comps-analysis

What it does

The skill teaches Claude to construct a comprehensive comparable company analysis that combines operating metrics, valuation multiples, and statistical benchmarking, producing a structured Excel/spreadsheet for peer comparison.

How it works

• It emphasizes starting from a clear structure and inputting data first, then building transparent formulas. It uses a header setup that includes an analysis title and a list of companies with tickers, plus a period and unit note.
• Operating statistics are organized with core columns: Company, Revenue, Revenue Growth, Gross Profit, Gross Margin, EBITDA, EBITDA Margin, plus optional additions like Free Cash Flow, FCF Margin, Net Income, Operating Income, CapEx, Rule of 40, and FCF Conversion. The skill prescribes formulas for core margins and notes that statistics should be calculated for comparable metrics (e.g., Revenue Growth %, Gross Margin %, EBITDA Margin %, EPS, EV/Revenue, EV/EBITDA, P/E, Dividend Yield %, Beta).
• Valuation multiples section requires Core Valuation Columns: Company, Market Cap, Enterprise Value, EV/Revenue, EV/EBITDA, P/E Ratio, with optional metrics like FCF Yield, PEG Ratio, Price/Book, ROE/ROA, CAGR, Asset Turnover, Debt/Equity. It enforces that EV/Revenue and EV/EBITDA reference operating metrics from the operating section (CRITICAL) and that statistics blocks mirror the structure of the operating section.
• Notes & Methodology Documentation specify data sources, period definitions, and how metrics are calculated, plus the framework for interpretation and investment thesis.
• Choosing metrics and best practices sections guide metric selection, sanity checks, and common mistakes to avoid, including ensuring proper references, avoiding mixing market cap with enterprise value, and maintaining a lean set of metrics (5 operating metrics and 5 valuation metrics).
• The workflow section outlines a step-by-step process: set up structure, gather data via specified data source tools, build formulas progressively, add statistics, perform quality control, and document sources and methodologies. It also provides practical tips for templates, outlier highlighting, linking sources, versioning, and collaboration.

When to use it

Use when you need an institutional-grade, peer-based comparison of operating performance and valuation to support M&A evaluation, investment decision, sector benchmarking, or performance reviews. Trigger considerations include audience (investment committee, board, quick reference, detailed memo) and the context (M&A evaluation, investment decision, sector benchmarking, performance review).

What it can touch

• Data collection references include: get_financial_statements(symbol, 'all', 'annual', 5), get_financial_ratios(symbol), get_growth_metrics(symbol), get_company_overview, and get_historical_valuation(symbol).
• The process specifies inputting raw numbers in blue, applying formulas, and linking to sources and SEC data when available.

Caveats

• License: Apache-2.0 (Derived from anthropics/financial-services-plugins). Modified for langalpha.
• It instructs using specific data sources and maintaining consistent units and periods (e.g., LTM vs quarterly) and to avoid duplicating raw data in multipliers.
• It emphasizes a lean metric set (5 operating metrics and 5 valuation metrics) to avoid noise, and requires quartile-based statistics without sector-statistics headers.