yux1azhengye/bestserenityskillfromat — explained in plain English
Analysis updated 2026-05-18
Ask an AI coding assistant to analyze a specific stock using the Serenity supply-chain bottleneck method.
Search for unpriced supply-chain bottleneck companies within a given sector.
Generate a single-stock or sector analysis report using the provided templates.
Compare methodology adaptations for Chinese A-share versus US stock markets.
| yux1azhengye/bestserenityskillfromat | alicankiraz1/codexqb | amirmushichge/vibemotion | |
|---|---|---|---|
| Stars | 28 | 28 | 28 |
| Language | — | Python | Python |
| Setup difficulty | easy | easy | moderate |
| Complexity | 2/5 | 3/5 | 3/5 |
| Audience | researcher | developer | designer |
Figures from each repo's GitHub metadata at analysis time.
Not investment advice, track record figures cited are self-reported and unaudited.
This project collects and synthesizes ten community GitHub repositories that all implement an investment analysis methodology developed by a Reddit user known as Serenity (@aleabitoreddit). The README is written in Chinese. The core idea behind the methodology is to trace a supply chain upstream until you find the single component or company that, if it ran out of stock, would disrupt an entire industry. The claim is that small-cap companies sitting at those critical bottleneck positions tend to offer outsized returns before the broader market notices them. The repository packages the best ideas from those ten source repos into a single unified skill file (v3.0) that works with AI coding assistants such as Claude Code, Cursor, and OpenAI Codex. Once installed, you can type a prompt like "analyze NVDA using the Serenity method" or ask the AI to look for unpriced supply-chain bottlenecks in a given sector, and the skill guides the AI through the analysis framework. The project folder contains the core skill instructions, a knowledge base covering market adaptations for both Chinese A-share and US stock markets, mental models, a supply-chain map reference, and report templates for single-stock and sector analysis. There are also two older archived versions of the unified skill file for reference. The README includes a clear disclaimer that this is not investment advice, that the project has no affiliation with the original Serenity account, and that the track record figures cited by Serenity are self-reported and have not been independently audited. The project is MIT licensed.
An AI coding assistant skill that packages a supply-chain bottleneck investment analysis method from ten community repos.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.