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Protremix
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xlsx

Create, edit, and validate Excel spreadsheets with formulas, formatting, and recalculation.

Updated Aug 7, 2026
Search Tags:#financial modeling#pandas#openpyxl#spreadsheet#excel#xlsx#formula recalculation
One-click install
npx skills add https://github.com/Protremix/EvolvixOS --skill xlsx-protremix
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/Protremix/EvolvixOS/tree/main/knowledge/experts/office-automation/skills/xlsx
Command: npx skills add https://github.com/Protremix/EvolvixOS --skill xlsx-protremix

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, pandas, defusedxml, lxml, and includes scripts (resource) components.

What problem does it solve? Working with spreadsheet files programmatically often leads to broken formulas, inconsistent formatting, and hardcoded values that make files impossible to maintain. This Skill provides a structured workflow for creating, editing, and analyzing .xlsx, .xlsm, .csv, and .tsv files so deliverables arrive with zero formula errors and professional formatting. ## Core Features & Use Cases - Formula-first spreadsheet generation: Writes native Excel formulas (SUM, AVERAGE, growth rates) instead of hardcoded Python-computed values, keeping workbooks dynamic and recalculable. - Automated recalculation and error detection: The scripts/recalc.py tool uses LibreOffice to recalculate all formulas and reports #REF!, #DIV/0!, #VALUE!, #NAME?, and other errors with exact cell locations. - Financial modeling conventions: Enforces industry-standard color coding (blue inputs, black formulas, green cross-sheet links), number formats ($#,##0, 0.0%, 0.0x), and assumption documentation. - Use Case: A user asks to build a revenue forecast model from a messy CSV export. The Skill cleans the data with pandas, builds the model with openpyxl using cell-referenced assumptions, recalculates via LibreOffice, and fixes any formula errors before delivery. ## Quick Start Ask the assistant to create or edit an Excel file, for example: build a financial model spreadsheet from my sales data with formulas and proper formatting.

Frequently Asked Questions about xlsx

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

FAQPage Schema
How do I create an Excel file with formulas in Python?▼

Use openpyxl to write formula strings like '=SUM(B2:B9)' directly into cells rather than computing values in Python. After saving, run scripts/recalc.py to recalculate all formulas with LibreOffice and verify no errors exist.

Should I use pandas or openpyxl for Excel files?▼

Use pandas for data analysis, bulk operations, and simple exports via read_excel and to_excel. Use openpyxl when you need formulas, cell formatting, styles, or edits to existing workbooks while preserving their structure.

Why do my openpyxl formulas show no calculated values?▼

openpyxl stores formula strings but never computes them, so cells appear empty until opened in Excel. Run scripts/recalc.py, which drives LibreOffice headlessly to recalculate every formula and save the computed values.

How do I find and fix #REF! or #DIV/0! errors in Excel files?▼

Run scripts/recalc.py on the file; it returns JSON listing each error type with exact sheet and cell locations. Fix invalid references for #REF! and guard denominators for #DIV/0!, then recalculate again until the error count is zero.

Does reading Excel with data_only=True cause problems?▼

Loading with data_only=True returns cached values, but saving that workbook permanently replaces all formulas with static values. Only use data_only=True for read-only analysis, never for files you intend to save.

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