Full-featured computational pathology toolkit. Use for advanced WSI analysis including multiplexed immunofluorescence (CODEX, Vectra), nucleus segmentation, tissue graph construction, and ML model training on pathology data. Supports 160+ slide formats. For simple tile extraction from H&E slides, histolab may be simpler.
8.3
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Machine Learning
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Excellent computational pathology skill with comprehensive coverage of advanced WSI analysis workflows. The description clearly articulates when to use this vs. simpler alternatives (histolab), and SKILL.md provides strong overview of 6 major capability areas with explicit pointers to detailed reference files. Structure is exemplary: concise main file with organized references for image loading, preprocessing, graphs, ML, multiparametric imaging, and data management. Task knowledge is extensive, covering complex workflows from CODEX/Vectra analysis to nucleus segmentation and graph neural networks. The skill addresses genuinely complex computational pathology tasks (160+ slide formats, HoVer-Net training, spatial proteomics) that would require substantial token expenditure and specialized domain knowledge for a CLI agent to handle independently. Quick start examples demonstrate practical usage patterns. Minor improvement possible in description brevity, but overall this is a high-quality, well-structured skill for advanced pathology computational workflows.
K-Dense-AI
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