Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.
8.6
Rating
0
Installs
Machine Learning
Category
Exceptional computational pathology skill with comprehensive coverage of whole-slide imaging workflows. The description clearly articulates when to use the skill (histopathology slides, H&E staining, multiplex immunofluorescence, spatial proteomics) with specific technologies and formats mentioned. The structure is exemplary: SKILL.md provides a concise overview with six well-organized capability areas, each delegating detailed documentation to appropriate reference files, avoiding clutter while maintaining completeness. Task knowledge is outstanding with concrete code examples, three common workflow templates, and systematic references to detailed documentation. The skill addresses a genuinely complex domain where manual CLI work would be extremely token-intensive due to diverse file formats (160+), specialized preprocessing pipelines, graph construction, and integration of multiple ML models. Minor limitation: while highly specialized and valuable for computational pathology, the novelty score reflects that some components (image loading, preprocessing) follow established patterns, though the domain integration and multiparametric capabilities are distinctive. Overall, this is a well-crafted skill that would significantly reduce token costs for pathology analysis tasks.
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