Token导航 LogoToken导航TokenDH.com
研究检索external-servicegithub未标认证来源可访问clear审计提醒

daily-ai-news每日 AI 新闻

Agent Skill

daily-ai-news 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

49,440

周安装

2,023

GitHub Stars

259

下载量

15,520
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:daily-ai-news(每日 AI 新闻)
来源仓库:https://github.com/yyh211/claude-meta-skill
仓库路径:skills/daily-ai-news
安装命令:
npx skills add https://github.com/yyh211/claude-meta-skill --skill daily-ai-news
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/yyh211/claude-meta-skill --skill daily-ai-news

简介

通过分类摘要和直接文章链接聚合来自多个来源的最新人工智能新闻。

  • 从 3-5 个主要 AI 新闻网站(VentureBeat、TechCrunch、The Verge、MIT Tech Review)获取内容,并使用日期过滤器执行网络搜索查询以捕获突发新闻
  • 将故事分为五类:主要公告、研究与论文、工业与商业、工具与应用以及政策与道德
  • 过滤过去 24-48 小时、删除重复项并优先考虑重大开发,例如产品发布、模型发布和融资公告
  • 提供焦点区域、深度级别、时间范围和输出格式的定制选项;支持后续查询以更深入地了解特定故事

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):

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenCode

29.75%
按下载量换算4,617

Cursor

21.98%
按下载量换算3,411

Claude Code

17.62%
按下载量换算2,735

Gemini CLI

13.1%
按下载量换算2,033

Antigravity

7.57%
按下载量换算1,175

trae

3.46%
按下载量换算537

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

继续浏览同类 Skills