Comps analysis

Skill Borjani1577/claude-office-skills/claude-in-excel/comps-analysis

Import Excel and PowerPoint skills into Claude Code to automate spreadsheets and presentations using local filesystem access.

Install

npx -y skills add Borjani1577/claude-office-skills --skill comps-analysis

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What its author says it does

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Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. Perfect for: Public company valuation, benchmarking, IPO pricing, outlier identification, IC presentations, sector overviews Not ideal for: Private companies without public peers, conglomerates, distressed/bankrupt, pre-revenue startups, unique business models

SKILL.md

5.2 KB, as published. Nobody here has run it

Comparable Company Analysis

Preflight: Dependency Check

Before starting, verify required libraries and tools are installed and install any that are missing.

python3 -c "import openpyxl" 2>/dev/null || python3 -m pip install openpyxl
command -v soffice >/dev/null 2>&1 || command -v libreoffice >/dev/null 2>&1 || ls /Applications/LibreOffice.app/Contents/MacOS/soffice >/dev/null 2>&1 || echo "WARNING: LibreOffice not found. Install: brew install --cask libreoffice (macOS) or apt install libreoffice (Linux). Required for scripts/recalc.py."

Important: Do not skip this step — scripts/recalc.py is required to verify quartile statistics and multiple-range sanity checks.

Scripts

scripts/recalc.py — Force formula recalculation via headless LibreOffice. Run after building: python scripts/recalc.py <comps.xlsx>

⚠️ CRITICAL: Data Source Priority (READ FIRST)

FIRST: Check for MCP data sources (S&P Kensho, FactSet, Daloopa)
DO NOT use web search if MCPs available
ONLY if MCPs unavailable: Bloomberg, SEC EDGAR
NEVER use web search as primary data source

Overview

Institutional-grade comps combining operating metrics, valuation multiples, statistical benchmarking.

Reference Material & Contextualization

comps_example.xlsx (bundled in this skill directory) for structural hierarchy understanding
DO use for: structure, rigor level, principles
DO NOT use for: exact reproduction, copying without context
ALWAYS ask: format preference? audience? key question? context?
Adapt for: industry, sector, company familiarity, decision type

⚠️ Formulas Over Hardcodes + Step-by-Step Verification

Office JS: range.formulas, not range.values
Merged cell pitfall: value to top-left first
Step-by-step: structure → raw inputs → operating metrics → valuation multiples → statistics

Section 1: Document Structure & Setup

Header Block (Rows 1-3): Title, Companies list, Date/Units

Visual Convention Standards (OPTIONAL - user prefs override)

Font: Times New Roman 11pt (data), 12pt (headers)
Color Palette: Dark blue #1F4E79/#17365D (headers), Light blue #D9E1F2 (column headers), White (data), Light grey #F2F2F2 (statistics)
Decimal precision: % 1 decimal, multiples 1 decimal, $ no decimals
No borders (clean minimal appearance)
All metrics center-aligned
Uniform column widths + consistent row heights

Section 2: Operating Statistics & Financial Metrics

Core Columns: Company, Revenue, Revenue Growth, Gross Profit, Gross Margin, EBITDA, EBITDA Margin

Optional: FCF, FCF Margin, Net Income, Operating Income, CapEx, Rule of 40, FCF Conversion

Statistics Block: Maximum, 75th Percentile, Median, 25th Percentile, Minimum

Statistics for comparable metrics (ratios, margins, multiples) — NOT size metrics (absolute $)
One blank row between data and statistics — NO "SECTOR STATISTICS" header

Section 3: Valuation Multiples & Investment Metrics

Core: Company, Market Cap, Enterprise Value, EV/Revenue, EV/EBITDA, P/E

Optional: FCF Yield, PEG Ratio, Price/Book, ROE/ROA, CAGR, Asset Turnover, Debt/Equity

Cross-Reference Rule: Multiples MUST reference operating metrics section

Statistics Block: Same structure (Max, 75th, Med, 25th, Min)

Section 4: Notes & Methodology Documentation

Data Sources & Quality, Key Definitions, Valuation Methodology, Analysis Framework

Section 5: Choosing the Right Metrics (Decision Framework)

"Which is undervalued?" → EV/Rev, EV/EBITDA, P/E
"Which is most efficient?" → margins
"Which is growing fastest?" → growth rates
"Which generates most cash?" → FCF metrics

Industry-Specific: SaaS, Manufacturing, Financial Services, Retail

The "5-10 Rule": 5 operating + 5 valuation = 10 total

Section 6: Best Practices & Quality Checks

Cell comments on ALL hard-coded inputs (source OR assumption)
Sanity: Gross > EBITDA > Net margin
Multiple ranges: EV/Rev 0.5-20x, EV/EBITDA 8-25x, P/E 10-50x

Common Mistakes: mixing market cap/EV, inconsistent periods, hardcodes without comments

Section 6 (Advanced): Dynamic Headers, Quartile Analysis, Industry Modifications

Section 7: Workflow & Practical Tips

Set up structure (30min) → 2. Gather data (60-90min) → 3. Build formulas (30min) → 4. Add statistics (15min) → 5. Quality control (30min) → 6. Documentation (15min)