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skill mdSKILL.md4,848 B
docsSUMMARY.md474 B
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First seen on skills.sh
First recorded snapshot · 2,202 installs
SKILL.md
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
``bash python3 -m pip install -r skills/macro-regime-detector/requirements.txt uv run python3 skills/macro-regime-detector/scripts/macroregimedetector.py --output-dir reports/ `` This fetches 600 days of data for 9 ETFs. With an FMP key, the client tries FMP first and fetches Treasury rates (~10 API calls total), then falls back to yfinance for unavailable ETF history. Without an FMP key, it runs in yfinance-only mode and uses SHY/TLT as the yield-curve fallback.
The detector fails closed and writes no report when none of its six components has usable data. Do not treat a missing report or non-zero exit as a valid low-transition regime.
Read the generated Markdown report and present findings to user.
Provide additional context using references/historical_regimes.md when user asks about historical parallels.
Prerequisites
Python dependencies (required): install requirements.txt, including yfinance and requests
FMP API Key (optional): set FMPAPIKEY or pass --api-key to use FMP and Treasury data before the yfinance/SHY-TLT fallbacks
The FMP free tier may not serve every ETF; unavailable symbols automatically use yfinance
1. Current Regime Assessment 2. Transition Signal Dashboard 3. Component Details 4. Regime Classification Evidence 5. Portfolio Posture Recommendations
Relationship to Other Skills
Aspect
Macro Regime Detector
Market Top Detector
Market Breadth Analyzer
Time Horizon
1-2 years (structural)
2-8 weeks (tactical)
Current snapshot
Data Granularity
Monthly (6M/12M SMA)
Daily (25 business days)
Daily CSV
Detection Target
Regime transitions
10-20% corrections
Breadth health score
API Calls
~10
~33
0 (Free CSV)
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/regimedetectionmethodology.md — Detection methodology and signal interpretation
references/indicatorinterpretationguide.md — Guide for interpreting cross-asset ratios
references/historical_regimes.md — Historical regime examples for context