xlsx

Convert CSV, TSV, and Excel files into clean .xlsx spreadsheets.

Updated Feb 12, 2026
One-click install
npx skills add https://github.com/omardelarosa/claude-configs --skill xlsx-omardelarosa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/omardelarosa/claude-configs/tree/main/skills/xlsx
Command: npx skills add https://github.com/omardelarosa/claude-configs --skill xlsx-omardelarosa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, defusedxml, lxml, and includes scripts (resource) components.

What problem does it solve?

Manual cleanup of messy data across CSV/TSV formats into consistent spreadsheet formats is time-consuming and error-prone. This Skill automates the cleaning, restructuring, and conversion of tabular data into polished spreadsheets ready for analysis or reporting.

Core Features & Use Cases

  • Open and normalize data: read .xlsx, .xlsm, .csv, or .tsv inputs and standardize headers, data types, and row structure.
  • Data cleaning and formatting: remove junk rows, fix misaligned headers, and apply common formatting rules to improve readability.
  • Formula and transformation support: apply deterministic formulas and transformations to generate derived metrics.
  • Format conversion: convert between tabular formats (CSV/TSV to Excel and vice versa) while preserving data integrity.
  • Use Case: take a messy CSV of sales data, clean headers, compute totals, and export a ready-to-share .xlsx workbook.

Quick Start

Load your input CSV, clean the data (fix headers, remove junk rows), apply a few formulas, and save the result as a new .xlsx.

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 convert it to an Excel file?

To clean messy CSV data and convert it to an Excel file, this Skill reads .csv inputs, removes junk rows, fixes misaligned headers, applies formatting rules, and exports a structured .xlsx workbook.

What is the best way to reformat spreadsheet headers and apply formulas to tabular data?

The best way to reformat spreadsheet headers and apply formulas to tabular data is using this Skill to standardize data types, apply deterministic transformations, and compute derived metrics across .xlsx and .tsv inputs.

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

Yes, this tool supports converting between TSV, CSV, and XLSX formats by reading various tabular inputs and writing clean .xlsx outputs while preserving data integrity during the format conversion.

Can I use openpyxl to process .xlsm files and output polished spreadsheets?

Yes, you can process .xlsm files and output polished spreadsheets using this Skill, which leverages the openpyxl dependency to read .xlsm inputs, apply data cleaning, and generate final spreadsheet files.

How do I remove junk rows and fix misaligned headers in a messy spreadsheet?

To remove junk rows and fix misaligned headers in a messy spreadsheet, this Skill normalizes row structures and standardizes headers during the data cleaning process to improve overall readability.

What are the limitations of using Python for spreadsheet data transformation tasks?

Limitations of using Python for spreadsheet data transformation tasks include relying on libraries like openpyxl, defusedxml, and lxml to process data, which requires valid .xlsx, .xlsm, .csv, or .tsv inputs to function correctly.