Does this skill support multi-sheet Excel files?

Yes, the skill can process all sheets in a workbook simultaneously or target specific sheets by name for focused data extraction.

Can it handle very large Excel files?

Yes, it includes a specific implementation for chunking data, allowing it to process files with over a million rows without exhausting system memory.

What libraries are required to run this skill?

The Python implementation requires pandas, openpyxl, and xlrd, while the Node.js version utilizes the xlsx (SheetJS) library.

Does it extract formula results or the formulas themselves?

By using the --evaluate-formulas flag, the skill can use the openpyxl engine to calculate and return the evaluated results of Excel formulas.

Scanner Excel Extraction

Name: Scanner Excel Extraction
Author: takemi-ohama

bytakemi-ohama

Data Science & ML

Extracts, transforms, and structures data from complex Excel files into JSON or CSV formats.

About

The Scanner Excel Extraction skill empowers Claude to efficiently parse multi-sheet Excel workbooks, evaluate embedded formulas, and capture cell formatting. Designed for high-performance data processing, it handles large datasets through memory-efficient chunking and provides structured outputs for seamless integration with APIs or databases. This skill is ideal for developers needing to automate data entry, migrate legacy spreadsheet data, or convert complex workbooks into machine-readable formats like JSON and CSV.

Key Features

Structured JSON and CSV export options
0 GitHub stars
Multi-sheet reading and processing
Formula evaluation and value calculation
Memory-efficient chunking for large files
Cell formatting and metadata extraction

Use Cases

Converting financial spreadsheets into structured JSON for API consumption
Migrating legacy inventory data from Excel to a relational database
Automating the aggregation of monthly sales reports from multiple workbooks

About

Key Features

Structured JSON and CSV export options
0 GitHub stars
Multi-sheet reading and processing
Formula evaluation and value calculation
Memory-efficient chunking for large files
Cell formatting and metadata extraction

Use Cases

Converting financial spreadsheets into structured JSON for API consumption
Migrating legacy inventory data from Excel to a relational database
Automating the aggregation of monthly sales reports from multiple workbooks