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Agent Skill · 待分类

daily-ai-news(每日 AI 新闻)

daily-ai-news 用于补充待分类相关能力,适合在 Local Agent 中需要让 Agent 承接待分类相关任务时使用。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。

daily-ai-news 是待分类类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为需要联网;许可证信息还不明确,暂无第三方扫描结果,按安装量在待分类类的 11,209 个 Skill 里排第 7,661。

总安装 349周安装 14下载 113核验 2026-05-01
待分类需要联网unknown未标认证来源可访问许可证需确认审计未展示Local Agent

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
许可证
unknown

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://skills.volces.com
仓库路径:daily-ai-news
安装命令:
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。当前暂无明确安装命令,请以来源页面说明为准。

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

daily-ai-news 用于补充待分类相关能力,适配 Local Agent 中的待分类任务场景。它协助 Agent 处理与待分类相关的信息整合与任务流转需求。可参考来源仓库和原始文档进一步了解功能细节与使用限制。安装前务必确认权限边界和维护状态,防范潜在的文件读写或联网风险。

当前安装方式未知,建议人工验证部署路径与依赖关系。

来源仓库内路径:daily-ai-news

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Local Agent;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 daily-ai-news。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

daily-ai-news 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 daily-ai-news。

daily-ai-news 支持哪些 AI 工具?

公开资料标注支持 Local Agent。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

daily-ai-news 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

daily-ai-news 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

daily-ai-news 用的人多吗?

公开数据是累计安装 349 次,近一周安装 14 次,下载 113 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

daily-ai-news 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Local Agent,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
daily-ai-news

每日 AI 新闻 · 本页

349—需要联网未明确未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

Local Agent

80.02%
按下载量换算90

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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