

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

User: "Only show research papers"

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
• INLINECODE9 - Search query templates by category
• INLINECODE10 - Alternative output format templates