Extract text, tables, and metadata from PDFs using Python libraries.
npx skills add https://github.com/Haseeb-Arshad/TaskHive --skill pdf-haseeb-arshad
Please help me install this Agent Skill. Skill: pdf Source: https://github.com/Haseeb-Arshad/TaskHive/tree/main/.claude/skills/pdf Command: npx skills add https://github.com/Haseeb-Arshad/TaskHive --skill pdf-haseeb-arshad
Reading and manipulating PDFs is often tedious, error-prone, and manual. This skill provides a programmable toolkit to read, extract text and tables, merge and split PDFs, apply OCR to scanned documents, and handle forms and annotations to automate common PDF workflows.
Ask the AI to automate a workflow that reads a sample PDF, extracts its text and tables, and saves the results to a CSV.
High-intent search queries and answers about installing and using this skill.
To extract text and tables from PDF files, this skill uses pypdf and pdfplumber to parse content. It automates reading diverse documents like invoices and multi-page reports, turning them into structured, actionable data for administrative workflows.
Yes, you can apply OCR to scanned PDFs to make them searchable and indexable. The skill uses pdf2image and Pillow to render scanned documents, extracting readable text from images to automate archival digitization workflows.
Yes, this approach handles filling out both fillable and non-fillable PDF forms. It programmatically manages form filling, annotations, and simple edits to automate administrative workflows like contract review and invoice processing.
The best way to merge, split, and watermark PDF documents in Python is using a programmatic toolkit. This skill applies pypdf to manipulate pages, enabling you to merge, split, rotate, and annotate PDFs reliably for reporting and archival.
Yes, you need Python libraries like pypdf, pdfplumber, pdf2image, and Pillow installed to automate PDF processing. These dependencies are essential to parse text, render scanned documents, and manipulate pages reliably.
PDF text extraction fails on scanned documents because they contain images rather than embedded text. You can fix this by applying OCR using pdf2image and Pillow to render the pages, making the content searchable and indexable.
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