analyzing-financial-statements

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

153 stars

Best use case

analyzing-financial-statements is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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

Teams using analyzing-financial-statements should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/analyzing-financial-statements/SKILL.md --create-dirs "https://raw.githubusercontent.com/Microck/ordinary-claude-skills/main/skills_all/analyzing-financial-statements/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/analyzing-financial-statements/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How analyzing-financial-statements Compares

Feature / Agentanalyzing-financial-statementsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

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