Is it suitable for professional financial modeling?

Yes, it follows industry standards for color coding (blue for inputs, black for formulas) and specific number formatting for currency and multiples.

Does it support complex Excel formulas?

Absolutely. It prioritizes native Excel formulas over hardcoded values to ensure spreadsheets remain dynamic and updateable.

Can this skill handle existing Excel templates?

Yes, the xlsx skill is designed to study and exactly match existing formats, styles, and conventions when modifying files to preserve template integrity.

How does it ensure formula accuracy?

It uses a specialized recalculation script that leverages LibreOffice to evaluate formulas and detect errors like #REF!, #DIV/0!, or #VALUE!.

Spreadsheet Automation & Financial Modeling

Name: Spreadsheet Automation & Financial Modeling
Author: partme-ai

bypartme-ai

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Data Science & ML

Automates the creation, editing, and analysis of professional spreadsheets with advanced formula support and industry-standard financial modeling.

About

The xlsx skill empowers Claude to perform complex spreadsheet operations ranging from large-scale data analysis to the construction of institutional-grade financial models. By integrating pandas for data manipulation and openpyxl for precision formatting, it ensures spreadsheets are dynamic, well-structured, and error-free. The skill uniquely includes a dedicated formula recalculation and verification workflow using LibreOffice, ensuring that all generated models are fully functional and follow professional conventions such as input color-coding and source documentation.

Key Features

37 GitHub stars
Comprehensive data analysis and visualization using the integrated pandas library
Professional financial modeling standards including industry-standard color coding
Precise template preservation and formatting style matching for existing files
Automated formula recalculation and error auditing via LibreOffice scripts
Dynamic spreadsheet creation with native Excel formulas and zero-error validation

Use Cases

Building automated financial models with dynamic growth projections and assumption cells
Analyzing large CSV or Excel datasets to generate summarized, formatted reports
Modifying existing corporate spreadsheet templates while maintaining formula integrity and styles

About

Key Features

37 GitHub stars
Comprehensive data analysis and visualization using the integrated pandas library
Professional financial modeling standards including industry-standard color coding
Precise template preservation and formatting style matching for existing files
Automated formula recalculation and error auditing via LibreOffice scripts
Dynamic spreadsheet creation with native Excel formulas and zero-error validation

Use Cases

Building automated financial models with dynamic growth projections and assumption cells
Analyzing large CSV or Excel datasets to generate summarized, formatted reports
Modifying existing corporate spreadsheet templates while maintaining formula integrity and styles