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cellxgene-census

Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.

69

Quality

83%

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SKILL.md
Quality
Evals
Security

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, highly actionable body with concrete code and clearly signaled references, weakened mainly by redundancy between the inline overview/use-cases/best-practices and the bundled reference files. Adding an estimate-then-load checkpoint is a genuine strength; trimming restated material would lift conciseness.

Suggestions

Remove the 'When to Use This Skill' bullet list and the Census-definition prose in Overview — both restate the frontmatter description; keep only the cell/dataset scale stats that add new information.

De-duplicate the inline 'Key Concepts and Best Practices' and 'Available Metadata Fields' sections against references/common_patterns.md and references/census_schema.md, replacing the bulk with pointers and retaining only one signature example per concept.

For Use Case 3 and 4, either show complete executable snippets (imports + the scanpy call) or label them as illustrative and link to the fuller pattern in references/core_workflow_patterns.md.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete code, but the Overview re-explains what the Census is and the 'When to Use This Skill' section restates triggers already in the description, and inline best-practices/use-cases overlap the reference files — these could be trimmed.

3 / 5

Actionability

Provides copy-paste-ready executable code for opening, querying, presence matrices, and a TileDB-SOMA-ML dataloader, with only minor gaps (e.g., Use Case 3 leaves '# Training logic' as a placeholder and Use Case 4 calls scanpy without imports).

4 / 5

Workflow Clarity

Sequenced guidance is present — the 'Two-Step Workflow: Explore Then Query' and an explicit 'Estimate Query Size Before Loading' checkpoint (>100k cells triggers out-of-core) — with a Troubleshooting section for recovery; minor validation gaps remain rather than full validate-fix-retry loops.

4 / 5

Progressive Disclosure

SKILL.md is an overview pointing to three real, one-level-deep references each with a 'When to read' cue; structure is good, though inline metadata-field and best-practice content overlaps the reference files, keeping it just short of a clean split.

4 / 5

Total

15

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20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: third-person voice, comprehensive concrete actions, explicit 'Use when' trigger guidance, and clear disambiguation from neighboring tools. Every dimension lands at the top anchor with no padding.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — 'cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons' — giving comprehensive coverage rather than vague language.

5 / 5

Completeness

Explicitly answers both 'what' ('Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data') and 'when' ('Use when you need population-scale cell metadata, gene expression slices...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Covers natural domain terms and synonyms users would say ('single-cell', 'spatial transcriptomics', 'gene expression', 'embeddings', 'organisms, tissues, diseases, assays, and cell types') plus a disambiguating pointer to scanpy/anndata/scvi-tools for local data.

5 / 5

Distinctiveness Conflict Risk

Targets a specific named resource (CZ CELLxGENE Census) with a clear niche and explicitly redirects local-data analysis to scanpy/anndata/scvi-tools, minimizing conflict risk.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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