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analyze-stock

Aggregate stock data across five dimensions and generate HTML analysis reports.

Updated Mar 13, 2026
Search Tags:#market analysis#stock analysis#investment research#financial report#equity analysis#parallel data collection
One-click install
npx skills add https://github.com/gmh5225/k-skills --skill analyze-stock-gmh5225
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: analyze-stock
Source: https://github.com/gmh5225/k-skills/tree/main/skills/finance/analyze-stock
Command: npx skills add https://github.com/gmh5225/k-skills --skill analyze-stock-gmh5225

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires akshare, pandas, and includes scripts (resource) components.

What problem does it solve?

Manual stock analysis requires gathering scattered data from multiple sources including real-time prices, news, industry trends, market conditions, and corporate announcements, then cross-referencing and compiling structured reports, which is time-consuming and prone to missing key information for individual investors and financial analysts.

Core Features & Use Cases

  • Parallel 5-dimension data collection: Automatically gather stock price & technical indicators, recent news sentiment, industry competitive landscape, global market environment, and official company announcements via parallel subagents to ensure data timeliness.
  • Cross-dimensional analysis & attribution: Identify consistent and contradictory signals across data dimensions, attribute stock price changes to direct corporate, industry, and market factors, and provide short-term (1-2 weeks) and medium-term (1-3 months) trend forecasts with risk warnings.
  • Standardized report output: Generate a fully formatted HTML report with daily market highlights, 7-day price overview, causal analysis, news summary, industry comparison, and sourced reference links, supporting A-shares, Hong Kong stocks, and US stocks.
  • Use case: Quickly obtain a comprehensive analysis of a stock you are tracking to understand its recent performance, core driving factors, and potential risks without manually collecting data from multiple financial platforms.

Quick Start

Use the analyze-stock skill to generate a full analysis report for Tesla (TSLA) stock.

Frequently Asked Questions about analyze-stock

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a comprehensive stock analysis report without manually gathering data from multiple financial platforms?▼

To generate a comprehensive stock analysis report without manual data gathering, you can automate multi-dimensional data collection covering stock price trends, news sentiment, industry landscape, market environment, and corporate announcements into a standardized HTML output.

Does this stock analysis approach support A-shares, Hong Kong stocks, and US stocks?▼

Yes, this stock analysis approach supports A-shares, Hong Kong stocks, and US stocks by aggregating real-time prices, news sentiment, industry trends, and corporate announcements into standardized HTML reports for investment decision-making.

What is the best way to attribute stock price movements to specific market and industry factors?▼

The best way to attribute stock price movements is cross-dimensional analysis that identifies consistent and contradictory signals across data dimensions, directly linking price changes to corporate, industry, and market factors with sourced reference links.

How do I get short-term and medium-term trend forecasts with risk warnings for individual stocks?▼

To get short-term and medium-term trend forecasts with risk warnings, perform cross-dimensional analysis on stock price trends, news sentiment, and industry landscape to generate 1-2 week and 1-3 month predictions.

Can I use pandas and akshare for parallel financial data collection in investment research?▼

Yes, you can use pandas and akshare for parallel financial data collection in investment research, gathering stock technical indicators, news sentiment, and corporate announcements simultaneously to ensure data timeliness.

What are the limitations of automated equity analysis for understanding recent stock performance?▼

Limitations of automated equity analysis include dependence on timely data aggregation from external sources and the inability to replace human judgment when interpreting contradictory signals across market environment and industry landscape dimensions.

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