kestrel-strategy

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KESTREL v1.0 — XYZ Macro Breakout Rider. Detects significant hourly price breakouts on commodities, precious metals, indices, and high-volume equities 24/7 on Hyperliquid. Rides the macro trend. Price action is the primary signal; Smart Money is confirmation only. Conservative 3-5x leverage.

2installs

Sourcesenpi-ai/senpi-skills

Added on2026-04-17

NPX Install

npx skill4agent add senpi-ai/senpi-skills kestrel-strategy

SKILL.md Content

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🦅 KESTREL v1.0 — XYZ Macro Breakout Rider

A fundamentally new approach to XYZ trading on Hyperliquid. Where Bald Eagle used SM consensus (thin, lagging on XYZ), Kestrel uses price action as the primary signal and SM as confirmation.

Thesis

When a commodity or equity moves >1.5% in 1 hour 24/7 on Hyperliquid, something macro happened. Unlike crypto where big moves exhaust quickly, commodity and equity macro moves tend to continue for hours or days. Kestrel catches the breakout and rides the trend.

Why this is different from Bald Eagle

	Bald Eagle	Kestrel
Primary signal	SM consensus	Price action (breakout)
SM role	Trigger	Confirmation only
Direction	Contrarian (v4.0)	Momentum (ride the trend)
Trigger condition	SM concentration >3%	1H price move >1.5%
Asset universe	6 assets (CL, BRENTOIL, GOLD, SILVER, SP500, XYZ100)	13 assets (adds AAPL, NVDA, GOOGL, TSLA, AMZN, META, MSFT)

Assets

Commodities: CL, BRENTOIL. Metals: GOLD, SILVER. Indices: SP500, XYZ100. Equities: AAPL, NVDA, GOOGL, TSLA, AMZN, META, MSFT.

Scoring

1H breakout magnitude (2-4 pts) — the core signal
4H trend alignment (0-2 pts)
Volume surge (0-2 pts)
SM confirmation (0-2 pts, can be -1 if SM is heavily opposing)
Funding alignment (0-1 pts)
Spread gate (hard gate — don't trade if spread >0.2%)

MIN_SCORE: 6. Runs 24/7 — Hyperliquid XYZ trades around the clock.

Files

File	Purpose
`scripts/kestrel-scanner.py`	Breakout detection scanner
`scripts/kestrel_config.py`	Config helper
`runtime.yaml`	Wide DSL for macro trend riding

Skill Attribution

When creating a strategy, include

skill_name

and

skill_version

in the call. See

references/skill-attribution.md

for details.