Agent skill

Lbo Model

by w95 in w95/awesome-claude-corporate-skills

This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations.

MITAuto-check passedDocuments & Office

Install Lbo Model

skills CLI
$ npx skills add w95/awesome-claude-corporate-skills --skill lbo-model -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install w95/awesome-claude-corporate-skills lbo-model --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/02-finance-accounting/lbo-model .claude/skills/lbo-model && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
lbo-model
GitHub stars
237
Used in
1 other repo
Token cost
~3k tokens
SKILL.md length
1,505 words
Files
1
Skills in repo
39
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations.

  • Works in 3 steps: Check the Template → Check the User's Instructions → Apply Standard Practice
  • Tasks that involve Excel spreadsheets
  • SKILL.md covers TEMPLATE REQUIREMENT, CRITICAL INSTRUCTIONS FOR…, TEMPLATE ANALYSIS PHASE - DO… and FILLING FORMULAS - GENERAL…, plus 2 more sections
  • Calls python

What it does

Lbo Model is an agent skill from w95/awesome-claude-corporate-skills. This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering Excel spreadsheets and Accounting and bookkeeping. It works with Microsoft Excel. The repository describes itself as: 166 production-ready Claude AI skills organized by corporate role — executive leadership, finance, HR, marketing, sales, legal, operations, engineering, product, data, customer…. The licence is MIT.

When your agent uses it

  • Tasks that involve Excel spreadsheets
  • Tasks that involve Accounting and bookkeeping

Example prompts

  • “/lbo-model”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Check the Template
  2. Check the User's Instructions
  3. Apply Standard Practice

What it can do on your machine

Read from SKILL.md and the folder at commit 78dbc7c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Lbo Model loads about 3k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 1,505 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~81
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from w95/awesome-claude-corporate-skills at commit 78dbc7c, republished under its MIT licence (© w95). 1,505 words, ~2,987 tokens.

Download SKILL.mdSave it as .claude/skills/lbo-model/SKILL.md (or your agent's skills folder).
name
lbo-model
description
This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.

TEMPLATE REQUIREMENT

This skill uses templates for LBO models. Always check for an attached template file first.

Before starting any LBO model:

  1. If a template file is attached/provided: Use that template's structure exactly - copy it and populate with the user's data
  2. If no template is attached: Ask the user: "Do you have a specific LBO template you'd like me to use? If not, I can use the standard template which includes Sources & Uses, Operating Model, Debt Schedule, and Returns Analysis."
  3. If using the standard template: Copy examples/LBO_Model.xlsx as your starting point and populate it with the user's assumptions

IMPORTANT: When a file like LBO_Model.xlsx is attached, you MUST use it as your template - do not build from scratch. Even if the template seems complex or has more features than needed, copy it and adapt it to the user's requirements. Never decide to "build from scratch" when a template is provided.


CRITICAL INSTRUCTIONS FOR CLAUDE - READ FIRST

Core Principles
  • Every calculation must be an Excel formula - NEVER compute values in Python and hardcode results into cells. The model must be dynamic and update when inputs change.
  • Use the template structure - Follow the organization in examples/LBO_Model.xlsx or the user's provided template. Do not invent your own layout.
  • Use proper cell references - All formulas should reference the appropriate cells. Never type numbers that should come from other cells.
  • Maintain sign convention consistency - Follow whatever sign convention the template uses (some use negative for outflows, some use positive). Be consistent throughout.
  • Work section by section - Complete one section fully before moving to the next, as later sections often depend on earlier ones.
Formula Color Conventions
  • Blue (0000FF): Hardcoded inputs - typed numbers that don't reference other cells
  • Black (000000): Formulas with calculations - any formula using operators or functions (=B4*B5, =SUM(), =-MAX(0,B4))
  • Purple (800080): Links to cells on the same tab - direct references with no calculation (=B9, =B45)
  • Green (008000): Links to cells on different tabs - cross-sheet references (=Assumptions!B5, ='Operating Model'!C10)
Number Formatting Standards
  • Currency: $#,##0;($#,##0);"-" or $#,##0.0 depending on template
  • Percentages: 0.0% (one decimal)
  • Multiples: 0.0"x" (one decimal)
  • MOIC/Detailed Ratios: 0.00"x" (two decimals for precision)
  • All numeric cells: Right-aligned

Clarify Requirements First

Before filling any formulas:

  • Examine the template structure - Identify all sections, understand the timeline (which columns are which periods), note any existing formulas
  • Ask the user if anything is unclear - If the template structure, calculation methods, or requirements are ambiguous, ask before proceeding
  • Confirm key assumptions - Any key inputs, calculation preferences, or specific requirements
  • ONLY AFTER understanding the template, proceed to fill in formulas

TEMPLATE ANALYSIS PHASE - DO THIS FIRST

Before filling any formulas, examine the template thoroughly:

  1. Map the structure - Identify where each section lives and how they relate to each other. Note which sections feed into others.

  2. Understand the timeline - Which columns represent which periods? Is there a "Closing" or "Pro Forma" column? Where does the projection period start?

  3. Identify input vs formula cells - Templates often use color coding, borders, or shading to indicate which cells need inputs vs formulas. Respect these conventions.

  4. Read existing labels carefully - The row labels tell you exactly what calculation is expected. Don't assume - read what the template is asking for.

  5. Check for existing formulas - Some templates come partially filled. Don't overwrite working formulas unless specifically asked.

  6. Note template-specific conventions - Sign conventions, subtotal structures, how sections are organized, whether there are separate tabs for different components, etc.


FILLING FORMULAS - GENERAL APPROACH

For each cell that needs a formula, follow this hierarchy:

Step 1: Check the Template
  • Does the cell already have a formula? If yes, verify it's correct and move on.
  • Is there a comment or note indicating the expected calculation?
  • Does the row/column label make the calculation obvious?
  • Do neighboring cells show a pattern you should follow?
Step 2: Check the User's Instructions
  • Did the user specify a particular calculation method?
  • Are there stated assumptions that affect this formula?
  • Any special requirements mentioned?
Step 3: Apply Standard Practice
  • If neither template nor user specifies, use standard LBO modeling conventions
  • Document any assumptions you make
  • If genuinely uncertain, ask the user

COMMON PROBLEM AREAS

The following calculation patterns frequently cause issues across LBO models. Pay special attention when you encounter these:

Balancing Sections
  • When two sections must equal (e.g., Sources = Uses), one item is typically the "plug" (balancing figure)
  • Identify which item is the plug and calculate it as the difference
Tax Calculations
  • Tax formulas should only reference the relevant income line and tax rate
  • Should NOT reference unrelated sections (e.g., debt schedules)
  • Consider whether losses create tax shields or are simply ignored
Interest and Circular References
  • Interest calculations can create circularity if they reference balances affected by cash flows
  • Use Beginning Balance (not average or ending) to break circular references
  • Pattern: Interest → Cash Flow → Paydown → Ending Balance (if interest uses ending balance, this circles back)
Debt Paydown / Cash Sweeps
  • When multiple debt tranches exist, there's usually a priority order
  • Cash sweep should respect the priority waterfall
  • Balances cannot go negative - use MAX or MIN functions appropriately
Returns Calculations (IRR/MOIC)
  • Cash flows must have correct signs: Investment = negative, Proceeds = positive
  • If using XIRR, need corresponding dates
  • If using IRR, cash flows should be in consecutive periods
  • MOIC = Total Proceeds / Total Investment
Sensitivity Tables
  • Excel's DATA TABLE function may not work with openpyxl
  • May need explicit formulas that reference row/column headers
  • Each cell should show a DIFFERENT value - if all same, formulas aren't varying correctly
  • Use mixed references (e.g., $A5 for row input, B$4 for column input)

Show full SKILL.md (586 more words)Show less

VERIFICATION CHECKLIST - RUN AFTER COMPLETION

Run Formula Validation
bash
python /mnt/skills/public/xlsx/recalc.py model.xlsx

Must return success with zero errors.

Section Balancing
  • Any sections that must balance (Sources/Uses, Assets/Liabilities) balance exactly
  • Plug items are calculated correctly as the balancing figure
  • Amounts that should match across sections are consistent
Income/Operating Projections
  • Revenue/top-line builds correctly from drivers or growth rates
  • All cost and expense items calculated appropriately
  • Subtotals and totals sum correctly
  • Margins and ratios are reasonable
  • Links to assumptions are correct
Balance Sheet (if applicable)
  • Assets = Liabilities + Equity (must balance)
  • All items link to appropriate schedules or roll-forwards
  • Beginning balances = prior period ending balances
  • Check row included and shows zero
Cash Flow (if applicable)
  • Starts with correct income figure
  • Non-cash items added/subtracted appropriately
  • Working capital changes have correct signs
  • Ending Cash = Beginning Cash + Net Cash Flow
  • Cash balances are consistent across statements
Supporting Schedules
  • Roll-forward schedules balance (Beginning + Changes = Ending)
  • Schedules link correctly to main statements
  • Calculated items use appropriate drivers
  • All periods are calculated consistently
Debt/Financing Schedules (if applicable)
  • Beginning balances tie to sources or prior period
  • Interest calculated on appropriate balance (typically beginning)
  • Paydowns respect cash availability and priority
  • Ending balances cannot be negative
  • Totals sum tranches correctly
Returns/Output Analysis
  • Exit/terminal values calculated correctly
  • All relevant adjustments included
  • Cash flow signs are correct (negative for investment, positive for proceeds)
  • IRR/MOIC formulas reference complete ranges
  • Results are reasonable for the scenario
Sensitivity Tables (if applicable)
  • Row and column headers contain appropriate input values
  • Each data cell contains a formula (not hardcoded)
  • Each data cell shows a DIFFERENT value
  • Values move in expected directions
  • Base case appears where headers match base assumptions
Formatting
  • Hardcoded inputs are blue (0000FF)
  • Calculated formulas are black (000000)
  • Same-tab links are purple (800080)
  • Cross-tab links are green (008000)
  • All numbers are right-aligned
  • Appropriate number formats applied throughout
  • No cells show error values (#REF!, #DIV/0!, #VALUE!, #NAME?)
Logical Sanity Checks
  • Numbers are reasonable order of magnitude
  • Trends make sense (growth, decline, stabilization as expected)
  • No obviously wrong values (negative where should be positive, impossible percentages, etc.)
  • Key outputs are within reasonable ranges for the type of analysis

COMMON ERRORS TO AVOID

ErrorWhat Goes WrongHow to Fix
Hardcoding calculated valuesModel doesn't update when inputs changeAlways use formulas that reference source cells
Wrong cell references after copyingFormulas point to wrong cellsVerify all links, use appropriate $ anchoring
Circular reference errorsModel can't calculateUse beginning balances for interest-type calcs, break the circle
Sections don't balanceTotals that should match don'tEnsure one item is the plug (calculated as difference)
Negative balances where impossiblePaying/using more than availableUse MAX(0, ...) or MIN functions appropriately
IRR/return errorsWrong signs or incomplete rangesCheck cash flow signs and ensure formula covers all periods
Sensitivity table shows same valueFormula not varying with inputsCheck cell references - need mixed references ($A5, B$4)
Roll-forwards don't tieBeginning ≠ prior endingVerify links between periods
Inconsistent sign conventionsAdditions become subtractions or vice versaFollow template's convention consistently throughout

WORKING WITH THE USER

  • If the template structure is unclear, ask before proceeding
  • If the user's requirements conflict with the template, confirm their preference
  • After completing each major section, offer to show the work or run verification
  • If errors are found during verification, fix them before moving to the next section
  • Show your work - explain key formulas or assumptions when helpful

This skill produces investment banking-quality LBO models by filling templates with correct formulas, proper formatting, and validated calculations. The skill adapts to any template structure while ensuring financial accuracy and professional presentation standards.

© w95, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in 02-finance-accounting/lbo-model of w95/awesome-claude-corporate-skills.

Open the folder on GitHubat commit 78dbc7c

Used in 1 other repository

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in w95/awesome-claude-corporate-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Works with

Questions about Lbo Model

What does Lbo Model do?

This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. Lbo Model is an agent skill from w95/awesome-claude-corporate-skills. This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations.

When should I use Lbo Model?

Lbo Model fits situations like: tasks that involve Excel spreadsheets; tasks that involve Accounting and bookkeeping.

How do I install Lbo Model in Claude Code?

Run `npx skills add w95/awesome-claude-corporate-skills --skill lbo-model -a claude-code`. Or copy the skill folder (02-finance-accounting/lbo-model in w95/awesome-claude-corporate-skills) into .claude/skills/lbo-model in your project. Claude Code loads it when a task matches its description.

How do I install Lbo Model in Codex?

Run `npx skills add w95/awesome-claude-corporate-skills --skill lbo-model -a codex`. Or copy the skill folder (02-finance-accounting/lbo-model in w95/awesome-claude-corporate-skills) into .agents/skills/lbo-model in your project. Codex loads it when a task matches its description.

Can I use Lbo Model in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add w95/awesome-claude-corporate-skills --skill lbo-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lbo-model, .gemini/skills/lbo-model, .github/skills/lbo-model and .opencode/skills/lbo-model in your project.

What does Lbo Model need to run?

Going by SKILL.md and its folder, Lbo Model needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Lbo Model access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Lbo Model safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Lbo Model use?

Lbo Model is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lbo Model use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Lbo Model?

Skills that share tags, products or a category with Lbo Model: Receipts To Expenses (skrun-dev/skrun, 210 stars), Audit Report Checker (nigo81/nigo-skills, 133 stars), CICPA Company Registration Query (nigo81/nigo-skills, 133 stars) and Bank Statement Merge and Reconciliation (nigo81/nigo-skills, 133 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lbo Model?

w95 (a GitHub user) maintains it in w95/awesome-claude-corporate-skills, which has 237 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on February 26, 2026.

Source: w95/awesome-claude-corporate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.