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.

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🔄 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.

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📰 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

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🛠️ 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

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.

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⚠️ Rules (Strict)

1. Language: ALL output in Simplified Chinese (简体中文). Keep well-known English proper nouns (ChatGPT, Python, etc.).
2. Time: MANDATORY field. Never skip. If missing in JSON, mark as "Unknown Time". Preserve "Real-time" / "Today" / "Hot" as-is.
3. Anti-Hallucination: Only use data from the JSON. Never invent news items. Use simple SVO sentences. Do not fabricate causal relationships.
4. Smart Keyword Expansion: When user says "AI" → auto-expand to "AI,LLM,GPT,Claude,Agent,RAG,DeepSeek". Similar expansions for other domains.
5. 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.
6. Save: Always save report to reports/YYYY-MM-DD/ before displaying.

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📋 Interactive Menu

When the user says "如意如意" or asks for "menu/help":

1. Read templates.md
2. Display the menu
3. Execute the user's selection using the Universal Workflow above

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Requirements

• Python 3.8+, pip install -r requirements.txt
• Playwright (for HF Papers & Ben's Bites): playwright install chromium