Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.
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Excellent skill providing comprehensive access to the CELLxGENE Census single-cell atlas. The description clearly identifies when to use this skill (population-scale queries, reference comparisons) versus alternatives (scanpy for own data). SKILL.md is exceptionally well-structured with progressive complexity: core patterns, exploration, small/medium queries, large-scale out-of-core processing, ML integration, and scanpy workflows. Task knowledge is outstanding with complete working examples, best practices (always filter is_primary_data, specify versions, estimate query size), and clear explanations of when to use each approach. The skill provides significant value by abstracting the complexity of querying 61M+ cells with proper resource management, chunked processing, and integration patterns that would require substantial token usage for an LLM to construct from scratch. Reference files are appropriately separated for schema details and additional patterns. Minor improvement possible in making the description even more concise, but overall this is a highly effective skill for bioinformatics workflows.
K-Dense-AI
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