A professional-grade skill for editing, replacing, and redacting PDF content using PyMuPDF to ensure high-fidelity results and preserved text layers.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install edit-pdf-pdf-editing
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 edit-pdf-pdf-editing using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
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What is PDF Editing & Redaction?
The PDF Editing skill provides a robust framework for programmatically manipulating PDF documents using Python and PyMuPDF (fitz). Unlike basic tools that flatten documents or use destructive rasterization, this skill focuses on maintaining the integrity of the PDF text layer. It allows developers to search for specific text coordinates, cover existing data with clean white overlays, and insert new information at precise locations.
By leveraging this Openclaw Skills resource, users can automate document workflows such as form filling, signature placement, and sensitive data masking. The skill emphasizes technical precision, ensuring that edited documents remain searchable and professional, avoiding common pitfalls like messy strikethroughs or suspicious black-box redactions.
PDF Editing & Redaction Use Cases
- Replacing outdated contact information or names in existing PDF documents.
- Filling empty form fields and adding dates or digital signatures programmatically.
- Performing true redaction on sensitive data like Social Security or Student ID numbers to ensure non-recoverability.
- Correcting errors in generated reports by overlaying accurate data at the exact original positions.
- Automating the processing of high-volume PDF batches while preserving the document structure.
How PDF Editing & Redaction Works
- The document is opened using the PyMuPDF (fitz) library to access its internal structure.
- A text extraction pass is performed to identify current content and specific string coordinates using the search function.
- For standard replacements, a white rectangle is drawn over the old text to hide it visually while keeping the layer intact.
- For sensitive data, a redaction annotation is applied and executed, which physically removes the underlying text from the PDF's binary structure.
- New text is inserted at the identified coordinates with matching font sizes and colors.
- The modified document is saved as a new file, ensuring all changes are committed and the text remains extractable.
PDF Editing & Redaction Setup
PyMuPDF is the recommended engine for this skill and comes pre-installed in many environments. You can verify your environment or install it manually using the following commands:
# Verify PyMuPDF installation
python3 -c "import fitz; print('PyMuPDF ready')"
# Manual installation if required
pip install pymupdf
PDF Editing & Redaction Data Schema & Taxonomy
This skill interacts with PDF document structures and organizes its workflow based on coordinate geometry and text mapping.
| Data Component | Description |
|---|---|
| Document Object | The root fitz.open("file.pdf") instance containing all pages and metadata. |
| Rect Object | A tuple or object defining (x0, y0, x1, y1) coordinates for text or shapes. |
| Redaction Annot | A specialized metadata layer used to mark content for physical deletion. |
| Text Layer | The searchable content preserved through direct insert_text methods. |
PDF Editing & Redaction Advanced Features
- True Redaction: Moves beyond visual covering to physically strip bytes from the PDF structure using apply_redactions().
- Coordinate-Match Insertion: Ensures visual consistency by inserting new values at the exact x0/y1 origin of the text being replaced.
- Multi-Agent Support: Can be integrated into automated pipelines where one agent identifies errors and this skill agent performs the fixes.
- Masking Logic: Built-in patterns for partial data masking (e.g., showing only the last four digits of a secure ID).
- Cross-Platform Compatibility: While Python-centric, it provides logic bridges for Node.js environments using pdf-lib.
SKILL.md
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