Loading...
Loading...
Found 197 Skills
A Tushare data research skill for Chinese natural language. It converts requests like "How has this stock been performing lately?", "Help me check the financial report trend", "Which sector is the strongest recently?", "What are northbound funds buying?", "Export a market data report for me" into executable workflows for data acquisition, cleaning, comparison, filtering, export, and brief analysis. It applies to research scenarios such as A-shares, indices, ETFs/funds, finance, valuation, capital flows, announcements & news, sector concepts, and macroeconomic data.
跨市场股票技术指标服务。支持 A股/港股/美股 27种技术指标，包括 MA/EMA/RSI/MACD/KDJ/布林带/ADX/ATR/CCI/VWAP等。 当用户询问"RSI""MACD""布林带""技术指标""KDJ""OBV"等时触发。 ⚠️ 加密货币技术指标请使用 crypto-indicators skill。
Finage integration. Manage data, records, and automate workflows. Use when the user wants to interact with Finage data.
Earnings estimate revision analysis for listed companies via Longbridge — tracks analyst consensus revision direction (upgrade / downgrade), earnings surprise (SUE = standardised unexpected earnings), PEAD post-earnings drift signals (consecutive beats + upward revisions = positive momentum), and management guidance revision impact. Builds on raw data from longbridge-consensus. Triggers: "预期修正", "盈利修正", "分析师上调", "分析师下调", "超预期", "低于预期", "PEAD", "财报后漂移", "业绩意外", "管理层指引", "預期修正", "盈利修正", "分析師上調", "分析師下調", "超預期", "低於預期", "財報後漂移", "業績意外", "管理層指引", "earnings revision", "estimate revision", "analyst upgrade", "analyst downgrade", "beat miss surprise", "SUE", "PEAD post-earnings drift", "guidance revision", "estimate cut raise".
Retrieve year-over-year growth in balance sheet items including Total Assets, Total Liabilities, Shareholders Equity, Cash, and Inventories. Use when analyzing company financial position trends, capital structure changes, or liquidity management.
Root-cause a reconciliation break to its source transaction or posting — follow the audit trail from the break row back to the originating entry on each side and state what differs and why. Use after gl-recon has classified a break.
Datos de CBOE via APIs publicas: cotizaciones delayed de indices, futuros VX, charts intraday, most-active, market summary (equities + opciones), symbol lookup, futures products. Sin API key.
Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group analysis via Longbridge. Frameworks: investment proposals, coverage initiation, stock research, competitive analysis, financial planning, and DeFi/on-chain analysis. Triggers: "机构评级", "目标价", "一致预期", "EPS预测", "内部人交易", "空头", "行业排名", "投资提案", "首次覆盖", "竞争格局", "财务规划", "DeFi收益", "链上数据", "機構評級", "目標價", "一致預期", "內部人交易", "空頭", "投資提案", "首次覆蓋", "競爭格局", "鏈上數據", "analyst rating", "price target", "consensus", "insider trades", "short interest", "coverage initiation", "DeFi yield", "on-chain", "earnings calendar", "finance calendar", "财报日历", "下周谁财报", "下周财报", "下周有哪些财报", "哪些财报", "谁财报", "FOMC", "非农", "股东", "谁持有", "股東", "基金持仓", "基金持倉", "機構評級", "目標價", "財務規劃"
Retrieve year-over-year growth in income statement items including Revenue, Gross Profit, Operating Income, Net Income, and EPS Diluted. Use when analyzing company financial growth trends, comparing fiscal year performance, or identifying profitability inflection points.
Build and deploy agentic finance applications on the Alva platform. Access 250+ financial data sources (crypto, equities, macro, on-chain, social), run cloud-side analytics, backtest trading strategies, and release interactive playbooks -- all from your AI agents.
Decompose Return on Equity into component ratios to identify performance drivers. Use for financial analysis, performance benchmarking, and identifying improvement opportunities.
This skill is based on the search capability of Eastmoney Miaoxiang, with intelligent source screening tailored for financial scenarios. It is used to obtain time-sensitive information or event-specific information, including news, announcements, research reports, policies, trading rules, specific events, various impact analyses, and non-common-sense information that requires external data retrieval. It prevents AI from referencing non-authoritative and outdated information when searching for financial scenario information.