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Data Analysis / AGENT SKILL
ocr-document-processor
0
Extract text, tables, and structured information from scans, images, and scanned PDFs.
Extract text and structure from scans, images, and scanned PDFs. Use for OCR, searchable PDFs, table extraction, receipt parsing, and business card parsing.
Understand the trade-offs.
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Original instructions from the publisher’s SKILL.md
# 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 1. Decide whether plain OCR, structured extraction, or document-specific parsing is needed. 2. Preprocess noisy inputs before extraction when skew, blur, or shadows are present. 3. Use `scripts/ocr_processor.py` for core OCR tasks. 4. Use the focused helpers when the input is specialized: - `scripts/business_card_scanner.py` - `scripts/receipt_scanner.py` 5. 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-suite` instead of OCR by default.