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histolab

8.7

by davila7

87Favorites
336Upvotes
0Downvotes

Digital pathology image processing toolkit for whole slide images (WSI). Use this skill when working with histopathology slides, processing H&E or IHC stained tissue images, extracting tiles from gigapixel pathology images, detecting tissue regions, segmenting tissue masks, or preparing datasets for computational pathology deep learning pipelines. Applies to WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.

digital pathology

8.7

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0

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Data & Analytics

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Quick Review

Exceptional skill documentation for digital pathology image processing. The description clearly articulates when to use the skill (WSI processing, H&E/IHC staining, tile extraction, tissue segmentation). SKILL.md provides comprehensive task knowledge with working code examples for all core capabilities, three distinct tile extraction strategies with clear use-case guidance, and complete end-to-end workflows. The structure is exemplary: a concise but thorough main document with well-organized sections, supported by five detailed reference files for deep-dive topics. This prevents clutter while maintaining completeness. The skill addresses a genuinely complex domain (gigapixel medical images, multiple extraction strategies, sophisticated tissue detection) that would require significant token investment for a CLI agent to handle independently. Minor room for improvement in the description's specificity about computational cost savings, but overall this is a highly polished, production-ready skill that meaningfully enhances agent capabilities in computational pathology.

LLM Signals

Description coverage9
Task knowledge10
Structure10
Novelty8

GitHub Signals

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Last commit 0 days ago

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davila7

davila7

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