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lbo-model

Build Excel LBO models with formula-driven sources-and-uses, debt schedules, and returns.

19|4|Updated Apr 22, 2026
Search Tags:#openpyxl#excel#sensitivity analysis#irr#leveraged buyout#debt schedule#lbo modeling
One-click install
npx skills add https://github.com/carterwayneskhizeine/hermes-agent-windows-R --skill lbo-model-carterwayneskhizeine
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lbo-model
Source: https://github.com/carterwayneskhizeine/hermes-agent-windows-R/tree/main/optional-skills/finance/lbo-model
Command: npx skills add https://github.com/carterwayneskhizeine/hermes-agent-windows-R --skill lbo-model-carterwayneskhizeine

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires excel-author, and includes scripts (resource) components.

What problem does it solve?

This Skill helps you create leveraged buyout (LBO) models that are consistent, formula-driven, and ready for valuation-focused decisioning instead of manual spreadsheet guesswork.

Core Features & Use Cases

  • Template-driven LBO modeling: Builds an Excel LBO using an attached template (or the standard LBO_Model.xlsx) to ensure the model’s structure matches professional layouts.
  • Formula-first calculations: Writes calculations as Excel formulas (not hardcoded Python outputs) so results update dynamically with your inputs.
  • Finance outputs for screening: Produces core LBO components such as Sources & Uses, operating projections, debt schedule logic, cash sweep assumptions, and returns outputs like IRR and MOIC with sensitivity tables.

Quick Start

Create an LBO model by attaching your preferred Excel template (or letting the standard template be used) and provide your deal assumptions to generate an updated .xlsx file with linked formulas.

Frequently Asked Questions about lbo-model

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

FAQPage Schema
How do I build a leveraged buyout model in Excel with dynamic formulas?▼

This Skill builds a leveraged buyout model by generating an .xlsx file with all calculations written as Excel formulas compatible with openpyxl, ensuring results update dynamically with your inputs.

Can I generate IRR and MOIC sensitivity tables for an LBO model?▼

Yes, the LBO model produces returns outputs including IRR and MOIC with sensitivity tables, alongside sources-and-uses, operating projections, and debt schedule dynamics for comprehensive screening.

Does openpyxl support writing Excel formulas for a debt schedule and cash sweep?▼

openpyxl supports writing Excel formulas for debt schedule and cash sweep behavior. The Skill writes formula-first calculations rather than hardcoded Python outputs, requiring recalculation via excel-author before delivery.

What's the best way to create an Excel LBO template for PE-style screening?▼

Use a template-driven approach by attaching your preferred Excel template or letting the standard LBO_Model.xlsx be used, ensuring the model structure matches professional layouts for PE-style screening and sponsor-case valuation.

Do I need excel-author to recalculate LBO models generated with openpyxl?▼

Yes, excel-author is required to recalculate LBO models generated with openpyxl. Because the Skill writes formulas instead of hardcoded Python outputs, the .xlsx file requires recalculation via excel-author before delivery.

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