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Kirankumar2604
Kirankumar2604COMMUNITY
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stock-analyzer

Synthesize market data, SEC filings, and technical indicators into PDF reports and DCF Excel models.

Updated Apr 28, 2026
Search Tags:#pdf#investment#excel#financial analysis#stocks#dcf#equity research
One-click install
npx skills add https://github.com/Kirankumar2604/solutionChallenge --skill stock-analyzer-kirankumar2604
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stock-analyzer
Source: https://github.com/Kirankumar2604/solutionChallenge/tree/main/.local/secondary_skills/stock-analyzer
Command: npx skills add https://github.com/Kirankumar2604/solutionChallenge --skill stock-analyzer-kirankumar2604

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires yfinance, fpdf2, openpyxl, matplotlib, pandas, and includes scripts (resource) components.

What problem does it solve?

This skill solves the challenge of performing deep, data-backed financial analysis by automating the retrieval of market data, SEC filings, and technical indicators, ensuring you have a structured, professional research report without the manual legwork.

Core Features & Use Cases

  • Automated Research Pipeline: Integrates yfinance data, SEC EDGAR filings, and technical analysis to generate comprehensive equity research reports.
  • Dual-Deliverable Generation: Simultaneously produces a professional PDF research report and a dynamic DCF Excel model with sensitivity and scenario analysis.
  • Use Case: When evaluating a potential investment, use this skill to pull real-time financials, compare against sector peers, and generate a multi-page report including valuation models and technical charts.

Quick Start

Use the stock-analyzer skill to generate a full research report and DCF model for the ticker NVDA with AMD and INTC as peers.

Frequently Asked Questions about stock-analyzer

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

FAQPage Schema
How do I automate equity research with SEC filings and real-time market data?▼

Automating equity research involves synthesizing real-time market data, SEC EDGAR filings, and technical indicators into structured reports. This skill builds an automated pipeline using yfinance to retrieve financial metrics and generate professional analysis without manual data entry.

Can I generate a DCF Excel model with sensitivity analysis for stock valuation?▼

Yes, you can generate a dynamic DCF Excel model with sensitivity and scenario analysis. The skill uses openpyxl to produce Excel deliverables alongside PDF research reports, enabling data-driven valuation modeling for investment insights.

What is the best way to compare a single stock against its sector peers?▼

The best way to perform peer comparison is to evaluate a target ticker alongside specified sector peers. This skill pulls real-time financials for each company, compares their performance metrics, and generates charts for visual sector-level evaluation.

Does this stock analysis tool require yfinance and matplotlib to generate PDF reports?▼

Yes, the automated research pipeline requires yfinance for market data retrieval and matplotlib for technical chart generation. It uses fpdf2 to compile the synthesized financial metrics, valuation models, and charts into a multi-page PDF report.

What are the limitations of using automated data pipelines for financial analysis?▼

Automated financial analysis pipelines depend on the availability and accuracy of real-time yfinance data and SEC EDGAR filings. Limitations include potential delays in SEC filing updates and the need to validate automated DCF valuation assumptions before making investment decisions.

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