Skill: cclank/news-aggregator-skill (version 0.1.0)

--- name: news-aggregator-skill description: "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." --- # 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)