Agent skill
Analyzing Financial Statements
This skill calculates key financial ratios and metrics from financial statement data for investment analysis
Install this agent skill to your Project
npx add-skill https://github.com/auldsyababua/instructor-workflow/tree/main/reference/claude-cookbooks/skills/custom_skills/analyzing-financial-statements
SKILL.md
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
- Input Data: Provide financial statement data (income statement, balance sheet, cash flow)
- Select Ratios: Specify which ratios to calculate or use "all" for comprehensive analysis
- 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 ratiosinterpret_ratios.py: Provides interpretation and benchmarking
Best Practices
- Always validate data completeness before calculations
- Handle missing values appropriately (use industry averages or exclude)
- Consider industry context when interpreting ratios
- Include period comparisons for trend analysis
- 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
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