xlsx

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

Updated Apr 17, 2026
One-click install
npx skills add https://github.com/Syedyasir001/RVULibPass --skill xlsx-syedyasir001
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/Syedyasir001/RVULibPass/tree/main/.agent/skills/library/xlsx
Command: npx skills add https://github.com/Syedyasir001/RVULibPass --skill xlsx-syedyasir001

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 produces broken formulas, hardcoded values, and inconsistent formatting. This Skill provides a complete workflow for creating, editing, and analyzing .xlsx, .xlsm, .csv, and .tsv files while guaranteeing zero formula errors and professional financial-model formatting standards. ## Core Features & Use Cases - Formula-first spreadsheet generation: Builds Excel files with live formulas (SUM, growth rates, ratios) instead of hardcoded Python-calculated values, keeping workbooks dynamic and updateable. - Automated recalculation and error detection: The scripts/recalc.py utility uses LibreOffice headless to recalculate all formulas and returns JSON reports locating every #REF!, #DIV/0!, #VALUE!, and #N/A error by cell. - Financial modeling conventions: Enforces industry-standard color coding (blue inputs, black formulas, green cross-sheet links), number formatting (parenthesized negatives, 0.0% percentages, 0.0x multiples), and source documentation 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, and fixes any reported errors before delivery. ## Quick Start Use the xlsx skill to create a formatted financial model from my sales data CSV with formulas for totals and growth rates, then verify it has no formula errors.

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. Formulas are stored but not evaluated, so run scripts/recalc.py afterward to compute values 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, multiple sheets, or edits to existing workbooks that must preserve structure.

Why do openpyxl formulas show no calculated values?▼

openpyxl stores formulas as strings without evaluating them, so cells appear empty when read with data_only=True. Recalculate the file with LibreOffice using scripts/recalc.py to populate computed values before reading results.

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

Run python scripts/recalc.py on the workbook. It recalculates all formulas with LibreOffice, scans every cell, and returns JSON listing each error type with counts and exact cell locations like Sheet1!B5.

Does reading Excel with data_only=True lose formulas?▼

Yes, if you load a workbook with data_only=True and then save it, all formulas are permanently replaced by their cached values. Only use data_only=True for read-only inspection, never for files you intend to save.