Agent Skills › Superior-Trade/superior-skills › intelligence

intelligence

GitHub

用于Hyperliquid及HIP-3市场的实时Alpha扫描，提供挤压燃料、隐蔽积累等策略评分与最佳时间框架推荐，辅助交易决策。

skills/intelligence/SKILL.md Superior-Trade/superior-skills

Trigger Scenarios

询问热门资产或市场动态查询特定交易设置如挤压或隐蔽积累分析具体交易对状态

Install

npx skills add Superior-Trade/superior-skills --skill intelligence -g -y

More Options

Use without installing

npx skills use Superior-Trade/superior-skills@intelligence

指定 Agent (Claude Code)

npx skills add Superior-Trade/superior-skills --skill intelligence -a claude-code -g -y

安装 repo 全部 skill

npx skills add Superior-Trade/superior-skills --all -g -y

预览 repo 内 skill

npx skills add Superior-Trade/superior-skills --list

SKILL.md

Frontmatter

{
    "name": "intelligence",
    "metadata": {
        "updated": 1778284800,
        "version": "0.1.0"
    },
    "description": "Use when the user asks what's hot, what's moving, if there's any alpha, \"show me squeeze setups\", \"what's the setup on ETH\", \"is SOL coiled\", \"should I deploy NEAR\", or any market-scan or pair-drilldown question. Surfaces live scoring for squeeze fuel, stealth accumulation, coiled spring and basis flipping across Hyperliquid alts and HIP-3, choosing the strongest timeframe per pair."
}

Intelligence

Live ranked alpha scan over Hyperliquid alts + HIP-3 markets. Returns the same Intelligence data from Superior Trade — 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. Pass category=both for any open-ended question. The parameter defaults to alts, so a bare call silently returns crypto perps only and never surfaces a single HIP-3 stock, index or commodity — even though this skill advertises them. Narrow to alts or tradfi only when the user asked for one. Add bucket when they named a specific setup.
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.