Professional financial modeling toolkit for Claude Code with auto-invoked Skills and Excel MCP integration. Build DCF models, LBO analysis, variance reports, and pivot tables using natural language.
Installation
npx claude-plugins install @jeremylongshore/claude-code-plugins-plus/excel-analyst-pro
Contents
Folders: skills, slash-commands
Files: DEMO_VIDEO_SCRIPT.md, GITHUB_DEPLOYMENT.md, LICENSE, PRODUCTION_SUMMARY.md, README.md
Documentation
Professional financial modeling toolkit for Claude Code with auto-invoked Skills and Excel MCP integration.
Build DCF models, LBO analysis, variance reports, and pivot tables using natural language. No formulas to remember, no manual Excel work—just describe what you need.
🚀 Features
Auto-Invoked Skills
- DCF Modeler: Build discounted cash flow valuation models with projections, WACC, and sensitivity analysis
- LBO Modeler: Create leveraged buyout models with debt schedules, cash flow waterfalls, and IRR calculations
- Variance Analyzer: Automate budget vs actual analysis with flagging, commentary, and executive summaries
- Pivot Wizard: Generate pivot tables and charts from raw data using natural language
Key Benefits
- ✅ Natural Language: Just describe what you want—no Excel formulas to remember
- ✅ Auto-Invoked: Claude automatically detects when to use each Skill
- ✅ Investment Banking Grade: Follows IB best practices and standards
- ✅ Local Processing: No cloud upload—all Excel work happens locally
- ✅ Token Efficient: Skills load only when relevant (50% cheaper than MCP alone)
- ✅ Team Standardization: Everyone uses the same best practices
📦 Installation
Prerequisites
- Claude Code 1.0+
- Node.js 18+
Quick Install
/plugin install excel-analyst-pro@claude-code-plugins
This will automatically:
- Install the plugin
- Configure @negokaz/excel-mcp-server
- Load all 4 Skills into Claude Code
- Add slash commands
🎯 Usage
DCF Valuation Model
Just ask in natural language:
You: "Create a DCF model for Tesla"
Claude: I'll build a DCF valuation model for Tesla. Let me gather some inputs.
What base year revenue should we use for Tesla?
(For reference, Tesla's 2023 revenue was approximately $96.8B)
You: $96.8 billion
Claude: Great! What revenue growth rates should we assume for Years 1-5?
You: 25%, 20%, 15%, 12%, 10%
Claude: [Builds complete DCF model with 4 sheets]
✅ DCF Model Complete!
📊 Valuation Results:
- Enterprise Value: $847.3 billion
- Implied equity value per share: $243
📁 Model saved to: Tesla_DCF_Model.xlsx
That’s it! No Excel formulas, no manual work.
LBO Analysis
You: "Build an LBO model for a $50M EBITDA software company"
Claude: I'll create an LBO model. What entry multiple should we assume?
(Software companies typically trade at 10-15x EBITDA)
You: 12x
Claude: [Builds complete LBO model with 6 sheets]
✅ LBO Model Complete!
📊 Base Case Returns (5-year hold, 12x exit):
- Exit Equity Value: $1,124M
- Money-on-Money: 4.2x
- IRR: 34.2%
📁 Model saved to: Software_LBO_Model.xlsx
Variance Analysis
You: "Analyze Q1 budget vs actual"
Claude: [Analyzes data and generates report]
✅ Variance Analysis Complete!
🔴 CRITICAL VARIANCES:
- EBITDA: $270K vs $450K (-40.0%) - $180K under
- Operating Expenses: $840K vs $750K (+12.0%) - $90K over
📁 Report saved to: Q1_2025_Variance_Analysis.xlsx
Pivot Tables
You: "Show sales by region and product category"
Claude: [Creates pivot table and visualization]
✅ Pivot Table Created!
Top Insights:
1. West region leads with $1.45M (30.3% of total)
2. Electronics is #1 category at $1.70M (35.6%)
3. Northeast + Electronics = $400K (highest cell)
Visualization: Added column chart comparing regions
FREE Financial Data Sources: No Bloomberg Required
Get company financials, market data, and economic indicators for your models - all free, no $24K/year Bloomberg subscription.
Quick Comparison
| Data Type | Paid Source | FREE Source |
|---|---|---|
| Company Financials | Bloomberg ($24K/year) | SEC EDGAR: $0 |
| Stock Prices | Capital IQ ($12K/year) | Yahoo Finance: $0 |
| Market Data | FactSet ($12K/year) | Alpha Vantage: $0 |
| Macro Indicators | Refinitiv ($12K/year) | FRED: $0 |
| Company News | S&P CapitalIQ ($12K/year) | Google News: $0 |
Annual Savings: $25K-74K for professional-grade model inputs.
Why Free Data Works for Financial Modeling
For DCF Models:
- Revenue/EBITDA: SEC 10-K/10-Q filings (FREE)
- Stock prices: Yahoo Finance (FREE)
- Risk-free rate: FRED (Federal Reserve, FREE)
- Beta: Calculated from Yahoo Finance data (FREE)
For LBO Models:
- Entry valuation: SEC filings + Yahoo Finance (FREE)
- Debt terms: Company 10-K disclosure (FREE)
- Comparable multiples: Public comps from Yahoo Finance (FREE)
- Exit assumptions: Historical trading multiples (FREE)
For Variance Analysis:
- Budget data: Your internal files (already have)
- Actual results: Your accounting system (already have)
- Industry benchmarks: BEA.gov, Census.gov (FREE)
15-minute delayed data is perfectly fine for financial modeling (not day trading).
Free Data Source Catalog
1. SEC EDGAR (Best for Fundamentals)
What: Official company filings (10-K, 10-Q, 8-K)
**Use
Included Skills
This plugin includes 4 skill definitions:
excel-dcf-modeler
|
View skill definition
Excel DCF Modeler
Overview
Creates professional DCF valuation models following investment banking standards with WACC calculations and sensitivity analysis.
Prerequisites
- Excel or compatible spreadsheet software
- Historical financial data for target company
- Industry comparables for WACC estimation
Instructions
- Create assumptions sheet with revenue growth, margins, WACC, and terminal growth rate
- Build free cash flow projections (5-year forecast)
- Calculate terminal value using Gordon Growth Model
- Discount cash flows and terminal value to present value
- Sum to get enterprise value, subtract net debt for equity value
- Add sensitivity tables for key assumptions
Output
- Complete 4-sheet DCF model with assumptions, projections, valuation, and sensitivity
- Enterprise value and equity value per share
- Sensitivity analysis on WACC and terminal growth rate
Error Handling
| Error | Cause | Solution |
|---|---|---|
| #DIV/0! in terminal value | WACC equals terminal growth | Terminal growth must be less than WACC |
| Negative FCF | High CapEx or WC needs | Review assumptions, may need different model |
| Unrealistic EV | Extreme growth assumptions | Benchmark against industry comparables |
Examples
Example: Value a SaaS Company Request: “Create a DCF model for a $50M ARR SaaS company growing 30%” Result: 4-sheet model with 5-year projections, 12% WACC, 3% terminal growth, sensitivity tables
**Example: M&A Valuation
excel-lbo-modeler
|
View skill definition
Excel LBO Modeler
Overview
Creates leveraged buyout models with debt structuring, amortization schedules, and sponsor returns analysis for private equity transactions.
Prerequisites
- Excel or compatible spreadsheet software
- Target company financial data
- Debt term sheet parameters
- Entry/exit multiple assumptions
Instructions
- Set up transaction structure (purchase price, debt/equity split)
- Build debt schedules for each tranche (senior, mezzanine, etc.)
- Create operating projections with debt service
- Calculate cash flow available for debt paydown
- Model exit scenarios and calculate IRR/MOIC
Output
- Complete LBO model with sources & uses, debt schedules, and returns
- IRR and MOIC at various exit multiples and years
- Sensitivity tables for entry/exit multiple and leverage
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Negative cash flow | Debt service exceeds EBITDA | Reduce leverage or restructure debt terms |
| IRR #NUM! | No valid solution | Check exit value exceeds equity contribution |
| Circular reference | Cash sweep tied to interest | Enable iterative calculation |
Examples
Example: Mid-Market LBO Request: “Build an LBO model for a $100M EBITDA company at 8x entry” Result: 60% senior / 40% equity structure, 5-year model, IRR analysis at 7x-10x exits
Example: Add-On Acquisition Request: “Model a bolt-on acquisition with synergies” Result: Integrated model with synergy phase-in and ac
excel-pivot-wizard
|
View skill definition
Excel Pivot Wizard
Overview
Creates advanced pivot tables with calculated fields, slicers, and dynamic dashboards for data analysis and reporting.
Prerequisites
- Excel or compatible spreadsheet software
- Tabular data with headers
- Clear understanding of analysis dimensions and measures
Instructions
- Verify source data is in tabular format with headers
- Create pivot table from data range
- Configure rows, columns, values, and filters
- Add calculated fields for custom metrics
- Insert slicers for interactive filtering
- Format and style for presentation
Output
- Configured pivot table with appropriate aggregations
- Calculated fields for derived metrics
- Interactive slicers for filtering
- Dashboard-ready formatting
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Field not found | Changed source data | Refresh data connection |
| Calculated field error | Invalid formula | Check field names match exactly |
| Slicer not updating | Disconnected report | Reconnect slicer to pivot |
Examples
Example: Sales Dashboard Request: “Create a pivot summarizing sales by region and product” Result: Pivot with region rows, product columns, revenue values, and date slicer
Example: Financial Analysis Request: “Build a pivot showing monthly trends by cost center” Result: Time-series pivot with calculated YoY growth fields
Resources
- Microsoft Pivot Table Guide
- `{baseDir}/refe
excel-variance-analyzer
|
View skill definition
Excel Variance Analyzer
Overview
Performs comprehensive budget vs actual variance analysis with automated drill-down, root cause identification, and executive reporting.
Prerequisites
- Excel or compatible spreadsheet software
- Budget data by period and category
- Actual results for comparison
- Cost center or department structure
Instructions
- Import budget and actual data into comparison template
- Calculate absolute and percentage variances
- Apply materiality thresholds for flagging
- Create drill-down by category, period, or cost center
- Generate variance waterfall chart for executive reporting
Output
- Variance summary with favorable/unfavorable indicators
- Materiality-filtered exception report
- Waterfall chart showing budget-to-actual bridge
- Drill-down by category or cost center
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Missing periods | Data gaps | Fill with zeros or interpolate |
| Percentage calc error | Zero budget | Use IF to handle div/0 |
| Misaligned categories | Changed chart of accounts | Create mapping table |
Examples
Example: Monthly P&L Variance Request: “Analyze why we missed budget by $500K this month” Result: Variance waterfall showing revenue shortfall offset by OPEX savings
Example: Department Budget Review Request: “Which departments are over budget YTD?” Result: Ranked list by variance magnitude with drill-down to line items
Resources
- [FP&A Best Practices](