sector-analyst

Name: sector-analyst
Availability: InStock
Author: fabio29t

Analyzes sector rotation patterns and market cycle phases from public CSV data.

2|Updated Mar 4, 2026

Search Tags:#data analysis #technical analysis #stock market #sector rotation #market cycle #risk regime

Ready to run

npx skills add https://github.com/Fabio29T/Trading-Skills --skill sector-analyst-fabio29t

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sector-analyst
Source: https://github.com/Fabio29T/Trading-Skills/tree/main/skills/sector-analyst
Command: npx skills add https://github.com/Fabio29T/Trading-Skills --skill sector-analyst-fabio29t

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the analysis of sector rotation patterns and market cycle positioning, providing data-driven insights into where the market is heading.

Core Features & Use Cases

Sector Ranking: Identifies leading and lagging sectors based on uptrend ratio data.
Market Cycle Estimation: Determines the current market cycle phase (Early, Mid, Late, Recession).
Risk Regime Assessment: Calculates cyclical vs. defensive positioning scores.
Overbought/Oversold Identification: Flags sectors showing extreme conditions.
Use Case: A portfolio manager can use this Skill to quickly assess the current market environment and adjust sector allocations based on predicted rotation patterns.

Quick Start

Run a sector rotation analysis using the default CSV data source.

Frequently Asked Questions about sector-analyst

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

FAQPage Schema

How do I analyze sector rotation patterns to identify leading and lagging sectors?▼

You can analyze sector rotation patterns by processing uptrend ratio data from CSV files. This identifies leading and lagging sectors, estimates market cycle phases, and assesses cyclical vs. defensive risk regimes using Python scripts.

Can I estimate market cycle phases using public CSV data without external API keys?▼

Yes, you can estimate market cycle phases using public CSV data without external API keys. Python scripts fetch and process data from specified GitHub repositories to determine Early, Mid, Late, or Recession phases.

What is the best way to assess cyclical vs. defensive risk regimes for portfolio allocation?▼

The best way to assess cyclical vs. defensive risk regimes is by calculating positioning scores from sector data. This flags overbought or oversold sectors, helping adjust allocations based on predicted rotation patterns.

Does this sector rotation analysis tool require any external dependencies or API keys?▼

No, this sector rotation analysis tool requires no external API keys or dependencies. It utilizes Python scripts to directly fetch and process public CSV data from specified GitHub repositories.

How do I run a market cycle analysis if I have my own CSV sector data?▼

To run a market cycle analysis with your CSV sector data, execute the provided Python scripts against your data source. The scripts will process the uptrend ratios to output the current market cycle phase and sector rankings.