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What is serenity-skill?

yijiashu/serenity-skill — explained in plain English

Analysis updated 2026-06-24

14PythonAudience · pm founderComplexity · 2/5Setup · easy

In one sentence

An AI skill that packages the investment analysis style of Twitter's @stockgodserenity into reusable mental models, focused on supply chain bottlenecks, institutional signals, and 3-5 year trends rather than short-term price movements.

Mindmap

mindmap
  root((repo))
    What It Does
      Packages tweet analysis
      AI chat skill
      Stock framework
    Mental Models
      Supply chain bottleneck
      Institutional signals
      Long-term trends
      Repricing spotting
    Decision Rules
      Upstream prioritization
      Scarcity pricing
      Disruption risk
      Timing rules
    Data Source
      5963 tweets
      July 2025 to June 2026
      96 percent English
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Code map

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filefunction / class

What do people build with it?

USE CASE 1

Ask an AI to analyze a stock ticker using Serenity's supply chain bottleneck framework instead of generic advice.

USE CASE 2

Quickly apply a consistent set of investment mental models to evaluate a company or industry sector.

USE CASE 3

Identify stocks that institutional investors are quietly accumulating as a signal of upcoming repricing.

USE CASE 4

Screen companies for long-term 3-to-5 year industry trends rather than reacting to short-term price swings.

What is it built with?

PythonAI chat skillTweet data analysis

How does it compare?

yijiashu/serenity-skill0c33/agentic-aialbertusreza/pr-pilot
Stars141414
LanguagePythonPythonPython
Setup difficultyeasyhardeasy
Complexity2/54/52/5
Audiencepm founderdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 30min

Clone the repo and load the skill into your AI chat tool of choice. Phrase questions using the Serenity style shown in the README. Includes a data analysis script for exploring the source tweet dataset.

No license information is mentioned in the explanation.

So what is it?

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.

Copy-paste prompts

Prompt 1
Give me the Serenity perspective on NVDA: which part of its supply chain is hardest to replace, and what are institutional investors signaling right now?
Prompt 2
Using the Serenity framework, analyze the semiconductor sector for supply chain choke points and upcoming repricing opportunities over the next 3-5 years.
Prompt 3
Apply the Serenity mental models to MSFT: is it upstream or downstream in its key supply chains, and how does scarcity pricing apply to its products?
Prompt 4
Using Serenity's 12 decision rules, evaluate GOOGL for technology disruption risk and signs of institutional accumulation.
Prompt 5
What does the Serenity supply chain analysis framework say about META's position, is it a bottleneck layer or a commodity layer in its industry?

Frequently asked questions

What is serenity-skill?

An AI skill that packages the investment analysis style of Twitter's @stockgodserenity into reusable mental models, focused on supply chain bottlenecks, institutional signals, and 3-5 year trends rather than short-term price movements.

What language is serenity-skill written in?

Mainly Python. The stack also includes Python, AI chat skill, Tweet data analysis.

What license does serenity-skill use?

No license information is mentioned in the explanation.

How hard is serenity-skill to set up?

Setup difficulty is rated easy, with roughly 30min to a first successful run.

Who is serenity-skill for?

Mainly pm founder.

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