fadewalk/serenity-stock-choke

What it solves

Investors often struggle to identify the “choke point” in a supply chain — the critical node where a disruption would shake an entire industry. This skill applies the supply-chain bottleneck theory popularized by Reddit legend Serenity to help investors trace upstream along the production chain, find small-cap companies with pricing power at those bottlenecks, and spot high-potential investment opportunities. It covers A-shares, Hong Kong, and US markets, turning abstract theory into a practical six-step analysis workflow.

How it works

The skill follows a six-step analysis chain: 1) locate sector cycle (judge whether demand is exploding, technology is shifting, or supply is constrained); 2) trace the supply chain to find which layer is the bottleneck; 3) find candidate stocks in the target market (A-shares, HK, or US); 4) filter for genuine bottlenecks vs. hype-driven names; 5) confirm long vs. short signals; 6) output a structured report with operation suggestions and risk warnings. Data acquisition uses a three-tier fallback: first, any financial MCP tools already in the agent environment; second, the built-in zero-dependency Python script (queries A-share, HK, and US quotes, valuations, sector K-lines, etc.); third, web search for supplementary information on supply-demand gaps, policies, fund flows, and more.

Who it’s for

This skill is designed for investors and analysts using AI coding agents like Claude Code, Codex, or Cursor — especially those focused on supply-chain bottleneck (“choke point”) themes and wanting a systematic way to screen potential small-cap stocks. It suits both retail and institutional researchers interested in sectors such as semiconductors, power, optical modules/CPO, military, and new energy vehicles across A-shares, Hong Kong, and US markets.

Highlights

• Based on Reddit legend Serenity’s supply-chain bottleneck theory, covering A-shares, Hong Kong, and US markets
• Six-step analysis framework — from sector cycle identification to structured report output
• Zero-dependency data query script: pure Python standard library, no API key required, supports A/H/US quotes, valuations, sector data, and more
• Three-tier data fallback (MCP tools → built-in script → web search) ensures usability in any environment
• Easy installation via one-line command, plugin marketplace, skills.sh, or manual clone; multi-language README provided