원클릭으로 Manus에서 모든 스킬 실행

intelligence

스타211

포크3

업데이트2026년 7월 15일 07:26

Use when the user asks "what's hot", "what's moving", "any alpha", "show me squeeze setups", "what's the setup on ETH", "is SOL coiled", "should I deploy NEAR" or any market-scan / single-pair-drilldown question. Surfaces Superior Trade's live multi-bucket scoring across Hyperliquid alts + HIP-3 (stocks/indices/commodities/FX) — Squeeze fuel, Stealth accumulation, Coiled spring, Basis flipping. The engine picks the strongest timeframe (15m/1h/4h/24h) per pair per bucket; you don't pick one. Pairs in to the existing strategy → backtest → deployment workflow at api.superior.trade.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

Manus에서 실행

출처

Superior-Trade

Superior-Trade/superior-skills

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

Intelligence

Live ranked alpha scan over Hyperliquid alts + HIP-3 markets. Returns the same data the Intelligence page at https://account.superior.trade/intelligence renders — bucket fits, per-pair best timeframes, snapshots, and recommended deploy templates.

Files in this skill

File	What it covers
`references/buckets.md`	The 4 buckets: Squeeze fuel, Stealth accumulation, Coiled spring, Basis flipping. Setup / Edge / Scoring + AI Critic concerns per bucket. Read this before presenting any scan output to the user.
`references/api.md`	The two endpoints: `GET /v2/intelligence/scan` (list mode) and `GET /v2/intelligence/setup/{pair}` (single-pair detail). Response schemas + examples.
`references/workflow.md`	Recommended end-to-end recipes: scan → pick → setup → backtest → deploy. How to translate a `best_fit` tuple into a `/v2/backtesting` call.
`references/glossary.md`	Plain-English definitions for the trading terms in scan responses (funding, OI, basis, fees-paid notional, OI turnover, CVD, etc.). Reference this when explaining results to a non-trader.

When to call which endpoint

List question ("what's hot", "any squeeze setups", "show me coiled springs in HIP-3") → GET /v2/intelligence/scan with optional bucket and category filters.
Single-pair question ("tell me about ETH", "is NEAR a stealth setup", "should I deploy AVAX") → GET /v2/intelligence/setup/{pair}. Always do this BEFORE backtesting / deploying so the choice is grounded in current data.

Critical: do not improvise rankings

Both endpoints return live, ranked data. Never substitute a market scan from training data — prices are stale, the ranking framework is Superior's, and timeframes are picked by the engine. When presenting:

Lead with the specific best_fit.bucket_title @ best_fit.timeframe (score) tuple per pair.
Cite the snapshot fields that drove the score (e.g. for squeeze: pct_change_24h + funding_paid_notional_usd_per_yr).
Mention bucket_fits only if asked why another bucket wasn't picked.
Reference the AI Critic concerns from references/buckets.md before recommending a deploy.

Caveats

Majors (BTC / ETH / SOL) are excluded by design — this is for alt + HIP-3 alpha discovery. For majors, use the regular price/chart tools.
Pairs below $100K daily volume are filtered out as too thin for live deployment.
HIP-3 stocks (xyz:NVDA, xyz:AAPL, etc.) trade 24/7 but the underlying equities only trade during NYSE hours — see the US Market Closed warning in references/buckets.md § Stocks.
News sentiment is not part of the current scan. The buckets are price + positioning + flow; news comes from external context.

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Use when the user asks about fees, slippage, maker vs taker, post-only orders, fee tiers, fee optimization, why my strategy is losing more than backtest, builder code fee, effective spread, order pricing, or wants to lower trading costs on a Hyperliquid Freqtrade deployment. Also use proactively when the user designs a high-turnover strategy (5m or faster, tight ROI < 0.5%) — fees often dominate edge there.

2026-07-15211

name	intelligence
description	Use when the user asks "what's hot", "what's moving", "any alpha", "show me squeeze setups", "what's the setup on ETH", "is SOL coiled", "should I deploy NEAR" or any market-scan / single-pair-drilldown question. Surfaces Superior Trade's live multi-bucket scoring across Hyperliquid alts + HIP-3 (stocks/indices/commodities/FX) — Squeeze fuel, Stealth accumulation, Coiled spring, Basis flipping. The engine picks the strongest timeframe (15m/1h/4h/24h) per pair per bucket; you don't pick one. Pairs in to the existing strategy → backtest → deployment workflow at api.superior.trade.
version	0.1.0
updated	"2026-05-09T00:00:00.000Z"

Intelligence

Files in this skill

File	What it covers
`references/buckets.md`	The 4 buckets: Squeeze fuel, Stealth accumulation, Coiled spring, Basis flipping. Setup / Edge / Scoring + AI Critic concerns per bucket. Read this before presenting any scan output to the user.
`references/api.md`	The two endpoints: `GET /v2/intelligence/scan` (list mode) and `GET /v2/intelligence/setup/{pair}` (single-pair detail). Response schemas + examples.
`references/workflow.md`	Recommended end-to-end recipes: scan → pick → setup → backtest → deploy. How to translate a `best_fit` tuple into a `/v2/backtesting` call.
`references/glossary.md`	Plain-English definitions for the trading terms in scan responses (funding, OI, basis, fees-paid notional, OI turnover, CVD, etc.). Reference this when explaining results to a non-trader.

When to call which endpoint

List question ("what's hot", "any squeeze setups", "show me coiled springs in HIP-3") → GET /v2/intelligence/scan with optional bucket and category filters.
Single-pair question ("tell me about ETH", "is NEAR a stealth setup", "should I deploy AVAX") → GET /v2/intelligence/setup/{pair}. Always do this BEFORE backtesting / deploying so the choice is grounded in current data.

Critical: do not improvise rankings

Lead with the specific best_fit.bucket_title @ best_fit.timeframe (score) tuple per pair.
Cite the snapshot fields that drove the score (e.g. for squeeze: pct_change_24h + funding_paid_notional_usd_per_yr).
Mention bucket_fits only if asked why another bucket wasn't picked.
Reference the AI Critic concerns from references/buckets.md before recommending a deploy.

Caveats

Majors (BTC / ETH / SOL) are excluded by design — this is for alt + HIP-3 alpha discovery. For majors, use the regular price/chart tools.
Pairs below $100K daily volume are filtered out as too thin for live deployment.
HIP-3 stocks (xyz:NVDA, xyz:AAPL, etc.) trade 24/7 but the underlying equities only trade during NYSE hours — see the US Market Closed warning in references/buckets.md § Stocks.
News sentiment is not part of the current scan. The buckets are price + positioning + flow; news comes from external context.