Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add BaggaT236/AI-Trading-Skills --skill macro-regime-detectorgit clone --depth 1 https://github.com/BaggaT236/AI-Trading-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/baggat236/ai-trading-skills/macro-regime-detector)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/macro-regime-detector"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/macro-regime-detector/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/macro-regime-detector"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/macro-regime-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.01062 |
| Opus 5 | $0.00046 | $0.00531 |
| Sonnet 5 | $0.00018 | $0.00212 |
| Haiku 4.5 | $0.00009 | $0.00106 |
Grade A, and why
macro-regime-detector scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.mdreferences/indicator_interpretation_guide.md
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Execute the main analysis script:
uv run python3 skills/macro-regime-detector/scripts/macro_regime_detector.py --output-dir reports/This fetches 600 days of data for 9 ETFs + Treasury rates (~10 API calls total). An FMP API key is required to run this skill (the client raises if it is missing). For individual ETFs whose FMP historical-price endpoint returns nothing, the client automatically falls back to yfinance — this fallback needs no additional API key, but it does not remove the FMP key requirement.
-
Read the generated Markdown report and present findings to user.
-
Provide additional context using
references/historical_regimes.mdwhen user asks about historical parallels.
Prerequisites
- FMP API Key (required): Set
FMP_API_KEYenvironment 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 |
What ships with it
28 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/historical_regimes.md 4.7 KB
- references/indicator_interpretation_guide.md 6.2 KB
- references/regime_detection_methodology.md 5.3 KB
- scripts/calculators/__init__.py 49 B runs code
- scripts/calculators/concentration_calculator.py 5.9 KB runs code
- scripts/calculators/credit_conditions_calculator.py 3.9 KB runs code
- scripts/calculators/equity_bond_calculator.py 6.7 KB runs code
- scripts/calculators/sector_rotation_calculator.py 3.9 KB runs code
- scripts/calculators/size_factor_calculator.py 4.1 KB runs code
- scripts/calculators/utils.py 11 KB runs code
- scripts/calculators/yield_curve_calculator.py 9.6 KB runs code
- scripts/fmp_client.py 15 KB runs code
- scripts/macro_regime_detector.py 9.6 KB runs code
- scripts/report_generator.py 20 KB runs code
- scripts/scorer.py 20 KB runs code
- scripts/tests/conftest.py 314 B runs code
- scripts/tests/test_concentration.py 3.4 KB runs code
- scripts/tests/test_credit_conditions.py 2.2 KB runs code
- scripts/tests/test_equity_bond.py 2.7 KB runs code
- scripts/tests/test_fmp_client.py 9.1 KB runs code
- scripts/tests/test_helpers.py 2.5 KB runs code
- scripts/tests/test_main_cli.py 1.8 KB runs code
- scripts/tests/test_report_generator.py 11 KB runs code
- scripts/tests/test_scorer.py 23 KB runs code
- scripts/tests/test_sector_rotation.py 3.2 KB runs code
- scripts/tests/test_size_factor.py 2.2 KB runs code
- scripts/tests/test_utils.py 5.4 KB runs code
- scripts/tests/test_yield_curve.py 6.3 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 97 lines · 91 tokens per session scan A aacb9e6542de
macro-regime-detector is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 8d ago), licensed MIT. It adds 91 tokens to every session and 1,062 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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