Word

When to Use This Skill

• User mentions a .docx or .docm file and wants to read, extract, or inspect its content
• Text extraction: extract text from paragraphs with heading detection
• Table extraction: extract tables as markdown, JSON, or CSV
• Metadata inspection: author, title, creation date, word count, structure
• Image extraction: extract embedded images from the document
• Markdown conversion: convert the full document to Markdown format

> Legacy .doc files: This skill handles .docx and .docm (modern Word formats). For legacy .doc files, the script will suggest converting to .docx first using LibreOffice (libreoffice --headless --convert-to docx file.doc) or an online converter.

Prerequisites

• python-docx — install with: pip install python-docx

Pre-flight check:

python3 -c "import docx; print(docx.__version__)"

Install if missing:

pip install python-docx

Workflow

1. Determine what the user wants (read text, extract tables, inspect metadata, convert to markdown, extract images)
2. Run the appropriate script subcommand
3. Read the output (text, markdown table, JSON, or confirmation) and present it to the user
4. For multi-step tasks, chain subcommands in sequence

All commands use:

python3 scripts/word_ops.py  [options] 

The script path is relative to this skill directory.

Command Reference

Inspect document metadata

python3 scripts/word_ops.py info document.docx

Shows file size, title, author, subject, creation/modification dates, paragraph count, table count, word count, section count, and heading outline.

Extract text

# Extract all text
python3 scripts/word_ops.py text document.docx

# Extract first 50 paragraphs
python3 scripts/word_ops.py text document.docx --limit 50

# Skip empty paragraphs
python3 scripts/word_ops.py text document.docx --skip-empty

Headings are shown with # markers for visual hierarchy.

Extract tables

# Extract all tables as markdown (default)
python3 scripts/word_ops.py tables document.docx

# Extract as JSON
python3 scripts/word_ops.py tables document.docx --format json

# Extract as CSV (one file per table)
python3 scripts/word_ops.py tables document.docx --format csv --output-dir ./tables/

Extract embedded images

# Extract all images to a directory
python3 scripts/word_ops.py extract-images document.docx --output-dir ./images/

Output files are named _image_1.png, _image_2.png, etc.

Convert to Markdown

# Print to stdout
python3 scripts/word_ops.py to-markdown document.docx

# Save to file
python3 scripts/word_ops.py to-markdown document.docx -o document.md

Preserves heading hierarchy, bold/italic formatting, and tables.

Composing Multi-Step Workflows

The commands above are building blocks. Combine them to accomplish complex user requests. Examples:

"What's in this Word document?":

1. info to see page count, title, author, etc.
2. text --limit 30 to read the first 30 paragraphs for a quick overview

"Extract the tables and save as CSV":

1. tables --format csv --output-dir ./tables/ to extract and save

"Convert this docx to markdown and show me":

1. to-markdown to convert and print the full document

"Read this Word doc and summarize it":

1. info to understand the structure
2. text to extract all content
3. Summarize based on the extracted text

Guidelines

• Read before manipulate: always info or text --limit 10 first to understand the document
• Large documents: use --limit to avoid overwhelming output
• Legacy .doc: the script handles .docx only; for .doc files, convert first with LibreOffice
• Tables: first row is treated as the header in markdown/JSON output
• Images: extracted in their original format (PNG, JPEG, etc.)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: jie-meng
• Source: jie-meng/mythril-agent-skills
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.