Total 50,510 skills, Data Processing has 2560 skills
Showing 12 of 2560 skills
通过Eureka专利数据平台获取专利摘要附图。当用户提到专利摘要附图、专利图纸、专利示意图、专利图片、摘要附图检索、专利图片查询、Eureka摘要附图、patent abstract images, patent drawings, patent illustrations, Eureka, abstract image lookup, patent figure时触发此技能。即使用户未明确说"摘要附图"，只要其需要查看专利文件中的图纸或示意图，也应触发此技能。
查询并分析极目数据的亚马逊细分市场洞察，包括市场指标、买家评论、竞争格局、价格走势和增长趋势。当用户提到细分市场分析、市场洞察、细分市场数据、市场竞争分析、品牌集中度、新品上架成功率、断货率、价格趋势、评论洞察、市场需求评分、niche market insights, market metrics, competition analysis, price trends, growth trends, Jiimore data, market intelligence, out-of-stock rate时触发此技能。即使用户未明确提及"极目"或"细分市场"，只要其需求涉及通过市场ID查询特定亚马逊细分市场的市场级情报，也应触发此技能。
Hedging strategy design framework — Beta hedge ratio (portfolio vs benchmark), option protection strategies (protective put / collar), tail-risk hedges (VIX-related / gold / treasuries), cross-asset hedges (currency risk), and hedge cost assessment (option premium vs protection value). Triggers: "对冲", "对冲策略", "Beta对冲", "保护性看跌", "领口策略", "尾部风险", "汇率对冲", "对冲比率", "對冲", "對冲策略", "Beta對冲", "保護性看跌", "領口策略", "尾部風險", "hedging", "hedge strategy", "beta hedge", "protective put", "collar strategy", "tail risk hedge", "currency hedge", "hedge ratio", "portfolio insurance".
Factor research framework for evaluating single-factor effectiveness across A-shares, HK, and US stocks — information coefficient (IC), information ratio (IR), decile portfolio backtests, and IC decay (serial autocorrelation). Triggers: "因子研究", "IC分析", "信息比率", "分层回测", "因子有效性", "单因子测试", "因子衰减", "因子评估", "IC分析", "信息比率", "分層回測", "因子有效性", "單因子測試", "factor research", "information coefficient", "IC", "IR information ratio", "factor backtest", "decile portfolio", "factor decay", "factor effectiveness".
Behavioral finance application framework — identify cognitive biases in markets (overreaction, underreaction, disposition effect, anchoring, herding), translate them into quantifiable trading signals (momentum / reversal), and assess whether current market sentiment shows systematic bias. Triggers: "行为金融", "认知偏差", "过度反应", "反应不足", "处置效应", "锚定效应", "羊群效应", "市场情绪偏差", "行為金融", "認知偏差", "過度反應", "反應不足", "處置效應", "錨定效應", "羊群效應", "behavioral finance", "cognitive bias", "overreaction", "underreaction", "disposition effect", "anchoring bias", "herding", "sentiment bias", "behavioral economics".
US ETF capital-flow analysis via Longbridge Securities — tracks institutional money migration via ETF creation/redemption changes, sector breadth signals, and thematic momentum. Analyses major SPDR sector ETFs (XLK / XLF / XLE / XLV etc.) for net inflow / outflow to gauge industry rotation and risk-appetite shifts. Triggers: "ETF资金流", "ETF流向", "美国ETF", "板块ETF", "XLK", "XLF", "XLE", "机构资金迁移", "行业轮动信号", "ETF資金流", "ETF流向", "美國ETF", "板塊ETF", "機構資金遷移", "ETF flow", "US ETF flow", "sector ETF", "SPDR", "institutional flow", "sector rotation signal", "ETF inflow outflow", "fund flow".
Comprehensive market scanner — combines real-time quotes, capital flow (large/medium/small order distribution), and candlestick data for multi-symbol technical analysis (MACD / RSI / Bollinger Bands computed from OHLCV). Supports batch multi-symbol scanning. Triggers: "行情扫描", "综合行情", "多标的扫描", "行情数据", "实时行情综合", "技术+资金综合", "行情指标", "行情監控", "行情掃描", "綜合行情", "多標的掃描", "技術+資金綜合", "market scanner", "comprehensive quote", "multi-stock scan", "real-time data", "market data query", "technical plus capital flow", "market overview", "batch quote", "technical indicators", "MACD RSI scan".
Sector screening and ranking — filter and rank A-share / HK / US industry sectors by valuation (PE/PB), capital inflow, price performance (1d/5d/20d), and turnover rate. Outputs a sector leaderboard. Triggers: "板块筛选", "行业筛选", "强势板块", "弱势板块", "板块排行", "行业排名", "资金流入板块", "涨幅最大板块", "板塊篩選", "行業篩選", "強勢板塊", "弱勢板塊", "板塊排行", "行業排名", "sector screener", "sector filter", "sector ranking", "top sectors", "hot sectors", "capital inflow sectors", "sector scan", "industry ranking", "sector performance", "best sectors today".
Integrate Apify into an existing JavaScript/TypeScript or Python application using the apify-client package. Use when adding web scraping, automation, or data extraction capabilities to an existing app via the Apify API.
Tableau integration. Manage data, records, and automate workflows. Use when the user wants to interact with Tableau data.
Spatial data gridding and interpolation with a machine-learning style API. Process geographic and Cartesian point data onto regular grids. Use when Claude needs to: (1) Grid scattered spatial data onto regular grids, (2) Interpolate point data using splines, linear, or cubic methods, (3) Process geographic coordinates with projections, (4) Reduce large datasets using block averaging, (5) Remove polynomial trends from spatial data, (6) Cross-validate gridding parameters, (7) Create processing pipelines with Chain, (8) Grid vector data like GPS velocities.
Geochemistry data analysis and visualization for igneous, metamorphic, and sedimentary rocks. Use when Claude needs to: (1) Create ternary diagrams for compositional data, (2) Plot REE spider diagrams with normalization, (3) Build TAS or other classification diagrams, (4) Apply log-ratio transforms to compositional data, (5) Calculate CIPW norms, (6) Generate Harker variation diagrams, (7) Compute element ratios and anomalies.