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analyzing-financial-statements

analyzing-financial-statements

github.com/anthropicsData & databases53.9k348 installsUpdated 4d ago
Repository

About analyzing-financial-statements

A financial analysis skill for calculating and interpreting company ratios from financial statements. It serves analysts assessing performance, with optional benchmarks, period trends, and an Excel report.

Key features

  1. 01Profitability and liquidity ratios
  2. 02Leverage and efficiency ratios
  3. 03Valuation and per-share metrics
  4. 04Ratio interpretations and benchmarks
  5. 05Multi-period trend analysis
  6. 06Formatted Excel reports

Use cases

  1. 01Assess company profitability and liquidity
  2. 02Compare ratios with industry benchmarks
  3. 03Review financial trends across periods

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/anthropics/claude-cookbooks --skill analyzing-financial-statements

After installing, type/analyzing-financial-statementsin Claude Code to confirm it loaded.

Bundled filesinterpret_ratios.pycalculate_ratios.py

Details

From the project README

Financial Ratio Calculator Skill

This skill provides comprehensive financial ratio analysis for evaluating company performance, profitability, liquidity, and valuation.

Capabilities

Calculate and interpret:

  • Profitability Ratios: ROE, ROA, Gross Margin, Operating Margin, Net Margin
  • Liquidity Ratios: Current Ratio, Quick Ratio, Cash Ratio
  • Leverage Ratios: Debt-to-Equity, Interest Coverage, Debt Service Coverage
  • Efficiency Ratios: Asset Turnover, Inventory Turnover, Receivables Turnover
  • Valuation Ratios: P/E, P/B, P/S, EV/EBITDA, PEG
  • Per-Share Metrics: EPS, Book Value per Share, Dividend per Share

How to Use

  1. Input Data: Provide financial statement data (income statement, balance sheet, cash flow)
  2. Select Ratios: Specify which ratios to calculate or use "all" for comprehensive analysis
  3. Interpretation: The skill will calculate ratios and provide industry-standard interpretations

Input Format

Financial data can be provided as:

  • CSV with financial line items
  • JSON with structured financial statements
  • Text description of key financial figures
  • Excel files with financial statements

Output Format

Results include:

  • Calculated ratios with values
  • Industry benchmark comparisons (when available)
  • Trend analysis (if multiple periods provided)
  • Interpretation and insights
  • Excel report with formatted results

Example Usage

"Calculate key financial ratios for this company based on the attached financial statements"

"What's the P/E ratio if the stock price is $50 and annual earnings are $2.50 per share?"

"Analyze the liquidity position using the balance sheet data"

Scripts

  • calculate_ratios.py: Main calculation engine for all financial ratios
  • interpret_ratios.py: Provides interpretation and benchmarking

Best Practices

  1. Always validate data completeness before calculations
  2. Handle missing values appropriately (use industry averages or exclude)
  3. Consider industry context when interpreting ratios
  4. Include period comparisons for trend analysis
  5. Flag unusual or concerning ratios

Limitations

  • Requires accurate financial data
  • Industry benchmarks are general guidelines
  • Some ratios may not apply to all industries
  • Historical data doesn't guarantee future performance

Comments

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