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.

Install

openclaw skills install @superior-ai/intelligence

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

FileWhat it covers
references/buckets.mdThe 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.mdThe two endpoints: GET /v2/intelligence/scan (list mode) and GET /v2/intelligence/setup/{pair} (single-pair detail). Response schemas + examples.
references/workflow.mdRecommended end-to-end recipes: scan → pick → setup → backtest → deploy. How to translate a best_fit tuple into a /v2/backtesting call.
references/glossary.mdPlain-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:

  1. Lead with the specific best_fit.bucket_title @ best_fit.timeframe (score) tuple per pair.
  2. Cite the snapshot fields that drove the score (e.g. for squeeze: pct_change_24h + funding_paid_notional_usd_per_yr).
  3. Mention bucket_fits only if asked why another bucket wasn't picked.
  4. 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.