# Serenity.skill

An Agent Skill that gives AI agents a supply-chain research method for spotting stocks and funds tied to technology-hype cycles, tracing a hot theme down to its supply bottlenecks before ranking research candidates.

Serenity.skill packages a public supply-chain investment research method, inspired by the researcher known as Serenity, as an Agent Skill for AI coding and research agents. Given a hot theme such as AI semiconductors or robotics, it breaks the theme into its supply chain, looks for where real demand originates, and identifies bottleneck segments that are hard to expand or replace, such as suppliers with strict customer certification or limited production capacity.

From there it works back to candidate stocks and funds, checking company announcements, financial reports, customer relationships, production capacity and risk factors, and produces a prioritized research list with its reasoning and open questions rather than a buy or sell recommendation. It requires an agent client that can read Skill files and has its own web search, browser or filings data access; the skill itself provides the research method rather than a live market-data feed or account.

Its structural consistency checks are written in Python.

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