batch-ocr-processing

uatch ocr processing

7,385 stars

Best use case

batch-ocr-processing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

uatch ocr processing

Teams using batch-ocr-processing should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/batch-ocr-processing/SKILL.md --create-dirs "https://raw.githubusercontent.com/kreuzberg-dev/kreuzberg/main/.ai-rulez/domains/ocr-integration/skills/batch-ocr-processing/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/batch-ocr-processing/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How batch-ocr-processing Compares

Feature / Agent	batch-ocr-processing	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

uatch ocr processing

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

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SKILL.md Source

Process multiple images concurrently

1. Create OcrProcessor (shared)
2. Estimate optimal worker count
3. Create queue of images
4. Spawn worker tasks
5. Each worker:
   a. Process image from queue
   b. Handle errors independently
   c. Return results
6. Aggregate results maintaining order
7. Return batch results

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