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scgpt

Embed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.

78

Quality

100%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The body is a tight, executable reference: runnable code with concrete parameters, a clearly sequenced remote-compute workflow with a notification checkpoint, and a symptom→fix troubleshooting table. It does not waste tokens on concepts Claude already knows.

DimensionReasoningScore

Conciseness

Lean and efficient — no padding about what single-cell biology or scGPT is; every section (prerequisites, run, output, remote compute, gotchas, troubleshooting) earns its place and assumes Claude's competence. It is not the level-2 case because there is no unnecessary explanation that could be trimmed.

3 / 3

Actionability

Provides fully executable, copy-paste-ready code with specific values — GeneVocab.from_file on vocab.json, embed_data with gene_col and use_fast_transformer, and a complete submit_job call with real parameters (timeout 1800, 24 GB VRAM, named inputs/outputs).

3 / 3

Workflow Clarity

The remote-compute process is clearly sequenced with an explicit checkpoint: submit_job → 'cell ends here — kernel never blocks' → wait_for_notification → 'When the compute_done notification arrives, act on its payload' → re-enter kernel to attach_job/close, with a troubleshooting table providing error→fix feedback loops.

3 / 3

Progressive Disclosure

No bundle files exist, and the single SKILL.md is organized into well-signaled sections (Prerequisites, How to run, Output format, Remote compute, Gotchas, Troubleshooting) with no nested/deep references — well-organized sections suffice for this skill, per the simple-skills guidance.

3 / 3

Total

12

/

12

Passed

Description

100%

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

The description is concise, third-person, and covers what it does plus three explicit 'Use when' triggers while disambiguating from scVI. It is one of the strongest possible descriptions for this skill class.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Producing cell embeddings from an AnnData for clustering/integration', 'cell-type annotation', 'Gene-level representation for perturbation/GRN tasks' — matching the score-3 anchor of several specific concrete actions.

3 / 3

Completeness

Explicitly answers both 'what' ('Embed and annotate single-cell expression data with scGPT') and 'when' ('Use this skill when: (1)... (2)... (3)...'), matching the score-3 anchor with an explicit trigger clause.

3 / 3

Trigger Term Quality

Uses natural domain terms a single-cell practitioner would say — 'single-cell expression data', 'cell embeddings', 'AnnData', 'clustering/integration', 'cell-type annotation', 'perturbation/GRN' — giving good coverage rather than jargon-only phrasing.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (scGPT single-cell foundation model) and explicitly routes the overlapping case elsewhere ('For probabilistic single-cell models (scVI etc.), use the scvi-tools library'), making mis-triggering unlikely.

3 / 3

Total

12

/

12

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

13

/

16

Passed

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

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