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.
Best use case
news-aggregator-skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using news-aggregator-skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/news-aggregator-skill/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How news-aggregator-skill Compares
| Feature / Agent | news-aggregator-skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# News Aggregator Skill
Fetch real-time hot news from multiple sources.
## Tools
### fetch_news.py
**Usage:**
```bash
### 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"`
```bash
# 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").
```bash
python3 scripts/fetch_news.py --source all --limit 10 --keyword "DeepSeek" --deep
```
**Arguments:**
- `--source`: One of `hackernews`, `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):
1. **READ** the content of `templates.md` in the skill directory.
2. **DISPLAY** the list of available commands to the user exactly as they appear in the file.
3. **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):
1. **Prioritize User Window**: First, list all items that strictly fall within the user's requested time (Time < X).
2. **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.
2. **Annotation**: Clearly mark these older items (e.g., "⚠️ 18h ago", "🔥 24h Hot") so the user knows they are supplementary.
3. **High Value**: Always prioritize "SOTA", "Major Release", or "High Heat" items even if they slightly exceed the time window.
4. **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`).
### 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`
- **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").
**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.Related Skills
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