Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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medical-entity-extractor
Extract medical entities (symptoms, medications, lab values, diagnoses) from patient messages.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-spatial-transcriptomics-spatial-neighbors
Build spatial neighbor graphs for spatial transcriptomics data using Squidpy. Compute k-nearest neighbors, Delaunay triangulation, and radius-based connectivity for downstream spatial analyses. Use when building spatial neighborhood graphs.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-reporting-figure-export
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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transformers
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-structural-biology-alphafold-predictions
Access and analyze AlphaFold protein structure predictions. Use when predicted structures are needed for proteins without experimental structures, or for confidence scores (pLDDT).
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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umap-learn
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-read-qc-umi-processing
Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and accurate molecule counting is needed, such as in single-cell RNA-seq, low-input RNA-seq, or targeted sequencing to distinguish PCR from biological duplicates.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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rfdiffusion
Generate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying hotspot residues for interface design, (5) Creating symmetric oligomers.
For sequence design after backbone generation, use proteinmpnn. For structure validation, use alphafold or chai. For QC thresholds, use protein-qc.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bulk-rna-seq-deseq2-analysis-with-omicverse
Walk Claude through PyDESeq2-based differential expression, including ID mapping, DE testing, fold-change thresholding, and enrichment visualisation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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histolab
Digital pathology image processing toolkit for whole slide images (WSI). Use this skill when working with histopathology slides, processing H&E or IHC stained tissue images, extracting tiles from gigapixel pathology images, detecting tissue regions, segmenting tissue masks, or preparing datasets for computational pathology deep learning pipelines. Applies to WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-genome-assembly-assembly-polishing
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-geo-data
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-tcr-bcr-analysis-immcantation-analysis
Analyze BCR repertoires for somatic hypermutation, clonal lineages, and B cell phylogenetics using the Immcantation framework. Use when studying B cell affinity maturation, germinal center dynamics, or antibody evolution.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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ipsae
Binder design ranking using ipSAE (interprotein Score from Aligned Errors). Use this skill when: (1) Ranking binder designs for experimental testing, (2) Filtering BindCraft or RFdiffusion outputs, (3) Comparing AF2/AF3/Boltz predictions, (4) Predicting binding success rates, (5) Need better ranking than ipTM or iPAE.
For structure prediction, use chai or alphafold. For QC thresholds, use protein-qc.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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tooluniverse-gwas-finemapping
Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions. Computes posterior probabilities for causal variants, links variants to genes via L2G predictions, annotates functional consequences, and suggests validation strategies. Use when asked to fine-map GWAS loci, prioritize causal variants, identify credible sets, or link GWAS signals to causal genes.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bioservices
Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-multi-omics-mixomics-analysis
Supervised and unsupervised multi-omics integration with mixOmics. Includes sPLS for pairwise integration and DIABLO for multi-block discriminant analysis. Use when performing supervised multi-omics integration or identifying features that discriminate between groups.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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mesh-generation
Plan and evaluate mesh generation for numerical simulations. Use when choosing grid resolution, checking aspect ratios/skewness, estimating mesh quality constraints, or planning adaptive mesh refinement for PDE discretization.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-experimental-design-batch-design
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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differentiation-schemes
Select and apply numerical differentiation schemes for PDE/ODE discretization. Use when choosing finite difference/volume/spectral schemes, building stencils, handling boundaries, estimating truncation error, or analyzing dispersion and dissipation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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single-cell-annotation-skills-with-omicverse
Guide Claude through SCSA, MetaTiME, CellVote, CellMatch, GPTAnno, and weighted KNN transfer workflows for annotating single-cell modalities.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-clinical-databases-polygenic-risk
Calculate polygenic risk scores using PRSice-2, LDpred2, or PRS-CS from GWAS summary statistics. Use when predicting disease risk from genome-wide genetic variants.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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pytdc
Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-single-cell-doublet-detection
Detect and remove doublets (multiple cells captured in one droplet) from single-cell RNA-seq data. Uses Scrublet (Python), DoubletFinder (R), and scDblFinder (R). Essential QC step before clustering to avoid artificial cell populations. Use when identifying and removing doublets from scRNA-seq data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009