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AnandaAnugrahHandyanto
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lbo-model

Build end-to-end LBO models in Excel with template-driven formulas.

Updated Jun 19, 2026
Search Tags:#finance#openpyxl#modeling#valuation#lbo#excel-modeling#private-equity
One-click install
npx skills add https://github.com/AnandaAnugrahHandyanto/savarez_agent --skill lbo-model-anandaanugrahhandyanto
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lbo-model
Source: https://github.com/AnandaAnugrahHandyanto/savarez_agent/tree/main/optional-skills/finance/lbo-model
Command: npx skills add https://github.com/AnandaAnugrahHandyanto/savarez_agent --skill lbo-model-anandaanugrahhandyanto

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the creation of leveraged buyout models in Excel, reducing manual setup and calculation errors that slow down PE screening and deal analysis.

Core Features & Use Cases

  • Template-driven modeling that covers Sources & Uses, Operating Model, Debt Schedule, Cash Sweep, and Returns Analysis
  • Headless openpyxl workflow to populate inputs and recalibrate formulas from a user-provided template
  • Use cases include sponsor-side valuation, deal screening, and illustrative LBO scenarios for pitches or internal analyses

Quick Start

Copy the provided LBO template (LBO_Model.xlsx) into your working folder, fill in your assumptions, and run the excel-author recalc.py helper to refresh all 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 an LBO model in Excel for private equity screening?▼

Build an LBO model in Excel by using a template-driven workflow that generates sources & uses, debt schedule, cash sweep, and IRR/MOIC sensitivity analyses for PE scenarios. It automates formula recalibration via openpyxl to reduce manual setup errors.

What is included in a leveraged buyout model for deal analysis?▼

A leveraged buyout model includes sources & uses, an operating model, debt schedule, cash sweep, and exit multiple returns analysis. It enforces template-driven formulas, proper sign conventions, and explicit cash-flow link integrity checks for accurate deal screening.

Can I automate Excel modeling for valuation without manual formula entry?▼

Automate Excel modeling for valuation by using a headless openpyxl workflow to populate inputs and recalibrate formulas from a provided template. Run the recalc helper script to refresh all formulas without manual entry.

How do I calculate IRR and MOIC sensitivity for LBO scenarios in Excel?▼

Calculate IRR and MOIC sensitivity for LBO scenarios by applying template-driven formulas within Excel. The model computes returns analysis based on exit multiples and cash sweep mechanics, outputting sponsor-side valuation metrics.

Do I need openpyxl to run LBO modeling workflows?▼

You need openpyxl to run this LBO modeling workflow because it operates headlessly to populate inputs and enforce template-driven formulas in Excel. The workflow relies on openpyxl to recalculate and write formulas without opening Excel.

What's the best way to ensure cash-flow link integrity in an LBO Excel model?▼

Ensure cash-flow link integrity in an LBO Excel model by enforcing explicit sign conventions and template-driven formulas. The workflow checks link integrity automatically to prevent calculation errors in debt schedules and cash sweep outputs.

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