A comprehensive toolset for programmatic creation, reading, and manipulation of Microsoft Word documents within Openclaw Skills environments.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install docx-skill
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 docx-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The DOCX skill provides a robust API for handling Microsoft Word files, utilizing the power of the docx-js library and direct XML manipulation. As a key component of the Openclaw Skills ecosystem, it allows developers to build sophisticated document workflows including business report generation, invoice creation, and resume formatting. By treating .docx files as structured archives, this skill offers deep control over styles, headers, and metadata, ensuring professional-grade output for any automated workflow.
To install the necessary components for this skill, run the following commands in your terminal:
# Core document creation library
npm install -g docx
# Text extraction and conversion
brew install pandoc
# Validation and Python-based editing
pip install python-docx
Optional dependencies for extended functionality:
# For DOCX to PDF conversion
brew install --cask libreoffice
# For image asset optimization
brew install imagemagick
The DOCX skill organizes document data using a hierarchical metadata taxonomy. Below is a summary of how information is structured:
| Component | Organization Method | Metadata Scope |
|---|---|---|
| Sections | Logical page groupings | Margins, headers, footers, and page sizing |
| Paragraphs | Sequential text blocks | Alignment, spacing, and heading levels |
| Text Runs | Inline style segments | Fonts, colors, weight, and character sizing |
| Tables | Grid-based layouts | Cell borders, shading, and column widths |
| Media | Embedded binary objects | Transformation dimensions and alt-text descriptions |
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