What problem does it solve?
Provides a governed, production-grade workflow for creating, editing, cleaning, and converting spreadsheet files so the primary deliverable is always a valid, recalculable Excel workbook with zero formula errors and preserved templates.
Core Features & Use Cases
- Format-preserving edits: Modify existing .xlsx/.xlsm while exactly matching templates and style conventions.
- Data cleaning & restructuring: Repair malformed CSV/TSV/tabular data, normalize headers, remove junk rows, and convert into structured worksheets.
- Formula-first modeling: Add Excel formulas (not hardcoded values), build dynamic models, and enforce industry number formatting and color conventions for financial models.
- Recalculation & validation: Recalculate formulas using the provided LibreOffice-based recalc.py and scan for common Excel errors (#REF!, #DIV/0!, #NAME?, etc.) until clean.
- Integration patterns: Use pandas for data analysis and openpyxl for precise formatting and formula insertion; ideal for use cases like invoice rollups, financial model updates, chart generation, and format conversions.
Quick Start
Use the xlsx skill to read 'dirty.csv', clean and restructure the data into a new workbook, add dynamic formulas, run the recalculation script, and deliver 'cleaned_output.xlsx'.