xlsx

Process spreadsheet data and deliver formatted Excel workbooks.

1|1|Updated Jun 4, 2024
One-click install
npx skills add https://github.com/dhar174/tiny_village --skill xlsx-dhar174
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/dhar174/tiny_village/tree/main/.codex/xlsx
Command: npx skills add https://github.com/dhar174/tiny_village --skill xlsx-dhar174

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates repetitive spreadsheet tasks, including opening, reading, editing, formatting, computing formulas, and converting between tabular formats, to produce polished Excel workbooks with minimal manual effort.

Core Features & Use Cases

  • Automate common spreadsheet operations: read, update, apply formulas, format cells, and convert between .xlsx, .xlsm, .csv, and .tsv.
  • Clean, restructure, and standardize messy tabular data, align headers, and fix malformed rows for reliable analysis.
  • Output ready-to-share spreadsheets for reporting, data analysis, or archival records, with consistent styling and validation.

Quick Start

Convert the supplied dataset into a formatted Excel workbook with required formulas and formatting.

Frequently Asked Questions about xlsx

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

FAQPage Schema
How do I automate Excel spreadsheet data processing and formatting?

Automate Excel spreadsheet data processing by reading, modifying, and formatting .xlsx, .xlsm, .csv, and .tsv files to output a polished, ready-to-share workbook. The process relies on pandas and openpyxl to handle computations and ensure zero formula errors.

Can I convert CSV or TSV files into a formatted Excel workbook with formulas?

Yes, you can convert CSV or TSV files into a formatted Excel workbook. The automation reads tabular inputs, applies required formulas, standardizes headers, fixes malformed rows, and outputs a final .xlsx file ready for distribution.

What's the best way to clean and restructure messy tabular data for reliable analysis?

The best way to clean messy tabular data is to automate the restructuring process, aligning headers and fixing malformed rows. This standardizes the dataset within the .xlsx, .csv, or .tsv formats, resulting in reliable data for analysis.

Does this spreadsheet automation approach work with .xlsm macro-enabled files?

Yes, this spreadsheet automation approach works with .xlsm macro-enabled files. It handles inputs in .xlsx, .xlsm, .csv, and .tsv formats, performing read, modify, compute, and formatting operations to produce a final .xlsx output.

How do I ensure zero formula errors when automating Excel workbook generation?

Ensure zero formula errors during Excel workbook generation by using built-in validation and error handling. The process computes formulas using pandas and openpyxl, validating the data to guarantee the final .xlsx file is error-free.

Why does my spreadsheet data export have misaligned headers and malformed rows?

Misaligned headers and malformed rows in a spreadsheet data export occur when raw tabular data lacks standardization. Automating the data cleaning process restructures the file, aligns headers, and fixes rows to produce a consistent .xlsx output.