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Found 170 Skills
Evaluate the probability and path of copper prices breaking through key levels or entering a 'back-and-fill' pullback to support levels using cross-asset signals (global stock market resilience + Chinese interest rate environment).
Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if they are strengthened, weakened, or falsified.
Alpha Vantage API documentation reference - provides comprehensive information about stock data, forex, crypto, technical indicators, and fundamental data APIs.
Chart any technical indicator on a symbol using Plotly. Creates interactive dark-themed charts with candlestick, overlays, and subplots. Supports all 100+ openalgo.ta indicators.
Analyze stock correlations to find related companies and trading pairs. Use this skill whenever the user asks about correlated stocks, related companies, sector peers, trading pairs, or how two or more stocks move together. Triggers include: "what correlates with NVDA", "find stocks related to AMD", "correlation between AAPL and MSFT", "what moves with", "sector peers", "pair trading", "correlated stocks", "when NVDA drops what else drops", "find me a pair for", "stocks that move together", "beta to", "relative performance", "which stocks follow AMD", "supply chain partners", "correlation matrix", "co-movement", "related tickers", "sympathy plays", "if GOOGL moves what else moves", "semiconductor peers", "compare correlation", "hedging pair", "sector clustering", "realized correlation", "rolling correlation", or any request about finding stocks that move in tandem or inversely. Also triggers when the user mentions well-known pairs like AMD/NVDA, GOOGL/AVGO, LITE/COHR and wants to understand or find similar relationships. Always use this skill even if the user only provides one ticker — infer that they want to find correlated peers.
Generate a post-earnings analysis for any stock using Yahoo Finance data. Use when the user wants to review what happened after earnings, understand beat/miss results, see stock reaction, or get an earnings recap. Triggers: "AAPL earnings recap", "how did TSLA earnings go", "MSFT earnings results", "did NVDA beat earnings", "post-earnings analysis", "earnings surprise", "what happened with GOOGL earnings", "earnings reaction", "stock moved after earnings", "EPS beat or miss", "revenue beat or miss", "quarterly results for", "how were earnings", "AMZN reported last night", "earnings call recap", or any request about a company's recent earnings outcome. Use this skill when the user references a past earnings event, even if they just say "AAPL reported" or "how did they do".
Apply DuPont Analysis to decompose Return on Equity (ROE) into profitability, efficiency, and leverage components. Use this skill when the user needs to diagnose why ROE is high or low, compare financial performance drivers across companies, or identify which operational lever to pull — even if they say 'why is our ROE declining' or 'how do we improve returns'.
Finerio Connect integration. Manage data, records, and automate workflows. Use when the user wants to interact with Finerio Connect data.
Scraper de datos de Nasdaq.com via API REST interna: cotizaciones, short interest, financials, institutional holdings, opciones, noticias. Sin API key.
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.
Fetch financial and market data using the yfinance Python library. Use this skill whenever the user asks for stock prices, historical data, financial statements, options chains, dividends, earnings, analyst recommendations, or any market data. Triggers include: any mention of stock price, ticker symbol (AAPL, MSFT, TSLA, etc.), "get me the financials", "show earnings", "what's the price of", "download stock data", "options chain", "dividend history", "balance sheet", "income statement", "cash flow", "analyst targets", "institutional holders", "compare stocks", "screen for stocks", or any request involving Yahoo Finance data. Always use this skill even if the user only provides a ticker — infer intent from context.
This Skill is built based on Eastmoney's authoritative database and the latest underlying market data, supporting natural language queries for market data (real-time quotes, main capital flows, valuations, etc. of stocks, industries, sectors, indices, funds, bonds), financial data (basic information of listed companies, financial indicators, executive information, main business, etc.), and relationship and operation data (associated relationships, enterprise operation data). It prevents models from answering financial data questions based on outdated knowledge and provides authoritative and timely financial data.