name: comps-analysis description: 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
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)
Section 8: Example Template Layout (Simple ASCII art grid)
Section 9: Industry-Specific Additions (Optional)
SaaS, Financial Services, E-commerce, Healthcare, Manufacturing
Section 10: Red Flags & Warning Signs
Data quality, valuation, comparability issues
Section 11: Formulas Reference Guide
Statistical + Financial + Cross-Sheet + Formatting formulas