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Ai News Hub

v2.3.1

AI新闻阅读助手。100+ RSS源并发抓取、兴趣评分、跨天去重、统一预取。智能聚合AI/技术新闻、arXiv论文、GitHub热门项目、AI公司动态。支持日报/周报生成、关键词筛选、分类订阅。

0· 67·0 current·0 all-time
bytravelinglight@kingcodingking

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for kingcodingking/ai-news-hub.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Ai News Hub" (kingcodingking/ai-news-hub) from ClawHub.
Skill page: https://clawhub.ai/kingcodingking/ai-news-hub
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required binaries: python3
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install ai-news-hub

ClawHub CLI

Package manager switcher

npx clawhub@latest install ai-news-hub
Security Scan
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Purpose & Capability
Name/description match the included scripts: rss_aggregator.py, arxiv_papers.py, github_trending.py, summarize_url.py and a rss_sources.json of feeds. Requesting only python3 is coherent for a CLI Python aggregator.
Instruction Scope
Runtime instructions tell the agent to fetch many external RSS endpoints, arXiv, GitHub Trending and optionally call a third‑party 'Jina Reader' (r.jina.ai) to prefetch/parse article content. Those network calls are expected for this skill but mean the agent will make many outbound HTTP requests and (if Jina is used) send article URLs/content to a third party—this is a privacy/telemetry consideration rather than hidden malice.
Install Mechanism
There is no automated install spec (instruction-only). That lowers risk. However _meta.json lists 'feedparser' as a dependency while SKILL.md claims 'pure standard library' — an inconsistency to resolve before assuming zero-install runtime.
Credentials
The skill does not declare or require credentials (good). It does respect HTTP_PROXY/http_proxy and INSTALL.md mentions THREAD_POOL_SIZE, and some files reference optional dependency 'feedparser' — these environment interactions are reasonable but should be noted. No unrelated secrets or system paths are requested.
Persistence & Privilege
The skill does not request permanent presence (always:false) and does not attempt to modify other skills or system config. It writes a local cache file (.rss_cache.json) in its script directory which is normal for a feed aggregator.
What to consider before installing
This skill appears to do what it says (aggregate RSS, arXiv, GitHub trending and summarize content), but before installing or enabling it consider the following: - Privacy: summarize_url.py can call r.jina.ai (Jina Reader). If you enable that option the URL/content will be sent to a third‑party service; disable --jina if you want to avoid that. - Outbound network: the aggregator will perform many HTTP requests to feeds and GitHub; run it where that traffic is acceptable and rate-limits are tolerated. - Inconsistencies: metadata lists feedparser as a dependency while SKILL.md claims only stdlib; verify and, if needed, install feedparser or run tests locally. - Incomplete/quirky tests: tests import a module name (rss_aggregator_fast) that doesn't match the main script name; the test suite looks brittle and there are truncated file previews in the package — review the repo files locally to ensure no missing code before relying on it. - Local writes: it writes a cache file (.rss_cache.json) next to the scripts — if you need ephemeral runs, run from a temp directory or container. - Third‑party feed URLs: some entries use raw.githubusercontent.com or other mirrors for RSS feeds; review rss_sources.json and remove any feeds you do not trust. Recommended actions: inspect the repo locally, run the scripts in an isolated environment (container or VM), avoid enabling the Jina Reader option if you care about content confidentiality, and confirm dependency requirements (feedparser) before running in production.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

📰 Clawdis
OSLinux · macOS · Windows
Binspython3
latestvk970ns252d01r122n8kcjeqvms84vrb6
67downloads
0stars
2versions
Updated 2w ago
v2.3.1
MIT-0
Linux, macOS, Windows

AI News Hub — AI/技术新闻高性能聚合引擎

并发抓取 100+ RSS 源,12秒完成,支持 ETag/Last-Modified 缓存、日期过滤。

Setup

确保 Python 3.8+ 可用,无需额外依赖(纯标准库)。

When to Use

用户需要查看 AI/技术新闻、技术趋势、最新论文、GitHub 热门项目、AI 公司动态时使用。

触发关键词:

  • "AI 新闻"、"技术新闻"、"今天有什么新闻"、"科技早报"
  • "最新论文"、"arXiv"、"AI 研究"、"论文摘要"
  • "GitHub 热门"、"趋势项目"、"热门仓库"
  • "OpenAI 动态"、"Anthropic 更新"、"Claude更新"
  • "多智能体"、"LLM"、"大模型"、"Agent"
  • "机器学习"、"深度学习"、"NLP"、"计算机视觉"
  • "行业动态"、"投资融资"、"产品发布"

用户意图识别:

  • 快速了解:今天有什么AI新闻?
  • 深度追踪:OpenAI最近有什么更新?
  • 研究方向:多智能体的最新论文有哪些?
  • 项目发现:GitHub上有什么好的AI项目?
  • 特定关键词:搜索"多智能体"相关的新闻

用户交互场景

场景1:快速获取今日AI新闻

用户:今天有什么AI新闻?
助手:📰 今日AI新闻速递

━━━━━━━━━━━━━━━━━━━━━━━━━━
【公司动态】
• OpenAI 发布 GPT-5 预览版 | 2小时前
• Anthropic Claude 4 性能提升 40% | 5小时前
• Google DeepMind 发布新论文 | 8小时前

【论文发布】
• arXiv: 多智能体协作综述(热榜第一)
• HuggingFace: 新开源模型 Llama-4

【GitHub热门】
• langchain/langchain: 🔥 本周最热 +1200 stars
• microsoft/autogen: 多智能体框架 +800 stars

【投资融资】
• Mistral AI 完成6亿美元融资 | 估值60亿

━━━━━━━━━━━━━━━━━━━━━━━━━━
数据来源:100+ RSS源 | 聚合时间:2026-04-14

场景2:特定公司动态追踪

用户:OpenAI 最近有什么动态?
助手:🏢 OpenAI 近期动态追踪

━━━━━━━━━━━━━━━━━━━━━━━━━━
📅 最近7天更新(共12条)

【产品发布】
✅ GPT-5 预览版发布(2026-04-12)
✅ Sora 升级:支持高清视频生成(2026-04-10)

【技术博客】
✅ 推理能力优化新突破(2026-04-09)
✅ 多模态能力增强(2026-04-08)

【商业动态】
✅ 与微软深化合作(2026-04-07)
✅ 企业版新增功能(2026-04-06)

━━━━━━━━━━━━━━━━━━━━━━━━━━
数据来源:OpenAI Blog +媒体报道

场景3:arXiv论文搜索

用户:有什么最新的多智能体论文?
助手:🔬 arXiv 最新论文:多智能体专题

━━━━━━━━━━━━━━━━━━━━━━━━━━
【Top 5 热门论文】

1️⃣ Multi-Agent Collaboration: A Survey
   • 作者:Zhang et al.
   • 发布:2026-04-13
   • 引用:127 | ⭐ 热度:95
   • 摘要:系统综述多智能体协作的最新进展...

2️⃣ Efficient Multi-Agent Systems
   • 作者:Li et al.
   • 发布:2026-04-12
   • 引用:89 | ⭐ 热度:92
   • 摘要:提出高效的多智能体通信协议...

3️⃣ Autonomous Agent Teams
   • 作者:Wang et al.
   • 发布:2026-04-11
   • 引用:76 | ⭐ 热度:88
   • 摘要:实现完全自主的智能体团队...

━━━━━━━━━━━━━━━━━━━━━━━━━━
📝 查看论文摘要,回复编号获取详情

场景4:GitHub热门项目发现

用户:GitHub上有什么热门的AI项目?
助手:🔥 GitHub AI项目热门榜

━━━━━━━━━━━━━━━━━━━━━━━━━━
【本周Top 10】

1. 🔥 langchain/langchain
   • Stars: +1,234 ⭐
   • 描述:LLM应用开发框架
   • 语言:Python
   • 更新:5小时前

2. ⚡ microsoft/autogen
   • Stars: +876 ⭐
   • 描述:多智能体对话框架
   • 语言:Python
   • 更新:3小时前

3. 🚀 vllm-project/vllm
   • Stars: +654 ⭐
   • 描述:LLM推理加速引擎
   • 语言:Python
   • 更新:6小时前

━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 趋势分析:多智能体框架本周最受关注

场景5:关键词筛选

用户:搜索"多智能体"相关的新闻
助手:🔍 关键词搜索:多智能体

━━━━━━━━━━━━━━━━━━━━━━━━━━
【找到 8 条相关新闻】

📰 新闻资讯
• 多智能体协作技术突破 | MIT Tech Review
• 企业级多智能体应用案例 | The Verge
• 多智能体工具链兴起 | InfoQ

🔬 论文研究
• Multi-Agent Survey | arXiv热榜
• 协作机制优化论文 | arXiv新增

💻 项目动态
• autogen 新版本发布 | GitHub Trending
• swarm 多智能体库更新 | GitHub Trending

━━━━━━━━━━━━━━━━━━━━━━━━━━
时间范围:最近7天 | 相关度评分:>70

场景6:生成日报/周报

用户:生成今天的AI早报
助手:📱 AI科技早报

━━━━━━━━━━━━━━━━━━━━━━━━━━
📅 2026年4月14日 星期一

【头条】
• OpenAI GPT-5预览版震撼发布
• Anthropic融资60亿美元估值创新高

【技术前沿】
• 多智能体协作研究综述
• LLaMA 4开源,性能媲美GPT-4
• 3D生成模型迎来重大突破

【商业动态】
• AI基础设施投资热潮持续
• 企业AI应用落地加速

【GitHub精选】
• langchain 本周最热 +1234 stars
• autogen 多智能体框架受关注

━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 数据统计:100+源 | 去重后32条
⏱️ 聚合耗时:12.5秒

Architecture

ai-news-hub/
├── scripts/
│   ├── rss_aggregator.py      # 核心 RSS 抓取器
│   ├── rss_sources.json       # 100+ RSS 源配置
│   ├── arxiv_papers.py        # arXiv 论文搜索
│   ├── github_trending.py     # GitHub 热门项目
│   └── summarize_url.py       # 文章摘要
└── SKILL.md                   # 本文件

Data Sources

分类源数内容
company16OpenAI, Anthropic, Google, Meta, NVIDIA, Apple, Mistral 等官方博客
papers6arXiv AI/ML/NLP/CV, HuggingFace Daily Papers, BAIR
media16MIT Tech Review, TechCrunch, Wired, The Verge, VentureBeat 等
newsletter15Simon Willison, Lilian Weng, Andrew Ng, Karpathy 等专家
community12HN, GitHub Trending, Product Hunt, V2EX 等
cn_media5机器之心, 量子位, 36氪, 少数派, InfoQ
ai-agent5LangChain, LlamaIndex, Mem0, Ollama, vLLM 博客
twitter10Sam Altman, Karpathy, LeCun, Hassabis 等 AI 领袖

Core Commands

RSS 聚合

# 抓取所有源(最近3天新闻)
python3 scripts/rss_aggregator.py --category all --days 3 --limit 10

# 只看公司博客
python3 scripts/rss_aggregator.py --category company --days 1 --limit 5

# 只看中文媒体
python3 scripts/rss_aggregator.py --category cn_media --days 3 --limit 10

# AI Agent 相关
python3 scripts/rss_aggregator.py --category ai-agent --days 7 --limit 10

# 输出 JSON 格式
python3 scripts/rss_aggregator.py --category all --days 1 --json

arXiv 论文

# 最新 AI 论文(按热度排序)
python3 scripts/arxiv_papers.py --limit 5 --top 10

# 搜索特定主题
python3 scripts/arxiv_papers.py --query "multi-agent" --top 5

GitHub Trending

# AI 相关热门项目(今日)
python3 scripts/github_trending.py --ai-only

# 本周热门
python3 scripts/github_trending.py --since weekly

Core Rules

1. 优先使用 --days 参数

默认抓取最近 N 天的新闻,避免获取过期内容:

  • 日报:--days 1
  • 周报:--days 7
  • 月报:--days 30

2. 分类选择策略

用户需求推荐分类
公司动态--category company
技术论文--category papers
中文资讯--category cn_media
社区趋势--category community
AI Agent--category ai-agent

3. 缓存机制

  • 首次抓取后自动缓存(ETag/Last-Modified)
  • 缓存有效期 1 小时
  • 重复抓取秒级完成

Configuration

编辑 scripts/rss_sources.json 添加/删除 RSS 源:

{
  "name": "OpenAI Blog",
  "url": "https://openai.com/blog/rss.xml",
  "category": "company"
}

更新日志

v2.3.0 (2026-04-14) - 用户体验优化

  • ✅ 新增完整的用户交互场景(6个典型场景)
  • ✅ 优化输出格式:结构化展示、图标标注、分隔线美化
  • ✅ 新增关键词筛选功能(精准查找相关内容)
  • ✅ 新增分类订阅系统(支持按类别订阅)
  • ✅ 新增日报/周报生成功能(格式化报告输出)
  • ✅ 增强兴趣评分算法(智能计算相关性)
  • ✅ 性能优化:100源聚合时间缩短至10.2秒
  • ✅ 完善跨天去重机制
  • ✅ 增加趋势分析功能(热门榜、增长趋势)

v2.2.0

  • ✅ 统一预取缓存机制
  • ✅ 兴趣评分算法(基于关键词匹配)
  • ✅ 跨天去重
  • ✅ 仓库结构重构

v2.1.0

  • ✅ 10线程并发抓取
  • ✅ ETag/Last-Modified缓存
  • ✅ 15秒快速超时
  • ✅ 1小时TTL缓存持久化

v2.0.0

  • ✅ 初始版本
  • ✅ 支持70+ RSS源
  • ✅ arXiv论文搜索
  • ✅ GitHub Trending

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