High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
8.3
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Excellent genomic analysis skill with comprehensive coverage and outstanding structure. The SKILL.md provides clear, actionable descriptions of six specialized genomic modules (overlap detection, coverage tracks, tokenization, reference sequences, fragment processing, scoring) with immediate 'when to use' guidance and quick examples. Task knowledge is exceptional - practical workflows, both Python and CLI usage patterns, integration guidance, and well-organized reference documentation across multiple specialized files. Structure is exemplary: concise overview with clear module indexing, avoiding clutter by deferring details to appropriate reference files. Novelty is strong - genomic interval analysis with ML tokenization, IGD indexing, and high-performance Rust operations would require substantial effort and tokens for a CLI agent to replicate. Minor opportunity: could slightly expand the description to mention single-cell genomics capabilities for better discoverability.
K-Dense-AI
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