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dcf-model

Build end-to-end Excel DCF models with openpyxl formulas and sensitivity grids.

17|4|Updated Mar 11, 2026
Search Tags:#openpyxl#excel#valuation#financial-modeling#dcf#sensitivity-analysis#wacc
One-click install
npx skills add https://github.com/yuping322/financial-services-plugins-new --skill dcf-model-yuping322
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dcf-model
Source: https://github.com/yuping322/financial-services-plugins-new/tree/main/financial-analysis/skills/dcf-model
Command: npx skills add https://github.com/yuping322/financial-services-plugins-new --skill dcf-model-yuping322

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill eliminates manual, error-prone DCF construction by programmatically building institutional-quality Excel DCF models that include validated historical analysis, scenario assumptions, WACC calculation, terminal value, and fully populated sensitivity tables.

Core Features & Use Cases

  • Programmatic data retrieval and validation from MCP servers, user inputs, and web sources for historical financials and market data.
  • Automated Excel model creation using openpyxl with predefined layout planning, formula population, cell comments for all hardcoded inputs, and enforced recalculation and validation via recalc.py.
  • Comprehensive outputs including 5-10 year projections, mid-year discounting, perpetuity and exit multiple terminal values, Bear/Base/Bull scenario blocks, and three 5x5 sensitivity grids (75 formula cells total) for client-ready valuations.
  • Use case: Investment bankers or equity analysts needing a repeatable, auditable DCF delivered as a validated .xlsx with scenario selector and sensitivity analysis.

Quick Start

Create a 5-year DCF Excel model for ticker AAPL using MCP or provided financials, include Bear/Base/Bull scenarios, populate all sensitivity tables with full-recalc formulas, add source comments to inputs, and return the final .xlsx file.

Frequently Asked Questions about dcf-model

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

FAQPage Schema
How do I build a DCF model in Excel with sensitivity analysis?▼

You can programmatically build an institutional-quality DCF model in Excel by populating openpyxl formulas for 5-10 year projections, WACC calculation, terminal value, and 5x5 sensitivity grids, followed by mandatory post-creation recalculation validation.

What is the best way to automate DCF valuation for multiple scenarios?▼

Automating DCF valuation is best handled by generating Bear, Base, and Bull scenario blocks programmatically within an Excel workbook, using openpyxl to populate formula-driven projections and sensitivity tables rather than manual data entry.

Does openpyxl support creating Excel financial models with cell comments and formulas?▼

Yes, openpyxl supports institutional financial modeling by populating Excel formulas and attaching mandatory cell comments to hardcoded inputs, ensuring auditable DCF assumptions and structural validation.

Can I generate WACC and terminal value calculations in Excel without manual formulas?▼

You can generate WACC, perpetuity, and exit multiple terminal value calculations programmatically by using openpyxl to populate the required Excel formulas directly into the valuation model cells.

How do I validate an Excel DCF model after programmatic generation?▼

You validate a programmatically generated Excel DCF model by running a post-creation recalculation process that ensures all populated formulas, sensitivity grids, and scenario calculations execute correctly without errors.

What inputs do I need for an automated DCF Excel model?▼

Automated DCF Excel models require historical financial statements and market data retrieved from MCP servers, web sources, or direct user inputs to populate projections, WACC, and terminal value calculations.

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