Zero-Token Investment News Collector
Paste the following prompt into your AI chat to install this skill:
Please install @user_f0974107/investment-news-collector-xdj according to https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Financial news from CLS and Wall Street CN often arrives as complex JSON or Next.js pages, making it hard to consistently track IPOs, M&A, policy changes, and risk signals without relying on LLM APIs. Investment-News-Collector is a local rule-based pipeline that turns multi-source finance news into a reviewable investment signal digest.
How It Works
Local RSSHub normalizes CLS Depth and Wall Street CN Global News into RSS, while feedparser fetches both feeds in parallel with automatic fallback. The pipeline then applies MD5 deduplication, domain filtering, title-first event scoring, topic clustering, and rule-based summaries. Scoring covers ten event types such as IPO/listing, M&A/restructuring, risk warning, and policy/regulation, using Tier1/Tier2 company boosts from config/companies.yaml, amount-size factors, and time decay to produce a Markdown report.
Boundaries
This skill is suitable for local monitoring and signal screening, not as a substitute for due diligence or real-time trading decisions. Keyword- and title-based scoring can miss or mislabel nonstandard wording; CLS body availability is lower than Wall Street CN, so summary quality depends on retrieved content. Local Python dependencies and RSSHub routes must be available, and company lists, noise patterns, and source preferences should be maintained as priorities change.
Use Cases
- Track A-share IPOs and STAR Market industrial news by collecting CLS Depth and filtering high-risk events.
- Compile a deduplicated Markdown digest of global macro and U.S. tech news from Wall Street CN before morning meetings.
- Maintain Tier1 companies such as Nvidia and OpenAI so priority events score higher in the pipeline.
- Feed rule-based summaries into Obsidian as date-organized finance signal notes.
Best For
- Retail investors: track IPOs, M&A, policy regulation, and risk warnings with low API cost.
- Research assistants: extract scoreable event signals from CLS and Wall Street CN feeds.
- Knowledge-base maintainers: automatically archive finance digests into Obsidian.
- Local automation operators: avoid token consumption and external LLM API dependencies.
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