analysis▌

Create professional EARNINGS UPDATE REPORTS analyzing quarterly results for companies already under coverage, following institutional standards (JPMorgan, Goldman Sachs, Morgan Stanley format).

You are an expert in competitive intelligence for mobile apps. Your goal is to perform a thorough analysis of the user's competitors and identify actionable opportunities to outperform them.

Data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib. \n \n Covers DataFrame and Series creation, indexing, filtering, and type conversions for structured data handling \n Includes data cleaning techniques: missing value handling, deduplication, string operations, and date/time parsing \n Provides GroupBy aggregation, pivot tables, multi-level indexing, and window functions for exploratory analysis \n Integrates Matplotlib and Seaborn for statistical plotting, trend

Important: This skill assists with variance analysis workflows but does not provide financial advice. All analyses should be reviewed by qualified financial professionals before use in reporting.

Build intelligent agents for investment analysis, risk assessment, and portfolio recommendations. \n \n Integrates financial data collection via yfinance with technical analysis (moving averages, RSI, support/resistance) and fundamental analysis (profitability, valuation, and liquidity ratios) \n Includes risk assessment tools covering volatility, Value at Risk, Sharpe Ratio, and company-specific risk evaluation \n Generates investment recommendations (Strong Buy through Strong Sell) with confid

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

SQL-powered analysis of Excel and CSV files with schema inspection, aggregation, and multi-format export. \n \n Execute arbitrary SQL queries against uploaded data, including joins across multiple files, window functions, and pivot-style aggregations \n Inspect file structure (sheets, columns, data types, row counts) and generate statistical summaries (mean, median, stddev, percentiles, null counts) for numeric and string columns \n Export query results to CSV, JSON, or Markdown; results are cac

Answers: "Where is this token moving? Who is sending it and where?"

Answers: "Is this token held by quality wallets or retail noise?"

Multi-market stock analysis with fundamental and technical evaluation across US, China A-shares, and Hong Kong equities. \n \n Covers fundamental metrics (P/E, P/B, ROE, margins, growth rates) and technical patterns (moving averages, support/resistance, momentum indicators) \n Generates structured analysis reports including valuation assessment, peer comparison, risk factors, and investment thesis \n Supports quick overview or deep-dive analysis modes with customizable focus areas \n Works with