Scans ~100 US stocks via Finnhub to rank them by adaptive multi-factor scoring.
npx skills add https://github.com/MerkyorLynn/Lynn --skill quant-scanner
Please help me install this Agent Skill. Skill: quant-scanner Source: https://github.com/MerkyorLynn/Lynn/tree/main/skills2set/quant-scanner Command: npx skills add https://github.com/MerkyorLynn/Lynn --skill quant-scanner
Quant-scanner eliminates manual stock screening by automatically scanning a large US equity universe, detecting the current market regime, and ranking stocks using an adaptive multi-factor scoring model.
Run a full US stock quantitative scan with an HTML report using your Finnhub API key.
High-intent search queries and answers about installing and using this skill.
Automate US equity screening by scanning a ~100-stock universe with Finnhub data, detecting market regime, and ranking stocks using adaptive factor scoring across momentum, value, quality, and risk metrics.
Market regime detection classifies volatility level, momentum regime, and breadth bias from a scanned stock universe, dynamically adjusting factor weights to produce regime-aware ranked selections and anomaly lists.
Yes, you need a FINNHUB_API_KEY environment variable or an explicit --api-key argument to fetch data for adaptive factor scoring and generate ranked stock selections with HTML and JSON reports.
Yes, run a full scan on a ~100 US large and mid-cap stock universe to review top selections and anomalies, specifically designed for momentum, value, and quality play discovery in model portfolio construction.
Yes, the stock screening process outputs an HTML report by default and optionally generates a JSON file containing scored stock fields and regime metadata for downstream quantitative analysis.
Adaptive factor scoring is limited to a ~100 US large and mid-cap stock universe sourced via Finnhub, meaning it does not cover small-cap or international equities and requires valid API credentials to execute.
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