Summary
The ocr-document-processor skill extracts text and structured data from scanned images, PDFs, and handwritten documents using optical character recognition (OCR), supporting specialized parsing for receipts and business cards. It serves developers and data processors who need to convert unstructured visual documents into searchable, machine-readable formats like JSON, markdown, or HTML. The skill solves the problem of recovering legible text from low-quality or skewed scans while providing confidence assessments and specialized extraction modes for common document types.
Install to Claude Code
npx -y skills add dkyazzentwatwa/chatgpt-skills --skill ocr-document-processor --agent claude-codeInstalls into .claude/skills of the current project.
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SKILL.mdView on GitHub
OCR Document Processor
Handle OCR-heavy inputs where text must be recovered from images or scanned pages.
Use This For
- OCR on images and scanned PDFs
- Searchable PDF export
- Structured extraction to text, markdown, JSON, or HTML
- Table extraction from scanned material
- Receipt parsing and business card parsing
Workflow
- Decide whether plain OCR, structured extraction, or document-specific parsing is needed.
- Preprocess noisy inputs before extraction when skew, blur, or shadows are present.
- Use
scripts/ocr_processor.pyfor core OCR tasks. - Use the focused helpers when the input is specialized:
scripts/business_card_scanner.pyscripts/receipt_scanner.py
- Return confidence caveats when the source is low quality, rotated, handwritten, or multilingual.
Guardrails
- Prefer explicit language selection when accuracy matters.
- Do not claim fields are exact when OCR confidence is weak.
- Route non-scanned digital PDFs to
document-converter-suiteinstead of OCR by default.
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