Skip to the rows

agentsclimarketplace

Macro regime detector

Skill xonevn-ai/xone-trading-skills/skills/macro-regime-detector

Bộ "kỹ năng" (Claude Skills) hỗ trợ workflow giao dịch cho nhà đầu tư cá nhân Việt Nam có quỹ thời gian hạn chế. Mục tiêu là chuẩn hoá quy trình review thị trường, quản trị rủi ro, lập kế hoạch giao dịch, ghi nhật ký và cải tiến liên tục — không thay thế phán đoán của bạn, không đưa ra tín hiệu mua/bán.

Install

npx -y skills add xonevn-ai/xone-trading-skills --skill macro-regime-detector

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Detect structural macro regime transitions (1-2 year horizon) using cross-asset ratio analysis. Analyze RSP/SPY concentration, yield curve, credit conditions, size factor, equity-bond relationship, and sector rotation to identify regime shifts between Concentration, Broadening, Contraction, Inflationary, and Transitional states. Run when user asks about macro regime, market regime change, structural rotation, or long-term market positioning.

SKILL.md

4.1 KB, as published. Nobody here has run it

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

Load reference documents for methodology context:
- references/regime_detection_methodology.md
- references/indicator_interpretation_guide.md
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).
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

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

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/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

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.