# One-time use (no install required)
npx bioskill install
# Or install globally for repeated use
npm install -g bioskill
bioskill install
Awesome Bio Agent Skills
A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.
Now tracking NVIDIA BioNeMo Agent Toolkit, Claude Science built-in skills, and the emerging ecosystem of agent-callable tools for life sciences.
1,722 deduplicated skills from 22 open-source repositories, organized into 16 categories. Each skill is a self-contained SKILL.md folder compatible with Claude-based agent frameworks (OpenClaw, NanoClaw, Biomni).
About BioTender
This project is created and maintained by BioTender.
BioTender is a Chinese AI-for-Biology intelligence and media platform covering protein design, structure prediction, virtual cells, AI drug discovery, biological foundation models, scientific agents, AI4Bio startups, and frontier research.
- Website: https://www.biotender.online/
- About: https://www.biotender.online/about/
- Scholar Program: https://www.biotender.online/scholar-program.html
Contents
- Genomics
- Proteomics
- Single-Cell Analysis
- Biology and AI
- Clinical and Medical
- Transcriptomics
- Database Query
- Multi-Omics Integration
- Bioinformatics Utilities
- Visualization
- Workflow Orchestration
- Epigenomics
- Pathway Analysis
- Metagenomics
- Protein Design
- NVIDIA BioNeMo Skills
- Claude Science Skills
- Sources
Genomics
526 skills — WGS/WES analysis, variant annotation, GWAS, CNV, structural variants, haplotype phasing, genome assembly.
| Skill | Source | Description |
|---|---|---|
| bio-alignment-amplicon-clipping | bioskills | Trim PCR primers from aligned reads in amplicon-panel BAMs using samtools ampliconclip. Use when processing SARS-CoV-2 ARTIC, hereditary cancer pan... |
| bio-alignment-filtering | bioskills | Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality al... |
| bio-alignment-indexing | bioskills | Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific... |
| bio-alignment-io | bioskills | Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and othe... |
| bio-alignment-msa-parsing | bioskills | Parse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations,... |
| bio-alignment-msa-statistics | bioskills | Calculate alignment statistics including sequence identity, conservation scores, substitution matrices, and similarity metrics. Use when comparing... |
| bio-alignment-multiple | bioskills | Perform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee. Guides tool and algorithm selection based on dataset size, seq... |
| bio-alignment-pairwise | bioskills | Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, finding optimal alignments, scorin... |
| bio-alignment-sorting | bioskills | Sort alignment files by coordinate or read name using samtools and pysam. Use when preparing BAM files for indexing, variant calling, or paired-end... |
| bio-alignment-structural | bioskills | Align protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA. Predict, score, and superpose backbone coor... |
| bio-alignment-trimming | bioskills | Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when re... |
| bio-alignment-validation | bioskills | Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when... |
| bio-atac-seq-allele-specific-accessibility | bioskills | Detect allele-specific chromatin accessibility from ATAC-seq using WASP, GATK ASEReadCounter, or RASQUAL. Use when mapping cis-regulatory genetic v... |
| bio-atac-seq-atac-peak-calling | bioskills | Call accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC. Use when identifying open chromatin from aligne... |
| bio-atac-seq-consensus-peakset | bioskills | Build a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and major... |
| bio-bam-statistics | bioskills | Generate alignment statistics using samtools flagstat, stats, depth, coverage, and mosdepth. Use when assessing alignment quality, calculating cove... |
| bio-basecalling | bioskills | Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified b... |
| bio-bedgraph-handling | bioskills | Create, manipulate, and convert bedGraph files for genome browser visualization. Covers bedGraph format, conversion to/from bigWig, normalization,... |
| bio-biomart-queries | bioskills | Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use... |
| bio-causal-genomics-colocalization-analysis | bioskills | Test whether two or more traits share a causal variant at a locus using Bayesian colocalization (coloc.abf, coloc.susie, HyPrColoc, moloc, eCAVIAR,... |
| bio-causal-genomics-effector-gene-prioritization | bioskills | Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021),... |
| bio-causal-genomics-fine-mapping | bioskills | Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, M... |
| bio-causal-genomics-genetic-correlation | bioskills | Estimate bivariate genetic correlation (rg) between traits from GWAS summary statistics or individual-level genotypes using cross-trait LDSC, HDL,... |
| bio-causal-genomics-genomic-sem | bioskills | Fits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor... |
| bio-causal-genomics-mediation-analysis | bioskills | Decompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-st... |
| bio-causal-genomics-mendelian-randomization | bioskills | Estimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments. Implements IVW (fixed/random), MR-Egge... |
| bio-causal-genomics-pleiotropy-detection | bioskills | Detect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiot... |
| bio-causal-genomics-proteome-mr-drug-target | bioskills | Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP... |
| bio-causal-genomics-transcriptome-wide-association | bioskills | Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-Mu... |
| bio-cfdna-preprocessing | bioskills | Preprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate removal usi... |
| bio-chipseq-allele-specific-binding | bioskills | Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter;... |
| bio-chipseq-chip-deep-learning | bioskills | Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft moti... |
| bio-chipseq-peak-calling | bioskills | Calls ChIP-seq peaks with MACS3, MACS2, HOMER, or SPP across narrow (TF) and broad (histone) modes. Handles input control matching, fragment-size m... |
| bio-chipseq-visualization | bioskills | Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven trac... |
| bio-clinical-biostatistics-adaptive-designs | bioskills | Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Frie... |
| bio-clinical-biostatistics-categorical-tests | bioskills | Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern M... |
| bio-clinical-biostatistics-power-sample-size | bioskills | Computes sample size and power for clinical trials including continuous, binary, and time-to-event endpoints; superiority, non-inferiority, and equ... |
| bio-clinical-databases-acmg-classification | bioskills | Applies ACMG/AMP 2015 framework with ClinGen SVI specifications, Tavtigian 2018/2020 Bayesian point system, Abou Tayoun 2018 PVS1 decision tree, Pe... |
| bio-clinical-databases-clinvar-lookup | bioskills | Queries ClinVar for variant pathogenicity classifications, ClinGen VCEP curations, and somatic-vs-germline interpretations via REST API, weekly VCF... |
| bio-clinical-databases-dbsnp-queries | bioskills | Resolves rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build... |
...and 486 additional genomics skills in the skills/bioskills/, skills/openclaw/, skills/sciagent/ directories.
Proteomics
167 skills — mass spectrometry analysis, structure prediction, protein design, binding affinity optimization.
| Skill | Source | Description |
|---|---|---|
| bio-atac-seq-nucleosome-positioning | bioskills | Map nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter.... |
| bio-data-visualization-sequence-logos | bioskills | Build sequence logos from aligned DNA, RNA, or protein motifs using ggseqlogo (R), Logomaker (Python), or WebLogo with explicit bits vs probability... |
| bio-generative-design | bioskills | Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based ge... |
| bio-hi-c-analysis-hic-differential | bioskills | Compare Hi-C contact matrices between conditions to identify differential chromatin interactions. Compute log2 fold changes, statistical significan... |
| bio-hi-c-analysis-tad-detection | bioskills | Call topologically associating domains (TADs) from Hi-C data using insulation score, HiCExplorer, and other methods. Identify domain boundaries and... |
| bio-immunoinformatics-mhc-binding-prediction | bioskills | Predict peptide-MHC class I and II binding affinity using MHCflurry and NetMHCpan neural network models. Identify potential T-cell epitopes from pr... |
| bio-immunoinformatics-neoantigen-prediction | bioskills | Identify tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient... |
| bio-interaction-databases | bioskills | Query protein-protein and gene interaction databases (STRING, BioGRID, IntAct, SIGNOR, Reactome, HuRI, HuMAP, OmniPath, ConsensusPathDB, DIP). Use... |
| bio-ml-docking-rescoring | bioskills | Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity)... |
| bio-molecular-io | bioskills | Reads, writes, and converts molecular file formats (SMILES, InChI, SDF V2000/V3000, MOL2, PDB, MMTF) using RDKit and Open Babel with rigorous handl... |
| bio-molecular-standardization | bioskills | Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping,... |
| bio-pdb-geometric-analysis | bioskills | Perform geometric calculations on protein structures using Biopython Bio.PDB. Use when measuring distances, angles, and dihedrals, superimposing st... |
| bio-pdb-structure-io | bioskills | Parse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB,... |
| bio-pdb-structure-modification | bioskills | Modify protein structures using Biopython Bio.PDB. Use when transforming coordinates, removing atoms or residues, adding new entities, modifying B-... |
| bio-pdb-structure-navigation | bioskills | Navigate protein structure hierarchy using Biopython Bio.PDB SMCRA model. Use when accessing models, chains, residues, and atoms, iterating over st... |
| bio-phylo-tree-manipulation | bioskills | Modify phylogenetic tree structure using Biopython Bio.Phylo. Use when rooting trees with outgroups, midpoint, or MAD methods, pruning taxa, collap... |
| bio-population-genetics-population-structure | bioskills | Analyze population structure using PCA and admixture analysis with PLINK and ADMIXTURE. Identify population clusters, assess ancestry proportions,... |
| bio-pose-validation | bioskills | Validates docked / generated protein-ligand poses using PoseBusters physical-validity tests, strain energy quantification, geometric checks (planar... |
| bio-primer-design-primer-validation | bioskills | Validate PCR primers for specificity, dimers, hairpins, and secondary structures using primer3-py thermodynamic calculations. Check self-complement... |
| bio-protac-degraders | bioskills | Designs PROTACs, molecular glues, and bivalent degraders with explicit handling of E3 ligase choice (VHL, CRBN, IAP, MDM2, KEAP1), linker design (l... |
| bio-proteomics-data-import | bioskills | Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when star... |
| bio-proteomics-dia-analysis | bioskills | Data-independent acquisition (DIA) proteomics analysis with DIA-NN and other tools. Use when analyzing DIA mass spectrometry data with library-free... |
| bio-proteomics-peptide-identification | bioskills | Peptide-spectrum matching and protein identification from MS/MS data. Use when identifying peptides from tandem mass spectra. Covers database searc... |
| bio-proteomics-protein-inference | bioskills | Protein grouping and inference from peptide identifications. Use when resolving protein ambiguity from shared peptides. Handles protein groups and... |
| bio-proteomics-quantification | bioskills | Protein quantification from mass spectrometry data including label-free (LFQ, intensity-based), isobaric labeling (TMT, iTRAQ), and metabolic label... |
| bio-proteomics-spectral-libraries | bioskills | Build, manage, and search spectral libraries for proteomics. Use when creating or working with spectral libraries for DIA analysis. Covers DDA-base... |
| bio-qsar-modeling | bioskills | Builds QSAR / QSPR models using chemprop D-MPNN, MolFormer, Uni-Mol, ChemBERTa, random forest baselines, and Gaussian processes with explicit handl... |
| bio-rna-structure-ncrna-search | bioskills | Searches for non-coding RNA homologs and classifies RNA families using Infernal covariance model searches against the Rfam database. Identifies str... |
| bio-rna-structure-structure-probing | bioskills | Analyzes experimental RNA structure probing data from SHAPE-MaP and DMS-MaPseq experiments using ShapeMapper2. Converts mutation rates to per-nucle... |
| bio-scaffold-analysis | bioskills | Analyzes chemical libraries by scaffold using Bemis-Murcko scaffolds, generic frameworks, cyclic skeletons, matched molecular pair (MMP) analysis v... |
| bio-similarity-searching | bioskills | Performs molecular similarity searching using Tanimoto, Tversky, Dice, and cosine coefficients on bit/count fingerprints with explicit choice rules... |
| bio-structural-biology-alphafold-predictions | bioskills | Access and analyze AlphaFold protein structure predictions. Use when predicted structures are needed for proteins without experimental structures,... |
| bio-structural-biology-modern-structure-prediction | bioskills | Predict protein structures using modern ML models including AlphaFold3, ESMFold, Chai-1, and Boltz-1. Use when predicting structures for novel prot... |
| bio-substructure-search | bioskills | Searches molecular libraries for substructure matches using SMARTS patterns with explicit handling of recursive SMARTS, ring membership, aromaticit... |
| bio-transcription-translation | bioskills | Transcribe DNA to RNA and translate to protein using Biopython. Use when converting between DNA, RNA, and protein sequences, finding ORFs, or using... |
| bio-virtual-screening | bioskills | Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice ru... |
| adhd-daily-planner | openclaw | Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-a... |
| alphafold-database | openclaw | Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (... |
| antibody-design-agent | openclaw | An advanced agent for de novo antibody design and optimization using state-of-the-art protein language models (MAGE, RFdiffusion). |
| bindingdb-database | openclaw | Query BindingDB for measured drug-target binding affinities (Ki, Kd, IC50, EC50). Search by target (UniProt ID), compound (SMILES/name), or pathoge... |
...and 127 additional proteomics skills in the skills/kdense/, skills/openclaw/, skills/sciagent/ directories.
Single-Cell Analysis
144 skills — preprocessing, clustering, cell type annotation, trajectory inference, cell communication, multimodal integration.
| Skill | Source | Description |
|---|---|---|
| bio-atac-seq-co-accessibility | bioskills | Infer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linki... |
| bio-atac-seq-deep-learning-atac | bioskills | Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or EnFormer. Use when correcting Tn5 bias with neural networks beyond... |
| bio-atac-seq-enhancer-gene-linking | bioskills | Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target g... |
| bio-atac-seq-motif-deviation | bioskills | Analyze TF motif accessibility variability across samples or single cells using chromVAR. Use when identifying TF motifs whose accessibility correl... |
| bio-atac-seq-single-cell-atac | bioskills | Process and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC. Use when handling 10X scATAC or 10X Multiome (pai... |
| bio-causal-genomics-heritability-partitioning | bioskills | Estimate SNP heritability and partition it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level gen... |
| bio-chipseq-chromatin-state-segmentation | bioskills | Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate H... |
| bio-chipseq-peak-annotation | bioskills | Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPsee... |
| bio-clip-seq-stamp-antibody-free | bioskills | Profiles RNA-binding protein targets without antibody or UV crosslinking using STAMP (APOBEC1-RBP fusion, C-to-U editing), scSTAMP (single-cell), T... |
| bio-crispr-screens-combinatorial-screens | bioskills | Designs and analyzes combinatorial CRISPR screens covering paired-Cas9 (Big Papi, Najm 2018), enhanced AsCas12a multiplex (enCas12a, DeWeirdt 2021)... |
| bio-crispr-screens-perturb-seq-analysis | bioskills | Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a s... |
| bio-data-visualization-dimensionality-reduction-plots | bioskills | Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, loc... |
| bio-data-visualization-matplotlib-fundamentals | bioskills | Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (... |
| bio-expression-matrix-normalization | bioskills | Normalize and transform RNA-seq count matrices for differential expression, visualization, and clustering. Covers between-sample (TMM, RLE, upper q... |
| bio-expression-matrix-sparse-handling | bioskills | Work with sparse matrices for memory-efficient storage of count data. Use when dealing with single-cell data or large bulk RNA-seq datasets where m... |
| bio-flow-cytometry-clustering-phenotyping | bioskills | Unsupervised clustering and cell type identification for flow/mass cytometry. Covers FlowSOM, Phenograph, and CATALYST workflows. Use when discover... |
| bio-flow-cytometry-doublet-detection | bioskills | Detect and remove doublets from flow and mass cytometry data. Covers FSC/SSC gating and computational doublet detection methods. Use when filtering... |
| bio-flow-cytometry-doublet-detection | bioskills | Detect and remove doublets from flow and mass cytometry data. Covers FSC/SSC gating and computational doublet detection methods. Use when filtering... |
| bio-gene-regulatory-networks-coexpression-networks | bioskills | Build weighted gene co-expression networks to identify modules of co-regulated genes and relate them to phenotypes using WGCNA and CEMiTool. Detect... |
| bio-gene-regulatory-networks-multiomics-grn | bioskills | Build enhancer-driven gene regulatory networks by integrating single-cell RNA-seq and ATAC-seq data using SCENIC+ to identify eRegulons linking tra... |
| bio-gene-regulatory-networks-scenic-regulons | bioskills | Infer gene regulatory networks and identify transcription factor regulons from single-cell RNA-seq data using pySCENIC. Discovers co-expression mod... |
| bio-imaging-mass-cytometry-cell-segmentation | bioskills | Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cell segme... |
| bio-imaging-mass-cytometry-interactive-annotation | bioskills | Interactive cell type annotation for IMC data. Covers napari-based annotation, marker-guided labeling, training data generation, and annotation val... |
| bio-imaging-mass-cytometry-phenotyping | bioskills | Cell type assignment from marker expression in IMC data. Covers manual gating, clustering, and automated classification approaches. Use when assign... |
| bio-imaging-mass-cytometry-spatial-analysis | bioskills | Spatial analysis of cell neighborhoods and interactions in IMC data. Covers neighbor graphs, spatial statistics, and interaction testing. Use when... |
| bio-machine-learning-atlas-mapping | bioskills | Maps query single-cell data to reference atlases using scArches transfer learning with scVI and scANVI models. Transfers cell type labels without r... |
| bio-methylation-dmr-detection | bioskills | Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions... |
| bio-read-qc-umi-processing | bioskills | Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and accurate... |
| bio-single-cell-batch-integration | bioskills | Integrate multiple scRNA-seq samples/batches using Harmony, scVI, Seurat anchors, and fastMNN. Remove technical variation while preserving biologic... |
| bio-single-cell-cell-annotation | bioskills | Automated cell type annotation using reference-based methods including CellTypist, scPred, SingleR, and Azimuth for consistent, reproducible cell l... |
| bio-single-cell-cell-communication | bioskills | Infer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis. Use when i... |
| bio-single-cell-clustering | bioskills | Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for running PCA, computing neighbors, clu... |
| [bio-single-cell-data-io](https://github.com/BioTender-max/awesome-bio-ag |
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