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Docx Toolkit

Name: Docx Toolkit
Availability: InStock
Author: NEU-ZHA

skill-neu-zha-legal-ai-skills-docx-toolkit · by NEU-ZHA

Extract text, tables, and images from .docx and legacy .doc files. Handles large documents, CJK text, and complex table structures. Includes deduplication and filtering for extracted images.

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Install

$ agentstack add skill-neu-zha-legal-ai-skills-docx-toolkit

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

✓ Prompt-injection patterns
✓ Secret / credential exfiltration
✓ Dangerous shell & filesystem operations
✓ Untrusted network calls
✓ Known-malicious package signatures

What it can access

✓ Network access No
✓ Filesystem access No
✓ Shell / process execution No
✓ Environment & secrets No
✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

DOCX Toolkit

A complete toolkit for processing Microsoft Word documents (.docx and legacy .doc formats).

Capabilities

1. Text + Table Extraction (.docx)

python3 {baseDir}/scripts/extract_text.py input.docx output.txt

Extracts all paragraphs and tables with structure preserved. Tables are formatted as pipe-delimited rows for easy parsing.

2. Text Extraction (Legacy .doc)

python3 {baseDir}/scripts/extract_doc_text.py input.doc output.txt

Handles legacy OLE2 .doc format using olefile. Extracts Unicode text from the WordDocument stream.

3. Image Extraction (.docx)

python3 {baseDir}/scripts/extract_images.py input.docx output_dir/

Extracts all embedded images with:

Automatic deduplication (MD5 hash comparison)
Size filtering (skips tiny icons 200MB) may require significant RAM for olefile processing
Image extraction preserves original format (png/jpg/gif/etc.)
Deduplication catches exact duplicates; near-duplicates still pass through
CJK (Chinese/Japanese/Korean) text is fully supported in both extractors

Source & license

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

Author: NEU-ZHA
Source: NEU-ZHA/legal-ai-skills
License: MIT

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

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Versions

v0.1.0 Imported from the upstream source.