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Macro Regime Detector

Detect structural macro regime transitions using monthly-frequency cross-asset ratio analysis. This skill identifies 1-2 year regime shifts that inform strategic portfolio positioning.

When to Use

• User asks about current macro regime or regime transitions
• User wants to understand structural market rotations (concentration vs broadening)
• User asks about long-term positioning based on yield curve, credit, or cross-asset signals
• User references RSP/SPY ratio, IWM/SPY, HYG/LQD, or other cross-asset ratios
• User wants to assess whether a regime change is underway

Workflow

1. Load reference documents for methodology context:

   • references/regime_detection_methodology.md
   • references/indicator_interpretation_guide.md

2. Execute the main analysis script:

   python3 skills/macro-regime-detector/scripts/macro_regime_detector.py
   

This fetches 600 days of data for 9 ETFs + Treasury rates (10 API calls total).

1. Read the generated Markdown report and present findings to user.

2. Provide additional context using references/historical_regimes.md when user asks about historical parallels.

Prerequisites

• FMP API Key (required): Set FMP_API_KEY environment variable or pass --api-key
• Free tier (250 calls/day) is sufficient (script uses ~10 calls)

6 Components

| Component | Ratio/Data | Weight | What It Detects

---|---|---|---|---
1 | Market Concentration | RSP/SPY | 25% | Mega-cap concentration vs market broadening
2 | Yield Curve | 10Y-2Y spread | 20% | Interest rate cycle transitions
3 | Credit Conditions | HYG/LQD | 15% | Credit cycle risk appetite
4 | Size Factor | IWM/SPY | 15% | Small vs large cap rotation
5 | Equity-Bond | SPY/TLT + correlation | 15% | Stock-bond relationship regime
6 | Sector Rotation | XLY/XLP | 10% | Cyclical vs defensive appetite

5 Regime Classifications

• Concentration : Mega-cap leadership, narrow market
• Broadening : Expanding participation, small-cap/value rotation
• Contraction : Credit tightening, defensive rotation, risk-off
• Inflationary : Positive stock-bond correlation, traditional hedging fails
• Transitional : Multiple signals but unclear pattern

Output

• macro_regime_YYYY-MM-DD_HHMMSS.json — Structured data for programmatic use
• macro_regime_YYYY-MM-DD_HHMMSS.md — Human-readable report with:
  1. Current Regime Assessment
  2. Transition Signal Dashboard
  3. Component Details
  4. Regime Classification Evidence
  5. Portfolio Posture Recommendations

Relationship to Other Skills

Script Arguments

python3 macro_regime_detector.py [options]

Options:
  --api-key KEY       FMP API key (default: $FMP_API_KEY)
  --output-dir DIR    Output directory (default: current directory)
  --days N            Days of history to fetch (default: 600)

Resources

• references/regime_detection_methodology.md — Detection methodology and signal interpretation
• references/indicator_interpretation_guide.md — Guide for interpreting cross-asset ratios
• references/historical_regimes.md — Historical regime examples for context

Weekly Installs

155

Repository

tradermonty/cla…g-skills

GitHub Stars

398

First Seen

Feb 16, 2026

Security Audits

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Installed on

gemini-cli149

cursor149

github-copilot148

amp148

codex148

kimi-cli148