news-aggregator-skill

name news-aggregator-skill description Comprehensive news aggregator that fetches, filters, and deeply analyzes real-time content from 44+ sources including Hacker News, Lobsters, Dev.to, GitHub, arXiv, Hugging Face Papers, AIHOT, TLDR AI, Import AI, BBC, The Guardian, Al Jazeera, France 24, Reuters fallback, AI Newsletters, WallStreetCN, Weibo, 少数派, InfoQ 中文, Podcasts, and user-defined OPML feeds. Use when user requests 'daily scans', 'tech news', 'finance updates', 'AI briefings', 'international news', 'deep analysis', or says '如意如意' to open the interactive menu. News Aggregator Skill Fetch real-time hot news from 44+ sources (including international news + AI curated aggregators + user-defined OPML feeds), generate deep analysis reports in Chinese. 🔄 Universal Workflow (3 Steps) Every news request follows the same workflow, regardless of source or combination: Step 1: Fetch Data # Single source python3 scripts/fetch_news.py -- source <source_key> --no-save # Multiple sources (comma-separated) python3 scripts/fetch_news.py -- source hackernews,github,wallstreetcn --no-save # All sources (broad scan) python3 scripts/fetch_news.py -- source all -- limit 15 --deep --no-save # With keyword filter (auto-expand: "AI" → "AI,LLM,GPT,Claude,Agent,RAG") python3 scripts/fetch_news.py -- source hackernews --keyword "AI,LLM,GPT" --deep --no-save Step 2: Generate Report Read the output JSON and format every item using the Unified Report Template below. Translate all content to Simplified Chinese . Step 3: Save & Present Save the report to reports/YYYY-MM-DD/<source>_report.md , then display the full content to the user. 📰 Unified Report Template All sources use this single template. Show/hide optional fields based on data availability. #### N. [ 标题 (中文翻译) ]( https://original-url.com ) - **Source** : 源名 | **Time** : 时间 | **Heat** : 🔥 热度值 - **Links** : [ Discussion ]( hn_url ) | [ GitHub ]( gh_url ) ← 仅在数据存在时显示 - **Summary** : 一句话中文摘要。 - **Deep Dive** : 💡 **Insight** : 深度分析（背景、影响、技术价值）。 Source-Specific Adaptations Only the differences from the universal template: Source Adaptation Hacker News MUST include [Discussion](hn_url) link GitHub Use 🌟 Stars for Heat, add Lang field, add #Tags in Deep Dive Hugging Face Use 🔥 +N upvotes for Heat, include [GitHub](url) if present, write 深度解读 (not just translate abstract) Weibo Preserve exact heat text (e.g. "108万") AIHOT summary 已是中文编辑稿， 直接引用 不要再翻译；Heat 字段为空也别造数据；保留 推荐理由 风格的一句话点评 TLDR AI 单条标题往往是多主题混合（ Topic A 💻, Topic B ⚡, Topic C ⛪ ）， 拆成 bullet 列出每个主题 ； summary 是 HTML 段落，需要拆出每个主题对应的一两句概述 Import AI 周刊长文，标题形如 Import AI 458: 主题1; 主题2; 主题3 。 建议默认配 --deep ，否则 RSS summary 只是开头几句；Deep Dive 直接提炼 Jack Clark 的核心观点而非平铺事实 International News MUST use the Unified Report Template for every item；只使用最近 24h RSS 条目，不用更早新闻 Smart Fill；英文标题与摘要翻译成简体中文，保留原始媒体名与链接；同一事件多家媒体重复时可合并观点但不能合并链接 Reuters reuters 使用 Google News RSS 的 site:reuters.com fallback；报告里保留 Reuters (Google News fallback) source，不要写成官方公开 RSS 🛠️ Tools fetch_news.py Arg Description Default --source Source key(s), comma-separated. See table below. all --limit Max items per source 15 --keyword Comma-separated keyword filter None --deep Download article text for richer analysis Off --save Force save to reports dir Auto for single source --outdir Custom output directory reports/YYYY-MM-DD/ Available Sources (44+ with user OPML) Category Key Name Global News hackernews Hacker News 36kr 36氪 wallstreetcn 华尔街见闻 tencent 腾讯新闻 weibo 微博热搜 v2ex V2EX producthunt Product Hunt github GitHub Trending Tech Community (v2) lobsters Lobsters devto Dev.to AI/Tech huggingface HF Daily Papers arxiv arXiv (cs.AI/cs.CL/cs.LG, v2) ai_newsletters All AI Newsletters (aggregate) bensbites Ben's Bites interconnects Interconnects (Nathan Lambert) oneusefulthing One Useful Thing (Ethan Mollick) chinai ChinAI (Jeffrey Ding) memia Memia aitoroi AI to ROI kdnuggets KDnuggets Chinese (v2) sspai 少数派 infoq_cn InfoQ 中文站（RSS 只给标题， 推荐配 --deep 拿正文） AI Curated (v3) aihot AIHOT 中文 AI 精选（跨源 + 中文编辑稿） tldr_ai TLDR AI 英文日刊 import_ai Import AI by Jack Clark 周刊（ 推荐 --deep ） International News international 最近 24h 国际新闻聚合（BBC / Guardian / Al Jazeera / France 24 / Reuters fallback） bbc_top BBC Top News (24h) bbc_world BBC World (24h) bbc_chinese BBC 中文 (24h) guardian_world The Guardian World (24h) aljazeera Al Jazeera (24h) france24 France 24 (24h) reuters Reuters via Google News RSS fallback (24h) Podcasts podcasts All Podcasts (aggregate) lexfridman Lex Fridman 80000hours 80,000 Hours latentspace Latent Space Essays essays All Essays (aggregate) paulgraham Paul Graham waitbutwhy Wait But Why jamesclear James Clear farnamstreet Farnam Street scottyoung Scott Young dankoe Dan Koe Custom (v2) user Your OPML feeds (see below) 自定义订阅源 (User OPML) 把你常看的 RSS/Atom 源写进 OPML， --source user 即可统一抓取。 1. 放置 OPML 文件 （按优先级查找）： ~/.config/news-aggregator/user_sources.opml （推荐，跨 skill 复用） <skill_root>/user_sources.opml （本仓库内） 2. 文件格式 ：标准 OPML 2.0，可直接从 Feedly / Inoreader / NetNewsWire 导出。参考 user_sources.opml.example ： < outline type = "rss" text = "Simon Willison" title = "Simon Willison" xmlUrl = "https://simonwillison.net/atom/everything/" /> 只 xmlUrl 必填，其它可选。 3. 运行 ： python3 scripts/fetch_news.py --source user --limit 15 daily_briefing.py (Morning Routines) Pre-configured multi-source profiles: python3 scripts/daily_briefing.py --profile <profile> Profile Sources Instruction File general HN, 36Kr, GitHub, Weibo, PH, WallStreetCN instructions/briefing_general.md finance WallStreetCN, 36Kr, Tencent instructions/briefing_finance.md tech GitHub, HN, Product Hunt instructions/briefing_tech.md social Weibo, V2EX, Tencent instructions/briefing_social.md ai_daily HF Papers, AI Newsletters instructions/briefing_ai_daily.md reading_list Essays, Podcasts (Use universal template) Workflow : Execute script → Read corresponding instruction file → Generate report following both the instruction file AND the universal template. ⚠️ Rules (Strict) Language : ALL output in Simplified Chinese (简体中文) . Keep well-known English proper nouns (ChatGPT, Python, etc.). Time : MANDATORY field. Never skip. If missing in JSON, mark as "Unknown Time". Preserve "Real-time" / "Today" / "Hot" as-is. Anti-Hallucination : Only use data from the JSON. Never invent news items. Use simple SVO sentences. Do not fabricate causal relationships. Smart Keyword Expansion : When user says "AI" → auto-expand to "AI,LLM,GPT,Claude,Agent,RAG,DeepSeek" . Similar expansions for other domains. Smart Fill : If results < 5 items in a time window, supplement with high-value items from wider range. Mark supplementary items with ⚠️. Exception : International News sources are a hard 24h window; do not supplement with older items. Save : Always save report to reports/YYYY-MM-DD/ before displaying. 📋 Interactive Menu When the user says "如意如意" or asks for "menu/help": Read templates.md Display the menu Execute the user's selection using the Universal Workflow above Requirements Python 3.8+, pip install -r requirements.txt Playwright (for HF Papers & Ben's Bites): playwright install chromium