Skill

pdf-ocr

Extract text from PDF files using Apple Vision OCR, optimized for Apple Silicon

Install

npx claudepluginhub varunr89/claude-marketplace --plugin ocr-toolkit

Tool Access

This skill uses the workspace's default tool permissions.

Preview

Converts PDF pages to images using PyMuPDF, then runs Apple Vision OCR on each page in parallel. Produces Markdown, plain text, or JSONL output.

SKILL.md

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Last CommitMar 1, 2026

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PDF OCR

Converts PDF pages to images using PyMuPDF, then runs Apple Vision OCR on each page in parallel. Produces Markdown, plain text, or JSONL output.

When to use

Use this skill when the user wants to extract text from a PDF file -- especially scanned PDFs, image-based PDFs, or PDFs where copy-paste produces garbled text.

Usage

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/pdf_ocr.py <input.pdf> \ [-o output_file] \ [-f markdown|text|jsonl] \ [--dpi 200] \ [--workers N] \ [--languages en-US] \ [--fast] \ [--keep-images] [--images-dir <dir>] \ [--stdout]

Key arguments

Argument

Default

Description

pdf (positional)

required

Input PDF file path

-o, --output

<pdf_name>.md

Output file path

-f, --format

markdown

Output format: markdown, text, or jsonl

--dpi

200

Resolution for rendering PDF pages (higher = better quality, slower)

--workers

CPU count

Number of parallel OCR workers

--languages

en-US

Comma-separated recognition languages

--fast

false

Use faster, less accurate recognition

--keep-images

false

Keep the extracted page images after OCR

--images-dir

temp dir

Directory to save page images (requires --keep-images)

--stdout

false

Print extracted text to stdout instead of writing to file

Pipeline

PDF pages are rendered to PNG images at the specified DPI using PyMuPDF (fitz)

Apple Vision OCR runs in parallel across pages using ThreadPoolExecutor

Results are assembled in page order and written to the chosen output format

Output formats

markdown -- Each page becomes a ## Page N section with the OCR text

text -- Plain text with === Page N === separators

jsonl -- One JSON object per line with page, text, and backend fields

Dependencies

PyMuPDF (pip install pymupdf) -- PDF to image conversion

macOS + PyObjC (pip install pyobjc-core pyobjc-framework-Vision pyobjc-framework-Cocoa) -- Vision OCR

PDF OCR

Converts PDF pages to images using PyMuPDF, then runs Apple Vision OCR on each page in parallel. Produces Markdown, plain text, or JSONL output.

When to use

Use this skill when the user wants to extract text from a PDF file -- especially scanned PDFs, image-based PDFs, or PDFs where copy-paste produces garbled text.

Usage

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/pdf_ocr.py <input.pdf> \
  [-o output_file] \
  [-f markdown|text|jsonl] \
  [--dpi 200] \
  [--workers N] \
  [--languages en-US] \
  [--fast] \
  [--keep-images] [--images-dir <dir>] \
  [--stdout]

Key arguments

Argument	Default	Description
`pdf` (positional)	required	Input PDF file path
`-o, --output`	`<pdf_name>.md`	Output file path
`-f, --format`	`markdown`	Output format: markdown, text, or jsonl
`--dpi`	200	Resolution for rendering PDF pages (higher = better quality, slower)
`--workers`	CPU count	Number of parallel OCR workers
`--languages`	`en-US`	Comma-separated recognition languages
`--fast`	false	Use faster, less accurate recognition
`--keep-images`	false	Keep the extracted page images after OCR
`--images-dir`	temp dir	Directory to save page images (requires --keep-images)
`--stdout`	false	Print extracted text to stdout instead of writing to file

Pipeline

PDF pages are rendered to PNG images at the specified DPI using PyMuPDF (fitz)
Apple Vision OCR runs in parallel across pages using ThreadPoolExecutor
Results are assembled in page order and written to the chosen output format

Output formats

markdown -- Each page becomes a ## Page N section with the OCR text
text -- Plain text with === Page N === separators
jsonl -- One JSON object per line with page, text, and backend fields

Dependencies

PyMuPDF (pip install pymupdf) -- PDF to image conversion
macOS + PyObjC (pip install pyobjc-core pyobjc-framework-Vision pyobjc-framework-Cocoa) -- Vision OCR