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Found 67 Skills
Mainstream Spot Order v1.0 — Multi-chain DEX spot trading system. 6-signal ensemble (Momentum, EMA, RSI, MACD, BB, BTC Overlay) on 15m bars, 6 built-in pairs (SOL, ETH, BTC, BNB, AVAX, DOGE), auto-research strategy optimization, per-pair data collection + backtesting + paper/live trading. onchainos CLI driven, Agentic Wallet TEE signing, zero pip dependencies.
Trade execution modelling framework (backtesting analysis only) via Longbridge — covers slippage models (linear / square-root market impact), VWAP/TWAP execution logic, market impact cost estimation (Kyle lambda), volume participation rate (POV) strategy. Helps quant traders build realistic execution assumptions in backtests. Triggers: "执行模型", "滑点模型", "VWAP执行", "TWAP执行", "市场冲击", "执行成本", "成交量参与率", "交易执行", "執行模型", "滑點模型", "VWAP執行", "TWAP執行", "市場冲擊", "執行成本", "交易執行", "execution model", "slippage model", "VWAP", "TWAP", "market impact", "execution cost", "volume participation rate", "Kyle lambda", "square root model", "POV strategy".
Complete Guide to QMT (Xuntou High-Speed Strategy Trading System) Python Strategy Development. Covers strategy writing, backtesting, live trading, API references, and code examples. Use this skill when developing QMT quantitative strategies or querying QMT APIs.
Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.
Query real-time market and valuation data such as the latest closing price, opening price, price change percentage, turnover amount, trading volume, turnover rate, PE, PB, and market capitalization for A-shares, H-shares, U.S. stocks, and their indices. Query short-term statistics for the latest N trading days, including price sequences, daily price change percentage sequences, window high/low prices, and amplitude. Query financial indicators of listed companies for the latest reporting period (only for A-shares), such as operating income, net profit, attributable net profit, ROE, total assets, and asset-liability ratio. Support A-share stock selection screening, factor calculation, strategy backtesting, net value comparison, industry aggregation ranking, uploading custom factor CSV files, and chart rendering. Currently, H-shares and U.S. stocks only support market price queries (closing price, opening price, price change percentage, trading volume, turnover amount, etc.). Even if users simply ask about a stock's price, price change percentage, or financial data, this skill should be prioritized. Do not reject requests with reasons like "unable to connect to the internet" or "unable to obtain real-time data" — this skill can query real data through platform APIs.
MiniQMT Xuntou Quantitative Trading Interface, based on the XtQuant Python library, supports market data acquisition (K-line, tick data, financial data, etc.) and trading operations (order placement, order cancellation, querying assets/orders/positions) for A-shares, futures, and options. It is used when users need to obtain real-time/historical market data from MiniQMT, conduct quantitative trading, or perform backtesting.
Deploy and manage live trading agents on Hyperliquid. ⚠️ HIGH RISK - REAL CAPITAL AT STAKE ⚠️ Provides deployment_create (launch agent, $0.50), deployment_list (monitor), deployment_start/stop (control), and account tools (credit management). Supports EOA (1 deployment max) and Hyperliquid Vault (200+ USDC required, unlimited deployments). CRITICAL: NEVER deploy without thorough backtesting (6+ months, Sharpe >1.0, drawdown <20%). Start small, monitor daily, define exit criteria before deploying.
Starter Coach V2 — conversational 6-step skill that guides users to build their own automated DEX spot-trading bot on OKX DEX. Onboard → User Profile → Build Strategy → Paper Trade → Go Live. Uses OnchainOS CLI for all on-chain data, backtesting, and trade execution. No freeform trading code — emits validated JSON strategy specs. Triggers: starter coach, trading bot builder, strategy builder, help me build a bot, vibe trading, paper trade, backtest strategy, go live trading, build trading strategy, 交易机器人, 策略构建, 量化策略, 自动交易, 做单机器人, 帮我建策略
Guide the design and implementation of automated pre-trade compliance systems that validate orders before execution. Use when building a compliance rule engine for an RIA or broker-dealer, configuring hard blocks and soft blocks, maintaining restricted and watch lists including MNPI-driven restrictions, setting concentration limits at security/sector/issuer level, implementing position limits or short selling controls, enforcing wash sale detection or free-riding prevention or pattern day trader identification, applying client-specific ESG screens or legal constraints, designing compliance override workflows with authorization and documentation, backtesting compliance rules, or evaluating compliance check latency impact on execution quality.
Build and operate predictive models for logistics networks—demand forecasting at SKU/location/lane granularity; inventory positioning and safety stock optimization interfaces; ETA and lead-time prediction; capacity and congestion signals; route and network flow forecasting at model-integration level; cold chain and perishables; promotion and seasonality; model monitoring, drift, and backtesting against operational KPIs (fill rate, OTIF, WMAPE/MAPE). Use for predictive logistics, demand forecasting logistics, ETA prediction, inventory positioning, safety stock optimization, OTIF forecast, lane demand, WMAPE, logistics ML, capacity forecasting logistics, or cold chain forecast—not pure OR/MIP without logistics domain (operations-research-algorithm-developer), supply chain strategy only (supply-chain-manager), WMS feature dev (wms-developer), fleet telematics ingestion (geospatial-telematics-developer), generic ML without logistics (data-scientist), or EDI document mapping (edi-engineer).
生成 akquant 框架的可执行量化策略代码，涵盖数据接口、事件驱动、风控与优化；当用户需要开发 akquant量化策略 时使用
Router skill for LLMQuant options workflows. Use when the user needs IV rank, option scoring, strategy construction, Greeks, P&L simulation, volatility surface, unusual activity, earnings IV crush, backtests, or hedges.