news-aggregator-skill
Comprehensive news aggregator that fetches, filters, and deeply analyzes real-time content from 8 major sources: Hacker News, GitHub Trending, Product Hunt, 36Kr, Tencent News, WallStreetCN, V2EX, and Weibo. Best for 'daily scans', 'tech news briefings', 'finance updates', and 'deep interpretations' of hot topics.
Install
mkdir -p .claude/skills/news-aggregator-skill && curl -L -o skill.zip "https://mcp.directory/api/skills/download/2459" && unzip -o skill.zip -d .claude/skills/news-aggregator-skill && rm skill.zipInstalls to .claude/skills/news-aggregator-skill
About this skill
News Aggregator Skill
Fetch real-time hot news from multiple sources.
Tools
fetch_news.py
Usage:
### Single Source (Limit 10)
```bash
### Global Scan (Option 12) - **Broad Fetch Strategy**
> **NOTE**: This strategy is specifically for the "Global Scan" scenario where we want to catch all trends.
```bash
# 1. Fetch broadly (Massive pool for Semantic Filtering)
python3 scripts/fetch_news.py --source all --limit 15 --deep
# 2. SEMANTIC FILTERING:
# Agent manually filters the broad list (approx 120 items) for user's topics.
Single Source & Combinations (Smart Keyword Expansion)
CRITICAL: You MUST automatically expand the user's simple keywords to cover the entire domain field.
- User: "AI" -> Agent uses:
--keyword "AI,LLM,GPT,Claude,Generative,Machine Learning,RAG,Agent" - User: "Android" -> Agent uses:
--keyword "Android,Kotlin,Google,Mobile,App" - User: "Finance" -> Agent uses:
--keyword "Finance,Stock,Market,Economy,Crypto,Gold"
# Example: User asked for "AI news from HN" (Note the expanded keywords)
python3 scripts/fetch_news.py --source hackernews --limit 20 --keyword "AI,LLM,GPT,DeepSeek,Agent" --deep
Specific Keyword Search
Only use --keyword for very specific, unique terms (e.g., "DeepSeek", "OpenAI").
python3 scripts/fetch_news.py --source all --limit 10 --keyword "DeepSeek" --deep
Arguments:
--source: One ofhackernews,weibo,github,36kr,producthunt,v2ex,tencent,wallstreetcn,all.--limit: Max items per source (default 10).--keyword: Comma-separated filters (e.g. "AI,GPT").--deep: [NEW] Enable deep fetching. Downloads and extracts the main text content of the articles.
Output:
JSON array. If --deep is used, items will contain a content field associated with the article text.
Interactive Menu
When the user says "news-aggregator-skill 如意如意" (or similar "menu/help" triggers):
- READ the content of
templates.mdin the skill directory. - DISPLAY the list of available commands to the user exactly as they appear in the file.
- GUIDE the user to select a number or copy the command to execute.
Smart Time Filtering & Reporting (CRITICAL)
If the user requests a specific time window (e.g., "past X hours") and the results are sparse (< 5 items):
- Prioritize User Window: First, list all items that strictly fall within the user's requested time (Time < X).
- Smart Fill: If the list is short, you MUST include high-value/high-heat items from a wider range (e.g. past 24h) to ensure the report provides at least 5 meaningful insights.
- Annotation: Clearly mark these older items (e.g., "⚠️ 18h ago", "🔥 24h Hot") so the user knows they are supplementary.
- High Value: Always prioritize "SOTA", "Major Release", or "High Heat" items even if they slightly exceed the time window.
- GitHub Trending Exception: For purely list-based sources like GitHub Trending, strictly return the valid items from the fetched list (e.g. Top 10). List ALL fetched items. Do NOT perform "Smart Fill".
- Deep Analysis (Required): For EACH item, you MUST leverage your AI capabilities to analyze:
- Core Value (核心价值): What specific problem does it solve? Why is it trending?
- Inspiration (启发思考): What technical or product insights can be drawn?
- Scenarios (场景标签): 3-5 keywords (e.g.
#RAG #LocalFirst #Rust).
- Deep Analysis (Required): For EACH item, you MUST leverage your AI capabilities to analyze:
6. Response Guidelines (CRITICAL)
Format & Style:
- Language: Simplified Chinese (简体中文).
- Style: Magazine/Newsletter style (e.g., "The Economist" or "Morning Brew" vibe). Professional, concise, yet engaging.
- Structure:
- Global Headlines: Top 3-5 most critical stories across all domains.
- Tech & AI: Specific section for AI, LLM, and Tech items.
- Finance / Social: Other strong categories if relevant.
- Item Format:
- Title: MUST be a Markdown Link to the original URL.
- ✅ Correct:
### 1. [OpenAI Releases GPT-5](https://...) - ❌ Incorrect:
### 1. OpenAI Releases GPT-5
- ✅ Correct:
- Metadata Line: Must include Source, Time/Date, and Heat/Score.
- 1-Liner Summary: A punchy, "so what?" summary.
- Deep Interpretation (Bulleted): 2-3 bullet points explaining why this matters, technical details, or context. (Required for "Deep Scan").
- Title: MUST be a Markdown Link to the original URL.
Output Artifact:
- Always save the full report to
reports/directory with a timestamped filename (e.g.,reports/hn_news_YYYYMMDD_HHMM.md). - Present the full report content to the user in the chat.
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