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Claude Skills by mdbabumiamssm
github.com/mdbabumiamssm1,581 skills3 installs3,534 views
- Medgemma Health AiBuild and evaluate medical text and vision applications with Google MedGemma, including MedGemma 1.5 workflows for CT, MRI, whole-slide pathology, longitudinal chest X-rays, lab reports, and EHR text. Use when prototyping, fine-tuning, deploying, or validating MedGemma-based health AI under clinical data and safety controls.Votes: 0GitHub stars: 32
- Cjk Viz--> --- name: bio-cjk-viz description: "CJK (\u4E2D\u65E5\u97E9) \u5B57\u4F53\u68C0\u6D4B\u4E0E matplotlib \u914D\ \u7F6E\u3002\u4EFB\u4F55\u6D89\u53CA\u4E2D\u6587\u6807\u7B7E\u3001\u6807\u9898\u3001\ \u56FE\u4F8B\u7684 \u53EF\u89C6\u5316\u4EFB\u52A1\u542F\u52A8\u524D\u5FC5\u987B\u5148\ \u6267\u884C\u672C skill \u7684\u5B57\u4F53\u68C0\u6D4B\u6D41\u7A0B\uFF0C\u786E\u4FDD\ \u4E0D\u4F1A\u51FA\u73B0\u65B9\u5757\u4E71\u7801\u3002 \u9002\u7528\u4E8E matplotlib\ \ / seaborn / plotly \u9759\u6001\u5...Votes: 0GitHub stars: 32
- BioNeMo Framework--> --- name: nvidia-bionemo-framework description: Stand up NVIDIA BioNeMo Framework + NIM microservices to train, fine-tune, and deploy generative biomolecular models for drug discovery. keywords: - generative-ai - drug-discovery - protein-design - nvidia - bionemo measurable_outcome: Launch BioNeMo Framework from NGC, run one inference (NIM) and one fine-tuning recipe on DGX Cloud or on-prem GPUs within a single working day. license: Apache-2.0 (framework) / NVIDIA AI Enterprise (enterpris...Votes: 0GitHub stars: 32
- BiomedMultiAlignmentFoundationModel Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'biomed-multi-alignment-foundation-model' description: 'Use IBM biomed.omics.bl.sm.ma-ted-458m workflows to connect proteins, small molecules, and single-cell gene data for biomedical discovery.' measurable_outcome: 'Execute skill workflow successfully with valid output within 15 minutes.' allowed-tools: - read_file - run_shell_command - web_fetch ---Votes: 0GitHub stars: 32
- Admet Prediction--> --- name: bio-admet-prediction description: Predicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. Filters for PAINS and other structural alerts. Use when filtering compounds for drug-likeness or prioritizing leads by predicted safety. tool_type: python primary_tool: ADMETlab measurable_outcome: Execute skill workflow successfully with valid output within 15...Votes: 0GitHub stars: 32
- Molecular Descriptors--> --- name: bio-molecular-descriptors description: Calculates molecular descriptors and fingerprints using RDKit. Computes Morgan fingerprints (ECFP), MACCS keys, Lipinski properties, QED drug-likeness, TPSA, and 3D conformer descriptors. Use when featurizing molecules for machine learning or filtering by drug-likeness criteria. tool_type: python primary_tool: RDKit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_...Votes: 0GitHub stars: 32
- Molecular Io--> --- name: bio-molecular-io description: Reads, writes, and converts molecular file formats (SMILES, SDF, MOL2, PDB) using RDKit and Open Babel. Handles structure parsing, canonicalization, and full standardization pipeline including sanitization, normalization, and tautomer canonicalization. Use when loading chemical libraries, converting formats, or preparing molecules for analysis. tool_type: python primary_tool: RDKit measurable_outcome: Execute skill workflow successfully with valid o...Votes: 0GitHub stars: 32
- Reaction Enumeration--> --- name: bio-reaction-enumeration description: Enumerates chemical libraries through reaction SMARTS transformations using RDKit. Generates virtual compound libraries from building blocks using defined chemical reactions with product validation. Use when creating combinatorial libraries or enumerating products from synthetic routes. tool_type: python primary_tool: RDKit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file...Votes: 0GitHub stars: 32
- Similarity Searching--> --- name: bio-similarity-searching description: Performs molecular similarity searches using Tanimoto coefficient on fingerprints via RDKit. Finds structurally similar compounds using ECFP or MACCS keys and clusters molecules by structural similarity using Butina clustering. Use when finding analogs of a query compound or clustering chemical libraries. tool_type: python primary_tool: RDKit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed...Votes: 0GitHub stars: 32
- Substructure Search--> --- name: bio-substructure-search description: Searches molecular libraries for substructure matches using SMARTS patterns with RDKit. Filters compounds by pharmacophore features, functional groups, or scaffold matches with atom mapping. Use when finding compounds containing specific chemical moieties or filtering libraries by structural features. tool_type: python primary_tool: RDKit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tool...Votes: 0GitHub stars: 32
- Virtual Screening--> --- name: bio-virtual-screening description: Performs structure-based virtual screening using AutoDock Vina 1.2 for molecular docking. Prepares receptor PDBQT files, generates ligand conformers, defines binding site boxes, and ranks compounds by predicted binding affinity. Use when screening chemical libraries against a protein structure to find potential binders. tool_type: python primary_tool: vina measurable_outcome: Execute skill workflow successfully with valid output within 15 minut...Votes: 0GitHub stars: 32
- DeepsemsOceanBiosyntheticLlmAgent Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'deepsems-ocean-biosynthetic-llm-agent' description: 'Agentic workflow that applies a DeepSeMS-style large language model to mine biosynthetic gene clusters and secondary metabolite potential from global ocean microbiome metagenomes.' measurable_outcome: 'Execute skill workflow successfully with valid output within 15 minutes.' allowed-tools: - read_file - run_shell_command - web_fetch ---Votes: 0GitHub stars: 32
- Medea--> --- name: bio-medea-therapeutic-discovery description: An AI agent for therapeutic discovery that executes transparent, multi-step omics analyses including research planning, code execution, and literature reasoning. tool_type: mixed primary_tool: Unknown measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Medea is a multi-stage AI agent designed for therapeutic discovery, modeled after 2026 state-...Votes: 0GitHub stars: 32
- Boltz2 Biomolecular InteractionsRun Boltz-2 biomolecular interaction predictions for protein, nucleic-acid, ligand, and complex structures with binding-affinity outputs. Use for hit discovery, binder-versus-decoy prioritization, hit-to-lead comparisons, lead optimization, complex modeling, or reproducible Boltz YAML and batch inference workflows.Votes: 0GitHub stars: 32
- Txgemma TherapeuticsOperate Google TxGemma prediction and chat models for therapeutic property prediction across small molecules, proteins, nucleic acids, diseases, targets, and cell lines. Use when formatting Therapeutics Data Commons tasks, choosing TxGemma model size or variant, running local or Model Garden inference, fine-tuning on private therapeutic data, or evaluating TxGemma in drug-discovery workflows.Votes: 0GitHub stars: 32
- ChromfoundScatacFoundationModel Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'chromfound-scatac-foundation-model' description: 'Apply ChromFound, a genome-wide foundation model for single-cell chromatin accessibility (scATAC-seq), to enable cell-type annotation, regulatory element discovery, and cross-tissue transfer.' measurable_outcome: 'Execute skill workflow successfully with valid output within 15 minutes.' allowed-tools: - read_file - run_shell_command - web_fetch ---Votes: 0GitHub stars: 32
- Atac Peak Calling--> --- name: bio-atac-seq-atac-peak-calling description: Call accessible chromatin regions from ATAC-seq data using MACS3 with ATAC-specific parameters. Use when identifying open chromatin regions from aligned ATAC-seq BAM files, different from ChIP-seq peak calling. tool_type: cli primary_tool: macs3 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Atac Qc--> --- name: bio-atac-seq-atac-qc description: Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify problematic samples. tool_type: mixed primary_tool: deeptools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Differential Accessibility--> --- name: bio-atac-seq-differential-accessibility description: Find differentially accessible chromatin regions between conditions using DiffBind or DESeq2. Use when comparing chromatin accessibility between treatment groups, cell types, or developmental stages in ATAC-seq experiments. tool_type: r primary_tool: DiffBind measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Footprinting--> --- name: bio-atac-seq-footprinting description: Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when identifying TF occupancy patterns within accessible regions, as TF binding protects DNA from Tn5 cutting. tool_type: cli primary_tool: tobias measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Motif Deviation--> --- name: bio-atac-seq-motif-deviation description: Analyze transcription factor motif accessibility variability using chromVAR. Use when identifying which TF motifs show variable accessibility across samples or conditions in ATAC-seq data. tool_type: r primary_tool: chromVAR measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Measure per-sample variability in transcription factor motif accessibili...Votes: 0GitHub stars: 32
- Nucleosome Positioning--> --- name: bio-atac-seq-nucleosome-positioning description: Extract nucleosome positions from ATAC-seq data using NucleoATAC, ATACseqQC, and fragment analysis. Use when analyzing chromatin organization, identifying nucleosome-free regions at promoters, or characterizing nucleosome occupancy patterns from ATAC-seq fragment size distributions. tool_type: mixed primary_tool: NucleoATAC measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: ...Votes: 0GitHub stars: 32
- Chipseq Qc--> --- name: bio-chipseq-qc description: ChIP-seq quality control metrics including FRiP (Fraction of Reads in Peaks), cross-correlation analysis (NSC/RSC), library complexity, and IDR (Irreproducibility Discovery Rate) for replicate concordance. Use to assess experiment quality before downstream analysis. Use when assessing ChIP-seq data quality metrics. tool_type: mixed primary_tool: deepTools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allo...Votes: 0GitHub stars: 32
- Chipseq Visualization--> --- name: bio-chipseq-visualization description: Visualize ChIP-seq data using deepTools, Gviz, and ChIPseeker. Create heatmaps, profile plots, and genome browser tracks. Visualize signal around peaks, TSS, or custom regions. Use when visualizing ChIP-seq signal and peaks. tool_type: mixed primary_tool: deepTools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Differential Binding--> --- name: bio-chipseq-differential-binding description: Differential binding analysis using DiffBind. Compare ChIP-seq peaks between conditions with statistical rigor. Requires replicate samples. Outputs differentially bound regions with fold changes and p-values. Use when comparing ChIP-seq binding between conditions. tool_type: r primary_tool: DiffBind measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_comm...Votes: 0GitHub stars: 32
- Motif Analysis--> --- name: bio-chipseq-motif-analysis description: De novo motif discovery and known motif enrichment analysis using HOMER and MEME-ChIP. Identify transcription factor binding motifs in ChIP-seq, ATAC-seq, or other genomic peak data. Use when finding enriched DNA motifs in peak sequences. tool_type: cli primary_tool: HOMER measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Identify DNA sequence mot...Votes: 0GitHub stars: 32
- Peak Annotation--> --- name: bio-chipseq-peak-annotation description: Annotate ChIP-seq peaks to genomic features and genes using ChIPseeker. Assign peaks to promoters, exons, introns, and intergenic regions. Find nearest genes and calculate distance to TSS. Generate annotation plots and statistics. Use when annotating ChIP-seq peaks to genomic features. tool_type: r primary_tool: ChIPseeker measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_fi...Votes: 0GitHub stars: 32
- Peak Calling--> --- name: bio-chipseq-peak-calling description: ChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats including narrowPeak and broadPeak BED files. Use when calling peaks from ChIP-seq alignments. tool_type: cli primary_tool: macs3 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: ...Votes: 0GitHub stars: 32
- Super Enhancers--> --- name: bio-chipseq-super-enhancers description: Identifies super-enhancers from H3K27ac ChIP-seq data using ROSE and related tools. Use when studying cell identity genes, cancer-associated regulatory elements, or master transcription factor binding regions that cluster into large enhancer domains. tool_type: cli primary_tool: ROSE measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Identify supe...Votes: 0GitHub stars: 32
- Bismark Alignment--> --- name: bio-methylation-bismark-alignment description: Bisulfite sequencing read alignment using Bismark with bowtie2/hisat2. Handles genome preparation and produces BAM files with methylation information. Use when aligning WGBS, RRBS, or other bisulfite-converted sequencing reads to a reference genome. tool_type: cli primary_tool: bismark measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Dmr Detection--> --- name: bio-methylation-dmr-detection description: Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types. tool_type: r primary_tool: methylKit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Methylation Calling--> --- name: bio-methylation-calling description: Extract methylation calls from Bismark BAM files using bismark_methylation_extractor. Generates per-cytosine reports for CpG, CHG, and CHH contexts. Use when extracting methylation levels from aligned bisulfite sequencing data for downstream analysis. tool_type: cli primary_tool: bismark measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Methylkit Analysis--> --- name: bio-methylation-methylkit description: DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection. tool_type: r primary_tool: methylKit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Clinical Trial Matcher--> --- name: 'clinical-trial-matcher' description: 'Matches patient profiles to open clinical trials using vector similarity and inclusion/exclusion criteria. Use when a user provides patient data and asks for relevant trials.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- This skill matches a patient's clinical profile against a database of active clinical trials (ClinicalTrials.gov).Votes: 0GitHub stars: 32
- Crispr Designer--> --- name: 'crispr-designer' description: 'Designs guide RNA (gRNA) sequences for CRISPR-Cas9 editing, including off-target analysis. Use when a user needs to edit a gene or asks for gRNA sequences.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- This skill designs high-efficiency guide RNAs for gene editing experiments.Votes: 0GitHub stars: 32
- Regulatory Drafter--> --- name: 'regulatory-drafter' description: 'Drafts regulatory documents (FDA, EMA) with audit trails and specific "Thinking Block" reasoning. Use for high-stakes compliance writing.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- This skill generates compliant drafts for regulatory submissions, emphasizing auditability and adherence to guidelines (ICH, FDA).Votes: 0GitHub stars: 32
- Algorithmic Art--> --- name: 'algorithmic-art' description: 'Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists'' work to avoid copyright violations.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - ru...Votes: 0GitHub stars: 32
- Brand Guidelines--> --- name: 'brand-guidelines' description: 'Applies Anthropic''s official brand colors and typography to any sort of artifact that may benefit from having Anthropic''s look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 32
- Skill Creator--> ---name: skill-creator description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. metadata: short-description: Create or update a skill keywords: - skill-creator - automation - biomedical measurable_outcome: execute task with >95% success rate. allowed-tools: - read_file - run_shell_command ---" This skill provi...Votes: 0GitHub stars: 32
- Bulkrna Batch CorrectionLoad when removing batch effects from a multi-cohort bulk RNA-seq dataset using ComBat (R or Python implementation). Skip if there is only one batch, or for single-cell batch integration (use sc-batch-integration), or for spatial multi-slice integration (use spatial-integrate).Votes: 0GitHub stars: 32
- Bulkrna CoexpressionLoad when discovering gene co-expression modules and hub genes in a bulk RNA-seq cohort via WGCNA-style soft-thresholded networks. Skip for direct DE comparison (use bulkrna-de) or PPI lookup of an existing gene list (use bulkrna-ppi-network); single-cell co-expression uses sc-grn instead.Votes: 0GitHub stars: 32
- Bulkrna DeLoad when comparing gene expression between two conditions in bulk RNA-seq count data. Skip when the data is single-cell (use sc-de) or spatial (use spatial-de), or when you need exon-level alternative splicing (use bulkrna-splicing).Votes: 0GitHub stars: 32
- Bulkrna DeconvolutionLoad when estimating cell-type proportions in bulk RNA-seq samples from a single-cell or signature-matrix reference. Skip if the data is already single-cell (no deconvolution needed) or for spatial deconvolution (use spatial-deconv).Votes: 0GitHub stars: 32
- Bulkrna EnrichmentLoad when running pathway / GO term enrichment on a bulk RNA-seq DE result list. Skip if the input is single-cell (use sc-enrichment), spatial (use spatial-enrichment), or for metabolite pathways (use metabolomics-pathway-enrichment).Votes: 0GitHub stars: 32
- Bulkrna Geneid MappingLoad when converting gene identifiers between Ensembl, Entrez, and HGNC symbol in a bulk RNA-seq count matrix. Skip if the input is already in the desired identifier system, for organisms outside human/mouse, or for non-bulk-counts inputs.Votes: 0GitHub stars: 32
- Bulkrna Ppi NetworkLoad when querying STRING for the protein-protein interaction subgraph induced by a bulk RNA-seq DEG list and finding hub genes. Skip for pathway enrichment of the same list (use bulkrna-enrichment) or for de novo co-expression network discovery (use bulkrna-coexpression).Votes: 0GitHub stars: 32
- Bulkrna QcLoad when checking a bulk RNA-seq count matrix for library-size outliers, gene detection rates, and sample-sample correlation before DE. Skip if data is raw FASTQ (use bulkrna-read-qc) or aligner logs (use bulkrna-read-alignment), or for single-cell counts (use sc-qc).Votes: 0GitHub stars: 32
- Bulkrna Read AlignmentLoad when summarising STAR / HISAT2 / Salmon alignment-rate logs in bulk RNA-seq. Skip if data is raw FASTQ (use bulkrna-read-qc) or already counted (use bulkrna-qc), or for genome-DNA alignment (use genomics-alignment).Votes: 0GitHub stars: 32
- Bulkrna Read QcLoad when checking raw FASTQ quality (Phred / GC / adapter / Q20-Q30) before alignment in bulk RNA-seq. Skip if reads are already aligned (use bulkrna-read-alignment) or counted (use bulkrna-qc), or for single-cell FASTQ (use sc-fastq-qc).Votes: 0GitHub stars: 32
- Bulkrna SplicingLoad when summarising rMATS / SUPPA2 alternative-splicing output and identifying significant differential splicing events. Skip if you only have count-level DE (use bulkrna-de) or for splicing in single-cell or spatial data (currently unsupported).Votes: 0GitHub stars: 32