What problem does it solve? Spreadsheet tasks often fail silently: formulas written by openpyxl have no cached values, unsupported functions turn into #NAME? errors, and re-saving a workbook can destroy external links. This Skill provides a disciplined workflow for producing spreadsheet files that actually recalculate correctly and follow professional conventions. ## Core Features & Use Cases - Create and edit spreadsheets: Use openpyxl for formulas and formatting, pandas for bulk data in and out, and markitdown for quick sheet previews across .xlsx, .xlsm, .xltx, .csv, and .tsv files. - Mandatory formula recalculation: Run scripts/recalc.py to recalculate every formula via LibreOffice, returning a JSON report of error cells (#VALUE!, #REF!, #NAME?, and more) so no file ships with broken formulas. - Financial modeling conventions: Apply standard color coding (blue inputs, black formulas, green cross-sheet links), number formats, and assumption documentation for professional models. - Use Case: A user asks to build a revenue forecast workbook. The Skill writes SUMIFS and INDEX/MATCH formulas, recalculates the file, fixes any reported errors, and delivers a workbook whose formulas evaluate cleanly. ## Quick Start Use the xlsx skill to create a sales summary spreadsheet from my data with formulas and formatting, then recalculate it to verify there are no errors.