xlsx

Automates editing, cleaning, formatting and converting spreadsheet files using Python libraries like openPandas and openpyxl.

1|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/xiaoshuangLi/aibo --skill xlsx-xiaoshuangli
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/xiaoshuangLi/aibo/tree/main/skills/xlsx
Command: npx skills add https://github.com/xiaoshuangLi/aibo --skill xlsx-xiaoshuangli

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the tedious tasks of editing, cleaning, formatting, and converting spreadsheets by enabling automated, output-ready results from inputs like .xlsx, .xlsm, .csv, or .tsv.

Core Features & Use Cases

  • Open, read, edit, or fix spreadsheet files and create new spreadsheets from data sources.
  • Clean and restructure messy tabular data and convert between tabular formats (xlsx, csv, tsv).
  • Deliver a final spreadsheet file as the task output, suitable for downstream workflows or reporting.

Quick Start

Convert the provided input CSV to a clean, ready-to-use XLSX.

Frequently Asked Questions about xlsx

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

FAQPage Schema
How do I automate spreadsheet cleanup and convert CSV to XLSX?

You can automate spreadsheet cleanup and convert CSV to XLSX by applying Python libraries like pandas and openpyxl to read, clean inconsistent headers, and write output files while preserving tabular structure.

What is the best way to apply formulas and add columns to an existing XLSX file?

The best way to apply formulas and add columns to an XLSX file is using openpyxl to read the spreadsheet, programmatically insert new columns with formula logic, and export the final formatted file.

Can I convert between tabular formats like CSV, TSV, and XLSX automatically?

Yes, you can convert between tabular formats like CSV, TSV, and XLSX automatically by using pandas to read the source file and export the transformed data into your desired output format.

Does this approach work for cleaning messy headers and restructuring spreadsheet data?

Yes, this approach works for cleaning messy headers and restructuring spreadsheet data by leveraging pandas to normalize column names, fix inconsistencies, and reorganize rows for a final deliverable.

What are the limitations of using pandas and openpyxl for spreadsheet formatting?

Limitations of using pandas and openpyxl include potential loss of complex visual formatting like charts or pivot tables, as these libraries primarily focus on cell-level data and basic formula transformations rather than advanced visual elements.