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llmquant-crypto

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LLMQuant Crypto

LLMQuant 加密货币

This category routes crypto research and trading-context workflows. It covers market regime, token-level diligence, and perpetual funding or basis monitoring.
该类别用于路由加密货币研究和交易相关工作流，涵盖市场态势、代币层面尽职调查以及永续合约资金费率或基差监控。

Routing Rules

路由规则

  1. Identify the asset, chain, venue, horizon, benchmark, and requested decision.
  2. Select the closest workflow below.
  3. Open only that workflow and any referenced local resources.
  4. Use LLMQuant Data for crypto prices, liquidity, funding, open interest, on-chain context, macro, ETF, and risk inputs.
  5. Report timestamps, venue coverage, observation windows, stale notices, and unavailable future inputs.
  1. 确定资产、区块链、交易场所、时间范围、基准指标以及用户请求的决策内容。
  2. 选择下方最匹配的工作流。
  3. 仅打开该工作流及所有引用的本地资源。
  4. 使用LLMQuant Data获取加密货币价格、流动性、资金费率、持仓量、链上信息、宏观数据、ETF以及风险相关输入数据。
  5. 报告时间戳、覆盖的交易场所、观察窗口、数据过期通知以及无法获取的未来输入数据。

Workflow Index

工作流索引

User intentWorkflow
Diagnose the crypto market regime across BTC, ETH, majors, liquidity, leverage, and macro.
workflows/crypto-market-regime.md
Build a token or protocol research memo with tokenomics, usage, valuation, and risk evidence.
workflows/crypto-token-research.md
Monitor perpetual funding, basis, open interest, and leverage crowding.
workflows/crypto-perp-funding-monitor.md
用户意图工作流
诊断BTC、ETH、主流币种、流动性、杠杆及宏观层面的加密货币市场态势。
workflows/crypto-market-regime.md
撰写包含代币经济模型、使用情况、估值及风险依据的代币或协议研究备忘录。
workflows/crypto-token-research.md
监控永续合约资金费率、基差、持仓量及杠杆拥挤情况。
workflows/crypto-perp-funding-monitor.md

LLMQuant Data Contract

LLMQuant 数据协议

Prefer LLMQuant Data when available. The workflows may need these data capabilities:
  • Retrieve crypto spot prices, OHLCV history, realized volatility, drawdowns, correlations, and liquidity.
  • Retrieve perpetual funding, basis, open interest, liquidations, exchange flows, and venue-level timestamps.
  • Retrieve token supply, unlock schedules, protocol usage, revenue, TVL, holder concentration, governance, and security-risk context.
  • Retrieve macro, rates, liquidity, ETF, and equity-market inputs that affect crypto risk appetite.
Fallback:
  • If on-chain, funding, or venue-level data is unavailable, name the missing input and continue only with available price, macro, or user-provided evidence.
  • Do not infer live funding, liquidity, TVL, or holder behavior from memory.
优先使用可用的LLMQuant Data。工作流可能需要以下数据能力：
  • 获取加密货币现货价格、OHLCV历史数据、已实现波动率、回撤、相关性及流动性数据。
  • 获取永续合约资金费率、基差、持仓量、清算数据、交易所资金流及交易场所层面的时间戳。
  • 获取代币供应量、解锁时间表、协议使用情况、收入、TVL、持有者集中度、治理及安全风险相关信息。
  • 获取影响加密货币风险偏好的宏观数据、利率、流动性、ETF及股票市场输入数据。
备选方案：
  • 若链上、资金费率或交易场所层面的数据不可用，需说明缺失的输入项，并仅使用可用的价格、宏观数据或用户提供的信息继续操作。
  • 不得凭记忆推断实时资金费率、流动性、TVL或持有者行为。