serenity

Analyze US equities and AI infrastructure supply chains using Python.

146|19|Updated Jun 4, 2026
One-click install
npx skills add https://github.com/ZadAnthony/serenity-skill --skill serenity
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: serenity
Source: https://github.com/ZadAnthony/serenity-skill/tree/main
Command: npx skills add https://github.com/ZadAnthony/serenity-skill --skill serenity

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, pandas, numpy, scikit-learn, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Serenity Skill provides a comprehensive, repeatable analysis engine for US equities and the AI infrastructure supply chain, empowering users to conduct in-depth investment analysis.

Core Features & Use Cases

  • Comprehensive Analysis: Analyze stocks, sectors, and theses using the "reverse-engineer the supply-chain bottleneck" methodology of Serenity.
  • In-depth Reporting: Generate detailed research reports with valuation, risk analysis, and actionable insights.
  • Customizable Workflow: Integrate Serenity Skill into your existing agent runtime for seamless analysis and decision-making.

Quick Start

To install Serenity Skill, clone the repository and place the SKILL.md and methodology.md files into your agent's skills directory. To analyze a stock, use the command /serenity analyze $stock_symbol.

Frequently Asked Questions about serenity

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze US equities using the reverse-engineer the supply-chain bottleneck methodology?

To analyze US equities, the reverse-engineer the supply-chain bottleneck methodology identifies AI infrastructure bottlenecks to generate detailed investment research reports with valuation and risk analysis. You can execute this by running the `/serenity analyze $stock_symbol` command in your agent runtime.

What is the reverse-engineer the supply-chain bottleneck methodology for AI investment analysis?

The reverse-engineer the supply-chain bottleneck methodology isolates critical constraints within the AI infrastructure supply chain to evaluate technology equities. It systematically traces supply chain dependencies to produce actionable investment insights and in-depth research reports.

Do I need Python and pandas to run Serenity investment analysis?

Yes, you need Python installed along with pandas, numpy, and scikit-learn to run Serenity investment analysis. These dependencies are required for data retrieval, manipulation, and applying machine learning models to evaluate US equities and the AI infrastructure supply chain.

Can I use pandas and scikit-learn for stock and sector analysis in an agent runtime?

Yes, you can integrate this skill into your existing agent runtime to use pandas and scikit-learn for stock and sector analysis. This customizable workflow automates data retrieval and investment analysis directly within your established decision-making environment.

What is the best way to generate detailed research reports for AI infrastructure equities?

The best way to generate detailed research reports for AI infrastructure equities is applying the reverse-engineer the supply-chain bottleneck methodology. This approach provides comprehensive valuation, risk analysis, and actionable insights by tracing critical supply chain constraints.