An AI-powered PDF assistant for extracting content, generating smart summaries, and converting documents into clean Markdown format.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pdf-reader-cp3d
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 pdf-reader-cp3d 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 PDF Reader Assistant?
The pdf-reader-cp3d is a versatile tool designed for Openclaw Skills that transforms static PDF documents into dynamic, machine-readable data. It excels at parsing complex layouts, including academic papers, ebooks, and business reports, to provide structured text, tables, and intelligent summaries.
This skill enables AI agents to interactively read and understand document context, allowing for advanced Q&A and seamless data synthesis. By leveraging modern parsing libraries, it ensures that heading structures and formatting are preserved when moving data between formats, making it an essential component for any automated research or documentation workflow within the Openclaw Skills ecosystem.
PDF Reader Assistant Use Cases
- Researching academic papers to extract core contributions and methodologies.
- Converting technical manuals or ebooks into Markdown for structured documentation.
- Generating concise outlines and one-sentence summaries from lengthy corporate reports.
- Extracting structured data from tables within PDF forms for analysis.
- Performing context-aware Q&A to retrieve specific insights from deeply nested document chapters.
How PDF Reader Assistant Works
- The user triggers the skill by uploading a PDF file or providing a local file path.
- The system identifies the document type and metadata, such as page count and file size.
- Content is extracted using specialized libraries that recognize headings, lists, code blocks, and tables.
- The extracted content is transformed into a target format, such as Markdown, to preserve semantic structure.
- The AI agent processes the structured text to generate summaries or answer natural language questions about the document.
- All metadata and processing results are logged into the Openclaw Skills workspace for persistent history.
PDF Reader Assistant Setup
To integrate this capability into your environment, ensure you have the necessary Python dependencies installed for local processing. Use the following commands to set up the environment for Openclaw Skills:
# Install core PDF processing libraries
pip install PyMuPDF pdfplumber pymupdf4llm
For cloud-based extraction, ensure your API keys for services like Adobe PDF Extract or Google Document AI are configured in your environment variables.
PDF Reader Assistant Data Schema & Taxonomy
The skill organizes its output and tracking data within the Openclaw Skills workspace directory. It uses a structured JSON format to maintain a history of all processed files:
| Attribute | Type | Description |
|---|---|---|
| filename | String | Name of the processed PDF file |
| processed_date | String | The ISO date when the file was parsed |
| pages | Number | Total number of pages in the document |
| output_md | String | Local path to the generated Markdown file |
| summary | String | The intelligent summary generated by the AI |
PDF Reader Assistant Advanced Features
- Intelligent Markdown conversion that preserves hierarchical heading levels and list structures.
- Specialized table extraction that converts complex PDF grids into clean Markdown tables.
- High-fidelity content Q&A allowing users to query specific chapters or conclusions.
- Support for multiple output formats including plain text, HTML, and structured JSON.
- Batch processing support to handle large directories of documents efficiently within Openclaw Skills.
SKILL.md
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