Comprehensive US stock analysis including fundamental analysis (financial metrics, business quality, valuation), technical analysis (indicators, chart patterns, support/resistance), stock comparisons, and investment report generation. Use when user requests analysis of US stock tickers (e.g., "analyze AAPL", "compare TSLA vs NVDA", "give me a report on Microsoft"), evaluation of financial metrics, technical chart analysis, or investment recommendations for American stocks.
npx skills add https://github.com/nicepkg/ai-workflow --skill us-stock-analysis
Perform comprehensive analysis of US stocks covering fundamental analysis (financials, business quality, valuation), technical analysis (indicators, trends, patterns), peer comparisons, and generate detailed investment reports. Fetch real-time market data via web search tools and apply structured analytical frameworks.
Always use web search tools to gather current market data:
Primary Data to Fetch:
Search Strategy:
Quality Sources:
This skill supports four types of analysis. Determine which type(s) the user needs:
When to Use: User asks for quick overview or basic info
Steps:
Output Format:
When to Use: User wants financial analysis, valuation assessment, or business evaluation
Steps:
Critical Analyses:
When to Use: User asks for technical analysis, chart patterns, or trading signals
Steps:
Interpretation Guidelines:
When to Use: User asks for detailed report, investment recommendation, or complete analysis
Steps:
Report Must Include:
When to Use: User asks to compare two or more stocks (e.g., "compare AAPL vs MSFT")
Steps:
Output Format: Follow "Comparison Report Structure" in references/report-template.md
General Principles:
Formatting:
Tone:
Load these references as needed during analysis:
references/technical-analysis.md
references/fundamental-analysis.md
references/financial-metrics.md
references/report-template.md
Basic Info:
Fundamental:
Technical:
Comprehensive:
Comparison:
Query the U.S. Treasury Fiscal Data REST API for federal financial data. No API key required. Use for national debt (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates, foreign exchange rates, savings bonds, or U.S. government revenue and spending statistics.
Comprehensive US stock analysis including fundamental analysis (financial metrics, business quality, valuation), technical analysis (indicators, chart patterns, support/resistance), stock comparisons, and investment report generation. Use when user requests analysis of US stock tickers (e.g., "analyze AAPL", "compare TSLA vs NVDA", "give me a report on Microsoft"), evaluation of financial metrics, technical chart analysis, or investment recommendations for American stocks.
> Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Automatically checks system RAM/GPU before loading the model, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model. For classical statistical time series models (ARIMA, SARIMAX, VAR) use statsmodels; for time series classification/clustering use aeon.
Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.
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Cryptofeed - Real-time cryptocurrency market data feeds from 40+ exchanges. WebSocket streaming, normalized data, order books, trades, tickers. Python library for algorithmic trading and market data analysis.
Audit a spreadsheet for formula accuracy, errors, and common mistakes. Scopes to a selected range, a single sheet, or the entire model (including financial-model integrity checks like BS balance, cash tie-out, and logic sanity). Triggers on "audit this sheet", "check my formulas", "find formula errors", "QA this spreadsheet", "sanity check this", "debug model", "model check", "model won't balance", "something's off in my model", "model review".
Generate professional client-facing performance reports with portfolio returns, allocation breakdowns, and market commentary. Suitable for quarterly or annual distribution. Triggers on "client report", "performance report", "quarterly report for [client]", "generate reports", or "client statement".
Take nicepkg/us-stock-analysis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.