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finance-skills

Compute financial ratios, DCF valuations, budget variances, and rolling forecasts from JSON data.

1|Updated Mar 18, 2026
Search Tags:#python#forecasting#valuation#dcf#financial-analysis#ratio-analysis#budget-variance
One-click install
npx skills add https://github.com/xxih/ai-harness-zh --skill finance-skills-xxih
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: finance-skills
Source: https://github.com/xxih/ai-harness-zh/tree/main/references/translations/alirezarezvani-claude-skills/finance
Command: npx skills add https://github.com/xxih/ai-harness-zh --skill finance-skills-xxih

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Automates and standardizes manual financial analysis workflows so analysts and decision makers can reliably compute ratios, valuations, budget variances, and rolling forecasts from source financial data without ad hoc spreadsheets or inconsistent calculations.

Core Features & Use Cases

  • Ratio Analysis: compute profitability, liquidity, leverage, efficiency, and valuation ratios with built-in explanations and benchmarks.
  • DCF & Valuation: perform discounted cash flow valuation with WACC, terminal value options, and sensitivity analysis.
  • Budget & Forecasting: analyze budget variances and build driver-based rolling forecasts for scenario planning.
  • Use Case: CFOs or FP&A teams can run the included scripts on monthly financial JSON exports to produce repeatable metrics and valuation outputs for board reports.

Quick Start

Use the finance-skills to analyze local financial_data.json and produce ratios, a DCF valuation, a budget variance analysis, and a rolling forecast in human-readable or JSON output.

Frequently Asked Questions about finance-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute financial ratios from raw financial statements using Python?▼

You can compute financial ratios from raw statements by processing local JSON-formatted financial data with Python standard library scripts. The scripts calculate profitability, liquidity, leverage, and efficiency ratios, producing JSON or human-readable outputs with built-in explanations and benchmarks.

What is the best way to perform DCF valuation with WACC and terminal value options?▼

Discounted cash flow valuation is performed by running Python scripts on local financial JSON inputs. The process applies WACC, terminal value options, and sensitivity analysis to generate standardized DCF valuation outputs without relying on ad hoc spreadsheets.

How do I analyze budget variances and build rolling forecasts for scenario planning?▼

Budget variance analysis and rolling forecasts are generated by feeding budget data into local Python scripts. The scripts analyze variances and build driver-based short- to medium-term rolling forecasts to support scenario planning for FP&A teams.

Can I run financial analysis scripts offline without network access?▼

Yes, financial analysis scripts enforce non-networked execution and operate entirely offline. They process local JSON-formatted financial data using only the Python standard library, ensuring reliable computation without external API dependencies or internet connectivity.

Do I need external Python packages to compute financial valuations and forecasts?▼

No external Python packages are required because the scripts run on the Python standard library alone. This dependency-free approach ensures consistent calculation of valuations, ratios, and forecasts directly from your local JSON data exports.

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