xlsx

Create, edit, and analyze .xlsx, .xlsm, .csv, and .tsv spreadsheets with pandas and openpyxl.

Updated May 7, 2026
One-click install
npx skills add https://github.com/MOODMNKY-LLC/mnky-atlas --skill xlsx-moodmnky-llc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/MOODMNKY-LLC/mnky-atlas/tree/main/skills/xlsx
Command: npx skills add https://github.com/MOODMNKY-LLC/mnky-atlas --skill xlsx-moodmnky-llc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the tedious manual effort of working with spreadsheet files, handling everything from cleaning messy tabular data to building complex financial models without repetitive, error-prone manual work.

Core Features & Use Cases

  • End-to-End Spreadsheet Support: Create new spreadsheets from scratch or external data, edit existing .xlsx/.xlsm/.csv/.tsv files, and analyze tabular data for insights.
  • Dynamic Formula & Formatting Management: Build maintainable Excel formulas instead of hardcoded values, enforce professional formatting standards, and automatically recalculate and verify formulas to eliminate errors.
  • Use Case: You have a messy sales CSV with misaligned headers, junk rows, and missing calculated columns. Use this Skill to clean the data, add dynamic growth rate formulas, apply consistent professional formatting, and export a polished .xlsx file ready for stakeholder review.

Quick Start

Use the xlsx skill to clean the messy sales data in 'q3_sales.csv' and export it as a formatted .xlsx file with calculated monthly growth columns.

Frequently Asked Questions about xlsx

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

FAQPage Schema
How do I clean messy CSV data and export a formatted Excel file?

You can clean messy CSV data by automating the removal of junk rows and fixing misaligned headers, then exporting the results as a polished .xlsx file. This workflow applies consistent professional formatting and adds calculated columns without manual effort.

Can I create dynamic Excel formulas instead of hardcoded values in a spreadsheet?

Yes, you can create dynamic Excel formulas instead of hardcoded values by leveraging openpyxl for formula operations. A provided recalc script verifies formula accuracy and eliminates Excel errors, ensuring your spreadsheets remain maintainable and correct.

Does this tool support converting between CSV, TSV, and XLSX spreadsheet formats?

Yes, it supports converting between .xlsx, .xlsm, .csv, and .tsv spreadsheet formats. You can create new spreadsheets from external data, edit existing files, and analyze tabular data across all these supported formats seamlessly.

What is the best way to automate adding calculated columns to a sales spreadsheet?

The best way to automate adding calculated columns to a sales spreadsheet is by using pandas for data manipulation. This allows you to dynamically add calculated growth rate formulas and apply professional formatting directly to your tabular data.

Do I need pandas and openpyxl to build financial models from tabular data?

Yes, you need pandas and openpyxl to build financial models from tabular data. Pandas handles the underlying data manipulation, while openpyxl manages dynamic formula creation and professional formatting operations within the generated spreadsheet files.

Why do my Excel formulas show errors after editing an XLSX file programmatically?

Excel formulas may show errors after editing an XLSX file programmatically if they are not recalculated. Using a provided recalc script verifies formula accuracy and eliminates these Excel errors, ensuring your dynamic calculated columns function correctly.