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macro-regime-detector

Detect macro regime transitions across six cross-asset signals.

Updated Mar 25, 2026
Search Tags:#finance#data-analysis#risk-management#detector#macro#regime#cross-asset
One-click install
npx skills add https://github.com/MileniumTick/skills --skill macro-regime-detector-mileniumtick
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: macro-regime-detector
Source: https://github.com/MileniumTick/skills/tree/main/skills/macro-regime-detector
Command: npx skills add https://github.com/MileniumTick/skills --skill macro-regime-detector-mileniumtick

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Cross-asset macro regime transitions are complex; this skill provides a structured framework to detect regime shifts and translate signals into actionable positioning guidance for longer horizons.

Core Features & Use Cases

  • Six-component, cross-asset regime analysis (RSP/SPY, IWM/SPY, HYG/LQD, XLY/XLP, SPY/TLT, yield curve) to classify regimes.
  • Automated data workflow with deterministic monthly signals and a composite score to guide portfolio posture.
  • Use cases include strategic asset allocation, risk management, and regime-history benchmarking across Concentration, Broadening, Contraction, Inflationary, and Transitional states.

Quick Start

Analyze historical data and generate a report by running the main detector script and inspecting the JSON/Markdown outputs.

Frequently Asked Questions about macro-regime-detector

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

FAQPage Schema
How do I detect macro regime shifts using cross-asset data for portfolio positioning?▼

Cross-asset macro regime detection analyzes six component signals, including RSP/SPY, HYG/LQD, and yield curve spreads, to classify market states and guide long-horizon portfolio positioning. The framework outputs a deterministic composite score for strategic allocation.

What are the main cross-asset signals used to classify macro regimes?▼

Macro regime classification relies on six cross-asset signals: RSP/SPY, IWM/SPY, HYG/LQD, XLY/XLP, SPY/TLT, and the yield curve. These components evaluate market breadth, risk appetite, and duration sensitivity to categorize regimes into Concentration, Broadening, Contraction, Inflationary, or Transitional states.

Do I need an API key for Treasury yield curve data to run macro regime analysis?▼

An FMP API key is required to fetch Treasury yield curve data for accurate macro regime analysis. If Treasury data is unavailable, the workflow supports a SHY/TLT proxy fallback to calculate the signal and complete the classification.

Can I use macro regime detection for risk management and strategic asset allocation?▼

Macro regime detection is designed for strategic asset allocation and risk management. By benchmarking historical regime transitions and generating a monthly composite score, it translates cross-asset signals into actionable portfolio posture guidance for long-horizon positioning.

How do I generate a macro regime report from historical cross-asset data?▼

To generate a macro regime report, run the main detector script to process historical cross-asset data. The deterministic workflow outputs structured JSON and Markdown files containing the regime classification, component scores, and composite posture guidance.

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