xlsx

Create, edit, and recalculate Excel spreadsheets with formulas using openpyxl and LibreOffice.

Updated Mar 31, 2026
One-click install
npx skills add https://github.com/SESELOVSKYDarian/Vase --skill xlsx-seselovskydarian
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/SESELOVSKYDarian/Vase/tree/main/.agents/skills/xlsx
Command: npx skills add https://github.com/SESELOVSKYDarian/Vase --skill xlsx-seselovskydarian

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, hardcoded values that cannot update, and Excel errors like #REF! or #DIV/0! that only surface after delivery. This Skill provides a disciplined workflow for creating, editing, and analyzing .xlsx, .xlsm, .csv, and .tsv files so every deliverable arrives with working formulas, professional formatting, and zero formula errors. ## Core Features & Use Cases - Formula-first spreadsheet creation: Builds Excel files where all calculations use native Excel formulas instead of hardcoded Python-computed values, keeping workbooks dynamic and updateable. - Mandatory recalculation and error scanning: Uses scripts/recalc.py with LibreOffice to recalculate all formulas and report every #REF!, #DIV/0!, #VALUE!, #NAME?, and #N/A error with exact cell locations. - Financial modeling conventions: Enforces industry-standard color coding (blue inputs, black formulas, green cross-sheet links), number formatting rules, and documented sources for hardcoded values. - Use Case: A user asks to build a revenue projection model from a messy CSV export. The Skill cleans the data with pandas, constructs the model in openpyxl with assumption cells and formulas, recalculates via LibreOffice, fixes any reported errors, and delivers a polished .xlsx. ## Quick Start Use the xlsx skill to turn the attached sales-export.csv into a formatted Excel workbook with a summary sheet that totals revenue by region using live formulas.

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, then save the workbook. Because openpyxl stores formulas without computing them, run scripts/recalc.py afterward so LibreOffice calculates and caches the values.

Should I use pandas or openpyxl for Excel files?

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

Why do my openpyxl formulas show no values after saving?

openpyxl writes formulas as strings but never evaluates them, so cells appear empty until opened in Excel. Run scripts/recalc.py, which drives LibreOffice headlessly to recalculate all formulas and store the computed values in the file.

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

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

Can openpyxl read calculated values from an existing workbook?

Yes, load the file with data_only=True to read cached calculated values instead of formula strings. Never save a workbook opened this way, because doing so permanently replaces all formulas with their static values.