serenity-skill

This repository packages the investment analysis style of a Twitter personality known as Serenity (@stockgodserenity) into a reusable AI skill. The idea is that by studying nearly 6,000 of their tweets, the author distilled a consistent way of thinking about stocks into a set of rules and mental models that an AI assistant can apply when answering questions about companies or industries.

The framework centers on supply chain analysis rather than surface-level stock price movements. It breaks down into four main mental models: identifying which part of a supply chain is the hardest to replace (what the README calls the bottleneck or choke-point layer), reading what large institutional investors are doing as a signal of underlying value, focusing on three-to-five year industry trends rather than short-term price swings, and spotting situations where a stock is about to be repriced upward by the market. Below these models sit twelve more specific decision rules covering topics like upstream prioritization, scarcity pricing, technology disruption risk, and timing based on institutional behavior.

The skill is intended to be used in an AI chat context by phrasing questions in a particular style, such as asking for the Serenity perspective on a specific ticker or sector. The README lists example queries in Chinese and English. Stocks that appear most frequently in the source tweet data include NBIS, SIVE, LITE, AXTI, NVDA, MSFT, GOOGL, and META.

The source data covers 5,963 tweets from July 2025 through June 2026, of which about 96 percent are in English. The repository includes a data analysis script and reference documents. The README includes a disclaimer stating that the framework provides analytical perspective only, not investment advice, and that stock investments carry the risk of total loss.