Serenity Method - Find stocks with clear momentum
Let AI apply Serenity-style research to surface stocks and fund directions with clearer upside logic
When themes like AI semiconductors, robotics, CPO, compute, power equipment, or innovative drugs start trending, plenty of people can feel the heat — but few can tell which supply chain to follow, which type of company, which specific stock, or which fund direction to look at.
Serenity.skill turns the research approach observable in Serenity / @aleabitoreddit's public content into an Agent Skill. Starting from a hot theme, it breaks down the supply chain, locates the bottlenecks, screens candidate companies and fund directions, then checks filings, earnings, customers, capacity, and risks — and compiles it all into a prioritized research list.
The way it works is simple: first it unpacks the theme to find where the real demand is, then identifies which link in the chain is hardest to scale or hardest to substitute, and finally circles back to stocks and fund directions to judge which leads are worth digging into further.
It's built for investors facing a stream of trending headlines who want a systematic screening process — letting AI handle the first round of deep research, turning vague hype into research directions that are logical, evidence-backed, and bounded by risk.
Research support only. Serenity.skill handles research, ranking, and reasoning; the final buy/sell decision is always yours. Not financial advice.
Why the Serenity-style approach
Serenity / @aleabitoreddit has spent years doing supply-chain research across tech themes like AI, semiconductors, optical communications, and robotics. The core idea is clear: in a big move, the genuinely valuable opportunities often hide in the critical links that are hardest to bypass as a system scales up.
Serenity.skill reuses the research path from this public methodology:
- Start from a big theme and first look at where the real demand comes from.
- Break the theme into downstream demand, system integration, chips/components, equipment, materials, packaging & testing, and infrastructure.
- Find the links with few suppliers, long qualification cycles, hard-to-expand capacity, strict customer certification, and high material-purity requirements.
- Then return to stocks and fund directions to judge who sits closer to the real bottleneck and who is mostly just riding the theme.
- Finally, check filings, earnings, inquiry letters, orders, capacity, customers, and risks, and produce a prioritized research ranking.
This repository is a research tool built on public information. It absorbs the structured thinking of Serenity-style research, while requiring every company-level judgment to come back to filings, exchange documents, earnings reports, earnings calls, regulatory/project documents, patents, standards, credible media, and professional analysis.
What it can do for you
| Your situation | What to ask the AI | What Serenity.skill checks for you |
|---|---|---|
| You catch a trending theme everyone's talking about and don't know where to start | AI semiconductors are hot right now — which directions should a regular investor research first? |
Breaks down the supply chain first, then ranks the directions closest to real demand and capacity bottlenecks |
| You want to buy into robotics but can't tell whether the full machine, components, reducers, or sensors matter most | In the robotics supply chain, which links are most likely to see opportunities first? |
Compares supply-demand tightness, competitive landscape, and strength of evidence across links |
| Someone recommends a stock and you worry it's just riding the hype | Challenge whether this company is really a core CPO supplier |
Checks its true position in the chain, customer evidence, revenue quality, and key risks |
| You want a thematic fund or ETF but can't tell which sub-direction is worth a closer look | For robotics thematic funds, which upstream links should I focus on? |
Identifies the core beneficiary chain behind the fund and flags the holdings directions to verify |
| You hold a few candidate stocks and want the AI to rank them for research | Compare companies A, B, and C — whose upside logic is clearer? |
Ranks them by supply-chain position, strength of evidence, valuation pressure, and risk points |
| Doom-scrolling the news makes you anxious and you want a repeatable screening process | Teach me Serenity-style supply-chain research, asking me just one question at a time |
Builds a research framework step by step — theme, demand, chokepoint, evidence, risk |
Copy these prompts
Use serenity-skill to do deep research on the A-share AI semiconductor supply chain.
Go online to check filings, earnings, inquiry letters, investor-Q&A platforms, tenders/bids, environmental/energy assessments, patents, customer certifications, and financial quality.
First rank the supply-chain tiers, then find the 5 names most worth prioritizing,
and explain the chokepoint link, supply-chain position, evidence, ranking rationale, and key risks.
Use serenity-skill to research the recent robotics theme.
Break down the supply chain first, then judge which links sit closest to a real supply-demand bottleneck,
and finish with a prioritized research list of stock and fund directions.
Use serenity-skill to challenge [company / ticker].
Which tier does it actually choke at? Is the evidence strong enough? What might the market be overestimating?
What conditions would signal this thesis should be downgraded?
What the output looks like
I'd look at [Direction A] first, then [Direction B] and [Direction C].
If you're after stock leads, these are the companies I'd research first:
1. [Company A]: closest to [the key bottleneck link]; upside comes from [demand growth / tight capacity / customer validation / domestic substitution].
2. [Company B]: sits at [supply-chain position]; worth tracking [orders / gross margin / capacity utilization].
3. [Company C]: higher beta, but you need to confirm [a core risk or missing evidence].
If you'd rather buy a fund or ETF, I'd start with products exposed to [sub-direction A] and [sub-direction B],
then check whether their top-ten holdings include companies like [Company A] and [Company B] that truly sit near the bottleneck.
I'd temporarily deprioritize [hot direction X]: the story is hot, but it still lacks [order evidence / earnings delivery / customer certification].
For the next step, check three things first:
1. Whether revenue and gross margin for [key business] changed in [Company A]'s latest earnings.
2. Whether [Company B] has any new customer certifications, orders, or capacity-expansion announcements.
3. Whether [the related fund/ETF]'s holdings are concentrated in the links that actually benefit.
