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Agent skills

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Agent skill

Cell Figure Preparation Guide

Cell (Cell Press) figure preparation: resolution (300-1000 DPI), formats (TIFF/PDF), RGB color, Avenir/Arial fonts, uppercase panel labels, strict image manipulation policies.

ClaudeCodexOpenClawContent & Media
jaechang-hits385
Agent skill

PNAS Figure Preparation Guide

PNAS figure preparation: resolution (300-1000 PPI), formats (TIFF/EPS/PDF), strict RGB-only color, Arial/Helvetica fonts, italicized uppercase panel labels, automated image screening.

OpenClawContent & Media
jaechang-hits385
Agent skill

Chart Designer

Design and generate publication-quality charts — bar, line, pie, scatter, heatmaps, and interactive D3 visualizations.

ClaudeData & Analytics
inbharatai43
Agent skill

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Differential gene expression analysis for bulk RNA-seq count matrices using a DESeq2-like workflow in Python; use when you need Wald tests, FDR correction, and optional LFC shrinkage for condition/batch/covariate designs.

OpenClawData & Analytics
aipoch2,022
Agent skill

biopython-phylo

Use Bio.Phylo to read/write phylogenetic trees and perform visualization and statistics; use when tree parsing/conversion, pruning/rerooting, distance calculation, or plotting is required.

OpenClawData & Analytics
aipoch2,022
Agent skill

biopython-advanced

Advanced Biopython modules for motifs, population genetics, sequence utilities, restriction analysis, clustering, and GenomeDiagram visualization; use when you need extended bioinformatics analysis beyond basic sequence I/O and alignment.

OpenClawData & Analytics
aipoch2,022
Agent skill

Classification Models for Omics Data

Builds diagnostic and prognostic classifiers on omics feature matrices with regularized logistic regression, random forest, and gradient-boosted trees, handling the p>>n regime, batch shortcut learning, class imbalance, and probability calibration. Use when building a classifier from expression, ...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232
Agent skill

Model Interpretation for Omics Classifiers

Explains ML predictions on omics data with SHAP, LIME, and permutation importance, handling the correlated-feature trap, the conditional-vs-interventional Shapley choice, and the attribution-is-not-causation boundary. Use when interpreting an omics classifier, debugging shortcut/batch learning, o...

ClaudeCodexOpenClawData & Analytics
GPTomics1,232

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