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Agent Skill · 研究检索

daily-ai-news-skill-litiao(每日 AI 新闻技能丽条)

daily-ai-news-skill-litiao 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

daily-ai-news-skill-litiao 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 18,169。

总安装 6,229周安装 252GitHub Stars 公开资料未说明下载 1,956核验 2026-05-01

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。
GitHub
许可证
MIT-0
版本
1.0.0

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-skill-litiao(每日 AI 新闻技能丽条)
来源仓库:https://github.com/litiao1224/daily-ai-news-skill-litiao
安装命令:
openclaw skills install daily-ai-news-skill-litiao
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install daily-ai-news-skill-litiao

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

聚合多来源人工智能新闻,结合Tavily API与Brave Search生成每日摘要。适用于追踪AI领域动态、筛选热点资讯或获取行业趋势分析。支持自定义关键词检索,输出结构化内容便于快速阅读。安装命令:openclaw skills install daily-ai-news-skill-litiao。

使用前请确保已配置相关搜索API密钥,并注意数据更新频率限制。

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 OpenClaw;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

    可以直接复制的命令是 openclaw skills install daily-ai-news-skill-litiao;命令里的占位符换成自己的路径或密钥再执行。

  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

    它需要调用外部服务,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-skill-litiao 怎么安装?

在终端执行 openclaw skills install daily-ai-news-skill-litiao。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

daily-ai-news-skill-litiao 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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-skill-litiao 需要什么权限?

权限级别是调用外部服务。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。

daily-ai-news-skill-litiao 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

daily-ai-news-skill-litiao 用的人多吗?

公开数据是累计安装 6,229 次,近一周安装 252 次,下载 1,956 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-skill-litiao 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
daily-ai-news-skill-litiao

每日 AI 新闻技能丽条 · 本页

6,229—调用外部服务MIT-0有提醒

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

name
daily-ai-news-skill-litiao
description
Aggregates and summarizes the latest AI news from multiple sources including AI news websites and web search. Uses Tavily API (preferred) or Brave Search (fallback). Provides concise news briefs with direct links to original articles. Activates when user asks for 'today's AI news', 'AI updates', 'latest AI developments', or mentions wanting a 'daily AI briefing'.
metadata
{"clawdbot":{"emoji":"📰","requires":{"env":["TAVILY_API_KEY"]}}}

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

Preferred: Use Tavily Search (if TAVILY_API_KEY is available):

cd ~/.openclaw/workspace/skills/tavily-search-litiao

# General AI news
node scripts/search.mjs "AI news today" --topic news --days 1 -n 15

# Research papers
node scripts/search.mjs "AI research paper machine learning breakthrough" --topic news --days 3 -n 10

# Industry news
node scripts/search.mjs "AI startup funding company news" --topic news --days 3 -n 10

# Product launches
node scripts/search.mjs "AI application launch new tool" --topic news --days 3 -n 10

Fallback: Use Brave WebSearch (via web_search tool):

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
  • Tavily advantage: Better news clustering, cleaner snippets, --topic news optimized for current events

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

OpenClaw

87.44%
按下载量换算1,710

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

调用外部服务

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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