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single-cell-rnaseq-pipeline

Generate single-cell RNA-seq analysis code templates for Seurat and Scanpy, supporting QC, clustering, visualization, and downstream analysis. Trigger when users need scRNA-seq analysis pipelines, preprocessing workflows, or batch correction code.

88

1.28x
Quality

86%

Does it follow best practices?

Impact

90%

1.28x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Evaluation results

100%

20%

PBMC Multi-Donor Integration Analysis

Scanpy QC parameters and clustering

Criteria
Without context
With context

Human MT pattern

100%

100%

MT percent threshold

100%

100%

Min genes threshold

100%

100%

Max genes threshold

0%

100%

Normalization target sum

100%

100%

Log transform

100%

100%

HVG count

100%

100%

Leiden clustering

100%

100%

Wilcoxon markers

100%

100%

Neighbor parameters

50%

100%

Harmony for small batches

0%

100%

Relative paths

100%

100%

Without context: $0.3545 · 1m 40s · 16 turns · 23 in / 5,552 out tokens

With context: $1.0438 · 4m 50s · 33 turns · 1,761 in / 9,399 out tokens

100%

38%

Mouse Tumor Microenvironment Multi-Lab scRNA-seq Pipeline

Seurat pipeline with species-specific settings and batch correction

Criteria
Without context
With context

Mouse MT pattern

100%

100%

MT percent threshold

0%

100%

Min genes threshold

100%

100%

Max genes threshold

0%

100%

RPCA for large batches

0%

100%

LogNormalize scale factor

100%

100%

VST nfeatures

50%

100%

PCA dimensions

100%

100%

FindAllMarkers params

100%

100%

Clustering resolution

0%

100%

Relative paths

100%

100%

No API calls

100%

100%

Without context: $0.3013 · 2m 6s · 11 turns · 16 in / 6,415 out tokens

With context: $0.9555 · 3m 46s · 34 turns · 202 in / 7,518 out tokens

70%

2%

Generate scRNA-seq Analysis Pipelines for Cross-Tissue Developmental Study

CLI tool usage and output structure

Criteria
Without context
With context

Script invocation

100%

100%

Tool both flag

100%

100%

Species flag

100%

100%

Trajectory flag

100%

100%

Complex variation batch method

0%

0%

Seurat R file generated

100%

100%

Scanpy Python file generated

100%

100%

README generated

100%

100%

Trajectory code in Scanpy output

100%

100%

Invalid param error format

0%

20%

Batch method in Seurat output

0%

0%

Without context: $0.4615 · 2m 3s · 13 turns · 17 in / 8,908 out tokens

With context: $0.9580 · 3m 52s · 34 turns · 206 in / 9,151 out tokens

Repository
aipoch/medical-research-skills
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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