A comprehensive command-line tool for parsing Microsoft Word documents and extracting text, tables, and metadata into structured formats.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install word-reader
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install word-reader using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Word Document Reader?
The Word Document Reader is a specialized utility designed to bridge the gap between binary document formats and structured data. It enables users to programmatically access the contents of both modern .docx and legacy .doc files, making it an essential component for automated document processing within Openclaw Skills.
By leveraging the python-docx library, this tool accurately identifies document structures such as headers, footers, and nested tables. It provides a flexible way for developers and researchers to convert unstructured document data into clean Markdown, plain text, or machine-readable JSON, facilitating easier integration with AI models and data pipelines.
Word Document Reader Use Cases
- Automated analysis of project requirements and specifications stored in Word format.
- Extracting structured data from meeting minutes and converting them into project management tools.
- Batch processing large document repositories to create searchable text databases or knowledge bases.
- Converting legacy documentation into Markdown for modern documentation site generation.
How Word Document Reader Works
- The user initiates the tool by providing a file path or a directory path for batch processing.
- The script detects the file extension and utilizes python-docx for modern files or antiword for legacy formats.
- It iterates through the document hierarchy, capturing paragraphs, heading levels (H1-H6), and list items.
- Table structures are parsed cell-by-cell and converted into 2D arrays or Markdown tables.
- Document properties such as author name, creation date, and last modified time are retrieved from the metadata layer.
- The processed content is formatted into the requested output type (JSON, Markdown, or Text) and returned to the user.
Word Document Reader Setup
To get started with this skill for Openclaw Skills, ensure you have Python 3 installed and then follow these steps:
# Install the core Python dependency
pip3 install python-docx
# (Optional) Install antiword for legacy .doc support on Linux
sudo apt-get install antiword -y
# (Optional) Install antiword for legacy .doc support on macOS
brew install antiword
Word Document Reader Data Schema & Taxonomy
The tool organizes document data into a structured schema, especially when using the JSON output format:
| Key | Type | Description |
|---|---|---|
metadata |
object | Contains document properties like title, author, and timestamps |
text |
string | The complete text content extracted from the document |
tables |
array | An array of tables, where each table is a 2D array of strings |
images |
array | Metadata for embedded images, including filename and dimensions |
format |
string | The output format requested (json, text, or markdown) |
Word Document Reader Advanced Features
- Multi-format output support including JSON for data pipelines and Markdown for human-readable notes.
- Batch processing capabilities to handle entire directories of documents in a single command.
- Granular extraction filters to target only specific elements like tables, images, or metadata.
- Automatic style mapping for headers (H1-H6) and paragraph styles to maintain document hierarchy.
- Memory-efficient streaming for processing exceptionally large documents without crashing the environment.
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