Can I use this for professional financial modeling?

Yes, it follows strict industry-standard conventions, including specific color coding for inputs (blue text) and formulas (black text) and standardized currency/multiple formatting.

Can it handle existing Excel templates?

Absolutely; it is designed to study and match existing styles, conventions, and formatting to ensure consistency when updating established files.

How does jelly-xlsx ensure formula accuracy?

It uses a specialized recalculation script via LibreOffice to verify every cell, identifying and reporting errors like #REF! or #DIV/0! before final delivery.

Does it support CSV files?

Yes, the skill is triggered by both Excel (.xlsx, .xlsm) and CSV files for comprehensive data analysis and transformation tasks.

What libraries does this skill use?

It leverages pandas for high-performance data processing and openpyxl for preserving complex formatting and Excel-native formulas.

Jelly XLSX Specialist

Name: Jelly XLSX Specialist
Author: dev-jelly

bydev-jelly

数据科学与机器学习

Automates professional spreadsheet creation, data analysis, and financial modeling with industry-standard formatting and error-free formula calculation.

关于

Jelly-xlsx is a specialized Claude Code skill designed for high-stakes spreadsheet operations, ranging from complex financial modeling to large-scale data analysis. It bridges the gap between Python-based data manipulation and native Excel functionality by enforcing industry-standard color coding, formatting rules, and mandatory formula recalculation using LibreOffice. Whether building dynamic dashboards from scratch or auditing existing templates, this skill ensures zero formula errors and maintains strict documentation standards for all hardcoded assumptions, making it ideal for finance professionals and data analysts.

主要功能

Industry-standard financial modeling with specific color coding for inputs and formulas
Zero-error guarantee for #REF!, #DIV/0!, and #VALUE! errors
0 GitHub stars
Automated formula recalculation and verification using LibreOffice integration
Standardized number formatting for currency, percentages, and valuation multiples
Seamless integration between pandas data analysis and openpyxl formatting

使用场景

Auditing and updating complex legacy Excel templates while preserving existing formatting conventions
Cleaning and analyzing large CSV datasets using pandas and exporting to formatted Excel reports
Building dynamic three-statement financial models with automated scenario analysis

关于

主要功能

Industry-standard financial modeling with specific color coding for inputs and formulas
Zero-error guarantee for #REF!, #DIV/0!, and #VALUE! errors
0 GitHub stars
Automated formula recalculation and verification using LibreOffice integration
Standardized number formatting for currency, percentages, and valuation multiples
Seamless integration between pandas data analysis and openpyxl formatting

使用场景

Auditing and updating complex legacy Excel templates while preserving existing formatting conventions
Cleaning and analyzing large CSV datasets using pandas and exporting to formatted Excel reports
Building dynamic three-statement financial models with automated scenario analysis