analyzing-financial-statements

Pass

This skill calculates key financial ratios and metrics from financial statement data for investment analysis

@anthropics
MIT3/2/2026
56out of 100
(0)
33.9k
9
19

Install Skill

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Install globally (user-level):

npx skillhub install anthropics/claude-cookbooks/analyzing-financial-statements

Install in current project:

npx skillhub install anthropics/claude-cookbooks/analyzing-financial-statements --project

Suggested path: ~/.claude/skills/analyzing-financial-statements/

AI Review

Instruction Quality55
Description Precision25
Usefulness79
Technical Soundness65

Scored 56 because the two Python scripts are solid (safe division, type hints, benchmarks) but SKILL.md provides zero CLI commands for invoking them. Description is a single informational sentence with no trigger phrases — a significant miss for a skill from Anthropics. Description fix + CLI examples would push this to ~72.

SKILL.md Content

---
name: analyzing-financial-statements
description: This skill calculates key financial ratios and metrics from financial statement data for investment analysis
---

# 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