Skill

news-aggregator-skill-3

From sundial-org-awesome-openclaw-skills-4

Fetches, filters, and analyzes real-time news from Hacker News, GitHub Trending, Product Hunt, 36Kr, Tencent News, WallStreetCN, V2EX, Weibo using Python CLI tool. Useful for tech news scans and briefings.

Python

cli-tools

automation

Install

npx claudepluginhub joshuarweaver/cascade-ai-ml-agents-misc-2 --plugin sundial-org-awesome-openclaw-skills-4

Tool Access

This skill uses the workspace's default tool permissions.

Preview

Fetch real-time hot news from multiple sources.

Supporting Assets

README.mdrequirements.txtscripts/fetch_news.pytemplates.md

SKILL.md

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Last CommitFeb 1, 2026

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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 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):

READ the content of templates.md in 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).

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.