xlsx

Clean, format, and compute formulas in spreadsheet files.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/9999-12-31/Dr.Claw --skill xlsx-9999-12-31
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/9999-12-31/Dr.Claw/tree/main/src/qwenpaw/agents/skills/xlsx-en
Command: npx skills add https://github.com/9999-12-31/Dr.Claw --skill xlsx-9999-12-31

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill automates the tedious, error-prone tasks involved in handling spreadsheet data across formats. It supports opening, reading, editing, formatting, cleaning messy data, applying formulas, and producing a polished final spreadsheet file.

Core Features & Use Cases

  • Open, read, edit, format, validate, and convert between .xlsx, .xlsm, .csv, and .tsv
  • Create new spreadsheets from scratch or from existing data sources
  • Clean and restructure messy tabular data (headers, malformed rows) and apply common formulas for reporting
  • Use cases: transform a messy CSV into a structured Excel workbook with computed fields and consistent formatting

Quick Start

Provide the spreadsheet file and I will clean, format, and compute formulas to produce a polished final workbook.

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 into a formatted Excel workbook?

To clean messy CSV data, you can automate the restructuring of malformed rows and headers, then apply formulas to compute fields, ultimately converting the CSV into a structured, formatted .xlsx workbook.

What is the best way to automate applying formulas and formatting to spreadsheet data?

The best way to automate applying formulas and formatting to spreadsheet data is by using Python-based tooling to process .xlsx and .xlsm files, which guarantees deterministic results and a polished final workbook.

Does openpyxl support converting TSV files into structured xlsx workbooks?

Yes, openpyxl supports reading and converting .tsv files by parsing the tabular data, cleaning the input, and exporting a structured .xlsx workbook with consistent formatting and computed fields.

Can I use Python to clean malformed rows and headers in xlsx and xlsm files?

Yes, you can use Python to clean malformed rows and headers in .xlsx and .xlsm files by automating data validation, restructuring tabular data, and applying deterministic formatting rules across the spreadsheet.

How do I convert a spreadsheet with tabular data into a formatted Excel file with computed fields?

You can convert tabular data into a formatted Excel file by automating the data cleaning process, applying formula-based computations for new fields, and exporting a polished .xlsx workbook with deterministic results.

What are the limitations of using Python for spreadsheet data conversion and cleaning?

Limitations of using Python for spreadsheet data conversion include relying on deterministic processing logic rather than dynamic spreadsheet applications, which may limit complex real-time formula recalculation in the final .xlsx output.