Extract text, tables, and structured data from PDFs, including scanned OCR documents.
npx skills add https://github.com/open-neko/openneko --skill pdf-open-neko
Please help me install this Agent Skill. Skill: pdf Source: https://github.com/open-neko/openneko/tree/main/packages/llm/assets/builtin-skills/pdf Command: npx skills add https://github.com/open-neko/openneko --skill pdf-open-neko
Manually processing PDFs—extracting text or tables, merging and splitting files, filling out forms, or digitizing scanned documents—is slow, repetitive, and prone to human error. This Skill automates these tedious tasks to save you time and reduce mistakes.
Use this skill to extract all text and table data from the attached 'q3_financial_report.pdf' and save the extracted tables to a CSV file named 'report_data.csv'.
High-intent search queries and answers about installing and using this skill.
To extract text and tables from a scanned PDF, OCR renders the image-based pages into readable text and structured data. This process automatically digitizes scanned documents for use in spreadsheets or databases without manual entry.
Automating form filling for non-fillable scanned PDFs involves detecting field locations visually and entering data programmatically. This technique applies to both native fillable and scanned forms, adding validation to ensure correct data placement.
Merging multiple PDF files while extracting invoice data involves pulling line-item data from each document and compiling the totals into a CSV. This automated workflow also combines the individual PDFs into a single archived file.
Yes, Python libraries including pdfplumber and pypdf can be used for PDF table extraction. These dependencies parse binary PDF streams and extract embedded content, enabling automated retrieval of structured tabular data from documents.
Automated PDF text extraction works for both native text documents and image-based scanned files. By combining direct stream parsing with optical character recognition, the system pulls structured text from various document types.
Limitations of OCR for scanned document table extraction include potential misreads of complex layouts or low-quality images. While optical character recognition digitizes scanned pages, structured data accuracy depends heavily on the original document's clarity.
niduran-orionParse and extract text and tables from PDF documents using Python libraries.
thecloudtipsExtract structured financial data from invoice PDFs, JPGs, PNGs, and TIFFs.
claude-office-skillsExtract text from images and scanned documents using PaddleOCR.
SALDAPALExtract text, tables, and metadata from PDF documents using Python libraries.
