Extracting PDF Text for LLMs
0This skill provides tools and guidance for extracting text from PDFs in formats suitable for language model consumption. It is designed for developers and data scientists working with PDFs.
000Updated 3w ago
Text Extraction
Quick InstallView Source
$ npx skills add https://github.com/letta-ai/skills --skill extracting-pdf-textOverview
About This Skill
The PDF text extraction skill enables developers and data scientists to extract readable text from PDF documents in formats suitable for language model consumption. Located in the tools/pdf category of the Letta skills repository, it provides practical guidance and tools for handling PDF processing workflows. The skill addresses the common challenge of preparing PDF content for AI agents and LLMs by offering extraction methods that preserve document structure while removing formatting noise. This skill integrates with Letta Code and Claude Code frameworks through the skills system, allowing agents to dynamically load PDF processing capabilities on demand.
How to Use
Install via npm using the command `$ npx skills add https://github.com/letta-ai/skills --skill extracting-pdf-text`.
Use Cases
Extract simple text from PDF documents using PyMuPDF.
Retrieve tabular data from PDFs with pdfplumber.
Process scanned or image-based PDFs using OCR.
Implement a complete RAG pipeline using marker-pdf.
Tags
Setup & Installation
Quick Install
Terminal
$ npx skills add https://github.com/letta-ai/skills --skill extracting-pdf-textAlternative Install (Git Clone)
git clone https://github.com/letta-ai/skillsRequirements
- Claude Code or compatible AI agent
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
📝
No Examples Available
Check the GitHub repository or documentation for usage examples.
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