A high-performance Python library for reading and writing Microsoft Excel spreadsheets with support for complex components and large datasets.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install excelize
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install excelize using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Excelize is a comprehensive Python port of the renowned Go Excelize library, specifically engineered for manipulating Microsoft Excel files including XLAM, XLSM, XLSX, XLTM, and XLTX formats. It provides a robust set of functions that allow developers to build complex spreadsheet automation workflows within Openclaw Skills environments.
This tool stands out for its high compatibility with Microsoft Excel 2007 and later, offering a streaming API that enables efficient processing of massive worksheets without exhausting system resources. Whether you are generating reports from scratch or parsing existing data, this skill ensures data integrity and high performance for professional-grade automation.
To integrate this tool into your environment using Openclaw Skills, ensure you have Python 3.9 or later installed. Install the package via pip:
pip install excelize
Excelize manages data through a structured hierarchy reflecting the Office Open XML standard. The following table outlines the primary data components:
| Component | Description |
|---|---|
| File Handle | The primary object representing the entire Excel workbook. |
| Worksheets | Individual sheets identified by name or index. |
| Cells | Data storage units addressed by coordinates (e.g., A1, B2). |
| Graphics | External objects like images and charts embedded via specific options. |
| Metadata | Document properties and cell styles stored within the XML structure. |
Loading
An interactive AI-powered flashcard review session utilizing the FSRS-4.5 spaced repetition algorithm for peak memory retention.

A technical framework for building a holistic SEO data analysis system to monitor indexing, traffic, keywords, and backlinks.

A powerful cross-chain bridge and DEX aggregation skill for discovering optimal routes, generating quotes, and performing wallet prechecks via the LI.FI protocol.

A comprehensive interface for managing multilingual vocabulary, study lists, and personal language notes across Eudic, Frdic, Dehelper, and Eshelper.

A specialized tool to verify if psychology journals are indexed in SCI or SSCI databases to ensure high academic standards.

A comprehensive toolkit for managing and scaling Whop businesses, from offer optimization to advanced API automation.








































