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Claude Skills by mdbabumiamssm
github.com/mdbabumiamssm1,578 skills3 installs3,530 views
- BioMCP--> --- name: biomcp-server description: MCP bio bridge keywords: - MCP - PubMed - ClinicalTrials - server - uv measurable_outcome: Stand up a working BioMCP endpoint (pip or uv) and return ≥1 PubMed + ≥1 ClinicalTrials.gov response to the client within 10 minutes. license: MIT metadata: author: BioMCP Team version: "1.0.0" compatibility: - system: MCP-compliant clients allowed-tools: - web_fetch --- Deploy and operate the BioMCP server so MCP-compatible clients (Claude Desktop, LobeChat, etc...Votes: 0GitHub stars: 6
- BiocontextAiMcpRegistry Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'biocontext-ai-mcp-registry' description: 'Discover, evaluate, and integrate biomedical MCP servers from the BioContextAI Registry — a curated catalog of Model Context Protocol servers for bioinformatics, systems biology, and biomedical agentic AI.' measurable_outcome: 'Execute skill workflow successfully with valid output within 15 minutes.' allowed-tools: - read_file - run_shell_command - web_fetch ---Votes: 0GitHub stars: 6
- PubmedNcbiMcpServer Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'pubmed-ncbi-mcp-server' description: 'MCP server exposing NCBI E-utilities for PubMed search, article metadata and full-text retrieval, citation generation, MeSH exploration, and related-article discovery via STDIO or Streamable HTTP.' measurable_outcome: 'Execute skill workflow successfully with valid output within 15 minutes.' allowed-tools: - read_file - run_shell_command - web_fetch ---Votes: 0GitHub stars: 6
- SQLite MCP Agent**Domain:** Agentic AI / Model Context Protocol (MCP) **Status:** Active **Trend Context:** 2026 MCP StandardizationVotes: 0GitHub stars: 6
- Atlas Mapping--> --- name: bio-machine-learning-atlas-mapping description: Maps query single-cell data to reference atlases using scArches transfer learning with scVI and scANVI models. Transfers cell type labels without retraining on combined data. Use when annotating new single-cell datasets using pre-trained reference models. tool_type: python primary_tool: scvi-tools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_comm...Votes: 0GitHub stars: 6
- Biomarker Discovery--> --- name: bio-machine-learning-biomarker-discovery description: Selects informative features for biomarker discovery using Boruta all-relevant selection, mRMR minimum redundancy, and LASSO regularization. Use when identifying biomarkers from high-dimensional omics data. tool_type: python primary_tool: boruta measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Model Validation--> --- name: bio-machine-learning-model-validation description: Implements nested cross-validation and stratified splits for unbiased model evaluation on biomedical datasets. Prevents data leakage and overfitting in biomarker discovery. Use when validating classifiers or optimizing hyperparameters on omics data. tool_type: python primary_tool: sklearn measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Omics Classifiers--> --- name: bio-machine-learning-omics-classifiers description: Builds classification models for omics data using RandomForest, XGBoost, and logistic regression with sklearn-compatible APIs. Includes proper preprocessing and evaluation metrics for biomarker classifiers. Use when building diagnostic or prognostic classifiers from expression or variant data. tool_type: python primary_tool: sklearn measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. all...Votes: 0GitHub stars: 6
- Prediction Explanation--> --- name: bio-machine-learning-prediction-explanation description: Explains machine learning predictions on omics data using SHAP values and LIME for feature attribution. Identifies which genes or features drive classifier decisions. Use when interpreting biomarker classifiers or understanding model predictions. tool_type: python primary_tool: shap measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Survival Analysis--> --- name: bio-machine-learning-survival-analysis description: Analyzes time-to-event data using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards regression with lifelines. Builds survival models from clinical and omics features. Use when predicting patient survival or modeling time-to-event outcomes. tool_type: python primary_tool: lifelines measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_...Votes: 0GitHub stars: 6
- Linear Algebra--> --- name: 'tensor-operations' description: 'Tensor Operations' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Fundamental linear algebra operations for understanding Transformers and attention mechanisms.Votes: 0GitHub stars: 6
- Probability Statistics--> --- name: 'bayesian-optimizer' description: 'Bayesian Optimize' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Bayesian Optimizer** allows agents to efficiently explore a parameter space to maximize a target metric (yield, purity, binding affinity) with minimal experiments. It uses Gaussian Processes to model uncertainty and the Upper Confidence Bound (UCB) acquisition function.Votes: 0GitHub stars: 6
- Lipidomics--> --- name: bio-metabolomics-lipidomics description: Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classes, chain composition, or lipid-specific pathways. tool_type: mixed primary_tool: lipidr measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Metabolite Annotation--> --- name: bio-metabolomics-metabolite-annotation description: Metabolite identification from m/z and retention time. Covers database matching, MS/MS spectral matching, and confidence level assignment. Use when assigning compound identities to detected features in untargeted metabolomics. tool_type: mixed primary_tool: HMDB measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Msdial Preprocessing--> --- name: bio-metabolomics-msdial-preprocessing description: MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL output files for R/Python analysis or when preferring GUI-based preprocessing. tool_type: mixed primary_tool: msdial measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Normalization Qc--> --- name: bio-metabolomics-normalization-qc description: Quality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis. tool_type: r primary_tool: MetaboAnalystR measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Pathway Mapping--> --- name: bio-metabolomics-pathway-mapping description: Map metabolites to biological pathways using KEGG, Reactome, and MetaboAnalyst. Perform pathway enrichment and topology analysis. Use when interpreting metabolomics results in the context of biochemical pathways. tool_type: r primary_tool: MetaboAnalystR measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Statistical Analysis--> --- name: bio-metabolomics-statistical-analysis description: Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classification models. tool_type: r primary_tool: mixOmics measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Targeted Analysis--> --- name: bio-metabolomics-targeted-analysis description: Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves and internal standards. tool_type: mixed primary_tool: skyline measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Xcms Preprocessing--> --- name: bio-metabolomics-xcms-preprocessing description: XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for untargeted metabolomics. tool_type: r primary_tool: xcms measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Requires Bioconductor 3....Votes: 0GitHub stars: 6
- Microbiome Cancer Agent--> --- name: 'microbiome-cancer-agent' description: 'AI-powered analysis of microbiome-cancer interactions including tumor microbiome profiling, immunotherapy response prediction, and microbiome-targeted therapeutic opportunities.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Microbiome-Cancer Interaction Agent** analyzes relationships between the microbiome and cancer, including tumor-as...Votes: 0GitHub stars: 6
- Amplicon Processing--> --- name: bio-microbiome-amplicon-processing description: Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis. tool_type: r primary_tool: dada2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_s...Votes: 0GitHub stars: 6
- Differential Abundance--> --- name: bio-microbiome-differential-abundance description: Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data. tool_type: r primary_tool: ALDEx2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Diversity Analysis--> --- name: bio-microbiome-diversity-analysis description: Alpha and beta diversity analysis for microbiome data. Calculate within-sample richness, evenness, and between-sample dissimilarity with phyloseq and vegan. Use when comparing community composition across samples or testing for group differences in microbiome structure. tool_type: r primary_tool: phyloseq measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_she...Votes: 0GitHub stars: 6
- Functional Prediction--> --- name: bio-microbiome-functional-prediction description: Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is needed from 16S data without shotgun metagenomics sequencing. tool_type: cli primary_tool: picrust2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Qiime2 Workflow--> --- name: bio-microbiome-qiime2-workflow description: QIIME2 command-line workflow for 16S/ITS amplicon analysis. Alternative to DADA2/phyloseq R workflow with built-in provenance tracking. Use when preferring CLI over R, needing reproducible provenance, or working within QIIME2 ecosystem. tool_type: cli primary_tool: qiime2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Taxonomy Assignment--> --- name: bio-microbiome-taxonomy-assignment description: Taxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and exact matching approaches. Use when assigning taxonomy to ASVs after DADA2 amplicon processing. tool_type: mixed primary_tool: dada2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Data Harmonization--> --- name: bio-multi-omics-data-harmonization description: Preprocessing and harmonization of multi-omics data before integration. Covers normalization, batch correction, feature alignment, and missing value handling across data types. Use when preparing multi-omics datasets for integration analysis. tool_type: r primary_tool: MultiAssayExperiment measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Mixomics Analysis--> --- name: bio-multi-omics-mixomics-analysis description: 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. tool_type: r primary_tool: mixOmics measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell...Votes: 0GitHub stars: 6
- Mofa Integration--> --- name: bio-multi-omics-mofa-integration description: Multi-Omics Factor Analysis (MOFA2) for unsupervised integration of multiple data modalities. Identifies shared and view-specific sources of variation. Use when integrating RNA-seq, proteomics, methylation, or other omics to discover latent factors driving biological variation across modalities. tool_type: r primary_tool: MOFA2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:...Votes: 0GitHub stars: 6
- Similarity Network--> --- name: bio-multi-omics-similarity-network description: Similarity Network Fusion (SNF) for patient stratification using multi-omics data. Integrates multiple data types into a unified patient similarity network. Use when performing patient stratification or integrating multi-omics data into unified similarity networks. tool_type: r primary_tool: SNFtool measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_co...Votes: 0GitHub stars: 6
- Bowtie2 Alignment--> --- name: bio-read-alignment-bowtie2-alignment description: Align short reads using Bowtie2 with local or end-to-end modes. Supports gapped alignment. Use when aligning ChIP-seq, ATAC-seq, or when flexible alignment modes are needed. tool_type: cli primary_tool: bowtie2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Bwa Alignment--> --- name: bio-read-alignment-bwa-alignment description: Align DNA short reads to reference genomes using bwa-mem2, the faster successor to BWA-MEM. Use when aligning DNA short reads to a reference genome. tool_type: cli primary_tool: bwa-mem2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Hisat2 Alignment--> --- name: bio-read-alignment-hisat2-alignment description: Align RNA-seq reads with HISAT2, a memory-efficient splice-aware aligner. Use when STAR's memory requirements are too high or for general RNA-seq alignment. tool_type: cli primary_tool: HISAT2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Star Alignment--> --- name: bio-read-alignment-star-alignment description: Align RNA-seq reads with STAR (Spliced Transcripts Alignment to a Reference). Supports two-pass mode for novel splice junction discovery. Use when aligning RNA-seq data requiring splice-aware alignment. tool_type: cli primary_tool: STAR measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Adapter Trimming--> --- name: bio-read-qc-adapter-trimming description: Remove sequencing adapters from FASTQ files using Cutadapt and Trimmomatic. Supports single-end and paired-end reads, Illumina TruSeq, Nextera, and custom adapter sequences. Use when FastQC shows adapter contamination or before alignment of short reads. tool_type: cli primary_tool: cutadapt measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Remov...Votes: 0GitHub stars: 6
- Contamination Screening--> --- name: bio-read-qc-contamination-screening description: Detect sample contamination and cross-species reads using FastQ Screen. Screen reads against multiple reference genomes to identify bacterial, viral, adapter, or sample swap contamination. Use when suspecting cross-contamination or working with samples prone to microbial contamination. tool_type: cli primary_tool: fastq_screen measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tool...Votes: 0GitHub stars: 6
- Fastp Workflow--> --- name: bio-read-qc-fastp-workflow description: All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps. tool_type: cli primary_tool: fastp measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell...Votes: 0GitHub stars: 6
- Quality Filtering--> --- name: bio-read-qc-quality-filtering description: Filter reads by quality scores, length, and N content using Trimmomatic and fastp. Apply sliding window trimming, remove low-quality bases from read ends, and discard reads below thresholds. Use when reads have poor quality tails or require minimum quality for downstream analysis. tool_type: cli primary_tool: trimmomatic measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_fi...Votes: 0GitHub stars: 6
- Quality Reports--> --- name: bio-read-qc-quality-reports description: Generate and interpret quality reports from FASTQ files using FastQC and MultiQC. Assess per-base quality, adapter content, GC bias, duplication levels, and overrepresented sequences. Use when performing initial QC on raw sequencing data or validating preprocessing results. tool_type: cli primary_tool: fastqc measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell...Votes: 0GitHub stars: 6
- Rnaseq Qc--> --- name: bio-rnaseq-qc description: RNA-seq specific quality control including rRNA contamination detection, strandedness verification, gene body coverage, and transcript integrity metrics. Use when validating RNA-seq libraries before differential expression analysis. tool_type: mixed primary_tool: RSeQC measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- RNA-seq specific QC metrics beyond general...Votes: 0GitHub stars: 6
- Umi Processing--> --- name: bio-read-qc-umi-processing description: 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. tool_type: cli primary_tool: umi_tools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:...Votes: 0GitHub stars: 6
- Cancer Metabolism Agent--> --- name: 'cancer-metabolism-agent' description: 'AI-powered analysis of cancer metabolic reprogramming including Warburg effect, glutamine addiction, lipid metabolism, and metabolic vulnerabilities for therapeutic targeting.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Cancer Metabolism Agent** analyzes tumor metabolic reprogramming to identify vulnerabilities for therapeutic targeti...Votes: 0GitHub stars: 6
- Chromosomal Instability Agent--> --- name: 'chromosomal-instability-agent' description: 'AI-powered analysis of chromosomal instability (CIN) signatures for cancer prognosis, immunotherapy response prediction, and therapeutic vulnerability identification.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Chromosomal Instability Agent** analyzes CIN signatures to predict cancer prognosis, immunotherapy response, and therap...Votes: 0GitHub stars: 6
- Exosome EV Analysis Agent--> --- name: 'exosome-ev-analysis-agent' description: 'AI-powered extracellular vesicle and exosome analysis for cancer biomarker discovery, liquid biopsy applications, and intercellular communication profiling.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Exosome/EV Analysis Agent** provides comprehensive AI-driven analysis of extracellular vesicles for cancer biomarker discovery, liqui...Votes: 0GitHub stars: 6
- GiCancerAiManagementAgent Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'gi-cancer-ai-management-agent' description: 'Coordinate clinician-governed AI workflows for GI cancer management across endoscopy, imaging, pathology, molecular profiling, treatment, trials, and surveillance.' measurable_outcome: 'Execute skill workflow successfully with valid output within 15 minutes.' allowed-tools: - read_file - run_shell_command - web_fetch ---Votes: 0GitHub stars: 6
- HRD Analysis Agent--> --- name: 'hrd-analysis-agent' description: 'AI-powered homologous recombination deficiency (HRD) analysis for PARP inhibitor response prediction using genomic scarring signatures and BRCA pathway assessment.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **HRD Analysis Agent** provides comprehensive analysis of homologous recombination deficiency for predicting response to PARP inhibitor...Votes: 0GitHub stars: 6
- Cfdna Preprocessing--> --- name: bio-cfdna-preprocessing description: Preprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate removal using fgbio. Applies cfDNA-specific quality thresholds and fragment length filtering. Use when processing plasma cfDNA sequencing data before downstream analysis. tool_type: python primary_tool: fgbio measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-...Votes: 0GitHub stars: 6
- Ctdna Mutation Detection--> --- name: bio-ctdna-mutation-detection description: Detects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF above 0.5 percent using consensus-based approaches. Use when identifying tumor mutations from plasma DNA or tracking specific variants. tool_type: python primary_tool: VarDict measurable_outcome: Execute skill workflow successfully with valid output within 15 minut...Votes: 0GitHub stars: 6
- Fragment Analysis--> --- name: bio-fragment-analysis description: Analyzes cfDNA fragment size distributions and fragmentomics features using FinaleToolkit or Griffin. Extracts nucleosome positioning patterns, fragment ratios, and DELFI-style fragmentation profiles for cancer detection. Use when leveraging fragment patterns for tumor detection or tissue-of-origin analysis. tool_type: python primary_tool: FinaleToolkit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes....Votes: 0GitHub stars: 6