Extract text, tables, images, and form data from PDFs using Python.
npx skills add https://github.com/YHWriteCode/EconRAGent --skill pdf-yhwritecode
Please help me install this Agent Skill. Skill: pdf Source: https://github.com/YHWriteCode/EconRAGent/tree/main/skills/pdf Command: npx skills add https://github.com/YHWriteCode/EconRAGent --skill pdf-yhwritecode
Automates the repetitive and error-prone work of extracting content from PDFs and filling or annotating PDF forms so teams can convert documents into structured, actionable data without manual copy‑paste.
Extract all text, tables, and images from the attached file invoice-q3.pdf and produce a CSV of extracted tables plus a plain-text transcription.
High-intent search queries and answers about installing and using this skill.
To extract tables and text from scanned PDFs, this Skill uses pdfplumber and pdf2image with OCR fallbacks. It captures plain text, table data, and images from both digital and scanned documents, converting them into structured formats like CSV files for programmatic processing.
Yes, you can fill non-fillable PDF forms programmatically by adding coordinate-based annotations. The Skill detects fillable fields and extracts metadata, or applies coordinate-based overlays for scanned forms, enabling automated form completion without manual editing across finance and legal workflows.
Yes, pdfplumber works alongside pypdf and Pillow for comprehensive document manipulation. Together they handle merging, splitting, rotating, watermarking, and encrypting PDFs, while pdfplumber specifically manages advanced table extraction and coordinate-based form annotations.
The best way to batch process PDF extraction for archival workflows is using Python scripts with pypdf and pdfplumber. This automates repetitive extraction tasks across multiple documents, transforming unstructured PDF content into actionable plain text, structured table data, and extracted images.
Text extraction fails on some PDF documents when they contain scanned images instead of embedded digital text. This limitation requires OCR fallbacks using pdf2image to convert document pages to images, enabling the extraction of text from scanned administrative, legal, and archival documents.
ShunmeiChoExtract text, tables, and form data from PDFs using Python libraries.
ygfuyfffdf-maxExtract text, tables, and metadata from PDFs using Python scripts.
markoinlaExtract text, tables, and metadata from PDFs and fill forms.
lucasromanhExtract text, tables, and metadata from PDFs using Python libraries.
