Serenity White-Haired Stock Goddess Skill

Serenity has recently become the hottest figure in the US stock market. The reason is her exceptional ability. This repository distills insights from @aleabitoreddit’s entire tweet feed into a skill. Once installed, you can chat with it and ask it to analyze stocks and break down supply chains using Serenity’s thinking framework—it’s like having Serenity as your personal stock investment assistant. Let AI use the Serenity-style research method to screen for stocks and fund directions with clearer upside logic.

Repo: https://github.com/muxuuu/serenity-skill…

Finally, a risk reminder: stock investment carries risks. Always DYOR before buying.

I’m Nike. I regularly share useful and interesting tools and projects related to AI, US stocks, and Web3. Follow me if you’re interested. See you next time!

muxuuu/serenity-skill

Source: https://github.com/muxuuu/serenity-skill

Serenity.skill

Let AI use the Serenity-style research method to screen for stocks and fund directions with clearer upside logic

License: MIT Agent Skill 中文优先 English

When you see hot topics like AI semiconductors, robotics, CPO, computing power, power equipment, and innovative drugs, many people feel the buzz but struggle to decide which supply chain, which companies, which stocks, or which fund directions to focus on.

Serenity.skill turns the observable research methodology from Serenity / @aleabitoreddit (https://x.com/aleabitoreddit) public content into an Agent Skill. It starts from hot topics, breaks down the supply chain, finds supply chain bottlenecks, screens candidate companies and fund directions, then checks announcements, financial reports, customers, production capacity, and risks, finally compiling a prioritized research list.

How it works is simple: first, break down the hot topic to see where real demand lies; second, identify which links are harder to scale or replace; finally, go back to stocks and fund directions to determine which clues are worth deeper investigation.

It is suitable for investors facing a flood of hot topic information who want to establish a systematic screening process: let AI complete the first round of deep research, turning vague buzz into research directions with logic, evidence, and risk boundaries.

Research support only. Serenity.skill handles research, ranking, and reasoning; all final buy/sell decisions are yours.

Why the Serenity Method

Serenity / @aleabitoreddit (https://x.com/aleabitoreddit) has long focused on supply chain research around tech themes like AI, semiconductors, optical communications, and robotics in public content. The core idea is clear: truly valuable opportunities in major trends often hide in the key links that the system cannot easily bypass.

Serenity.skill replicates the research path from this public methodology:

• Start from major hot topics, first check where real demand comes from.
• Break the theme into downstream demand, system integration, chips/components, equipment, materials, packaging/testing, and infrastructure.
• Find links with low supplier count, long validation cycles, difficult capacity expansion, strict customer certification, and high material purity requirements.
• Then go back to stocks and fund directions to determine who is closer to the real bottleneck and who is just riding the theme.
• Finally, check announcements, financial reports, inquiry letters, orders, capacity, customers, and risks, and provide a prioritized research ranking.

This repository is a public research tool. It absorbs the structured thinking of Serenity-style research while requiring all judgments on companies to be based on announcements, exchange filings, financial reports, conference calls, regulatory/project documents, patents, standards, credible media, and professional analysis.

What It Can Help You With

Directly Copy This Prompt

text
Use serenity-skill to do a deep dive on the A-share AI semiconductor supply chain.
Search announcements, financial reports, inquiry letters, investor interactions, tenders, environmental/energy assessments, patents, customer certifications, and financial quality online.
First, rank the supply chain layers, then find the 5 most worthy candidates for priority research.
Explain the stuck link, supply chain position, evidence, ranking rationale, and major risks.

text
Use serenity-skill to research the robotics direction recently.
First, break down the supply chain, then determine which links are closer to real supply-demand bottlenecks.
Finally, give a prioritized research list of stocks and fund directions.

text
Use serenity-skill to challenge [company/ticker].
Which layer is it really stuck in? Is the evidence sufficient? What might the market be overestimating?
Under what conditions should this judgment be downgraded?

More copyable templates are available in assets/research-prompt-pack.md.

What the Output Looks Like

text
I'll first look at [Direction A], then [Direction B] and [Direction C].
If you want stock leads, I'll prioritize these companies:
1. [Company A]: Closest to [key bottleneck link]; the upside logic comes from [demand growth / capacity tightness / customer validation / import substitution].
2. [Company B]: Located at [supply chain position]; suitable to track [orders / gross margin / capacity utilization].
3. [Company C]: Has more upside elasticity but needs confirmation of [core risk or missing evidence].
If you prefer funds or ETFs, I'll first look at products exposed to [sub-direction A] and [sub-direction B].
Then check whether their top ten holdings include bottleneck-close companies like [Company A] or [Company B].
I'll temporarily deprioritize [hot direction X] because while the narrative is hot, it still lacks [order evidence / profit delivery / customer certification].
Next, check these three items:
1. Whether revenue and gross margin of [key business] in [Company A]'s latest financial report have changed.
2. Whether [Company B] has new customer certifications, orders, or capacity expansion announcements.
3. Whether holdings of [related fund/ETF] are concentrated in truly beneficial links.

Full examples:

• A-Share AI Semiconductor Scan
• AI Infrastructure Chokepoint Research
• Research Partner Conversation

Installation

Codex / OpenAI Agent Skills / General Agent Skills Clients

User-level installation:

SKILL_DIR="$HOME/.agents/skills/serenity-skill"
mkdir -p "$SKILL_DIR"
cp -R SKILL.md LICENSE references assets scripts examples agents "$SKILL_DIR"/

Project-level installation:

SKILL_DIR=".agents/skills/serenity-skill"
mkdir -p "$SKILL_DIR"
cp -R SKILL.md LICENSE references assets scripts examples agents "$SKILL_DIR"/

Claude Code

User-level installation:

SKILL_DIR="$HOME/.claude/skills/serenity-skill"
mkdir -p "$SKILL_DIR"
cp -R SKILL.md LICENSE references assets scripts examples agents "$SKILL_DIR"/

Project-level installation:

SKILL_DIR=".claude/skills/serenity-skill"
mkdir -p "$SKILL_DIR"
cp -R SKILL.md LICENSE references assets scripts examples agents "$SKILL_DIR"/

Hermes Agent

SKILL_DIR="$HOME/.hermes/skills/research/serenity-skill"
mkdir -p "$SKILL_DIR"
cp -R SKILL.md LICENSE references assets scripts examples agents "$SKILL_DIR"/

OpenClaw / Other AgentSkills-compatible Clients

Place SKILL.md, LICENSE, references/, assets/, scripts/, examples/, and agents/ into the serenity-skill/ directory of the corresponding client. The README and project maintenance docs are only for GitHub display and do not need to be installed into the runtime directory.

Local Bottleneck Scoring

Generate template:

python scripts/serenity_scorecard.py --template > my-company.json

Run scoring:

python scripts/serenity_scorecard.py --format md my-company.json

Validate Skill:

python scripts/validate_skill.py .

Repository Structure

serenity-skill/
├── SKILL.md
├── README.md
├── README.en.md
├── README.zh-CN.md
├── references/
│   ├── deep-research-workflow.md
│   ├── evidence-ladder.md
│   ├── market-source-playbook.md
│   ├── public-profile-and-evaluation.md
│   └── risk-and-compliance.md
├── assets/
│   ├── bottleneck-scorecard.json
│   ├── research-prompt-pack.md
│   └── thesis-template.md
├── scripts/
│   ├── serenity_scorecard.py
│   └── validate_skill.py
├── examples/
│   ├── a-share-ai-semiconductor-demo.md
│   ├── ai-infrastructure-chokepoint-demo.md
│   └── demo-conversation.md
└── evals/
    └── test-cases.md

Research Boundaries

Serenity.skill is an independent public methodology project, inspired by the observable research paradigm from Serenity / @aleabitoreddit (https://x.com/aleabitoreddit) public content. It aids research, ranking, and reasoning, with its functional scope limited to research assistance.

It provides research priorities, evidence chains, risk checks, and next-step checklists. Trade execution, account operations, return promises, and final buy/sell decisions remain entirely under user control.

Strong conclusions should be based on announcements, exchange filings, financial reports, conference calls, regulatory/project documents, patents, standards, credible media, and professional analysis. Social media content can serve as clue sources, but final judgments should return to stronger evidence.

License

MIT

Jealousy Nike (@eastweb3eth): What exactly is Serenity buying?

Today the white-haired stock goddess dropped another bombshell, and this time it’s exclusive for Chinese users: Harmonic Drive Systems (stock code 688017, market cap 577.3 billion RMB).

However, after the stock goddess tweeted, Harmonic Drive Systems surged 20% today, with market cap rising to 720 billion RMB.

I now believe Serenity’s call-out ability is on par with Jensen Huang’s—both are top-tier super leaders!