{"slug":"k-dense-ai-scanpy","source_name":"k-dense-ai/scanpy","name":"K Dense AI/Scanpy","description":"Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.","version":1,"lift":{"pass_rate_delta_pts":40.91,"pass_rate_pct":77.3,"total_cases":22,"passed_cases":17,"tokens_delta_pct":156.8,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-09T09:46:44.819118+00:00"},"skill_score":0.7727,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":40.91,"with_pass_pct":77.3,"without_pass_pct":36.4,"tokens_delta_pct":156.8,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":20,"verdict":"mixed","never_hurt":false,"completed_at":"2026-08-09T09:46:44.819118+00:00","run_id":"05323123-25e7-44ea-8e44-e71686a100f4","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"BSD-3-Clause","install_count":0,"manifest_hash":"d138621609f27c64a65742f921661b4ffbf3549e088894dfc07fedced15a9ee2","raw_url":"https://app.decimal.ai/s/k-dense-ai-scanpy/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/k-dense-ai-scanpy"}