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Claude Skills by mdbabumiamssm
github.com/mdbabumiamssm1,578 skills3 installs3,530 views
- Medaka Polishing--> --- name: bio-longread-medaka description: Polish assemblies and call variants from Oxford Nanopore data using medaka. Uses neural networks trained on specific basecaller versions. Use when improving ONT-only assemblies or calling variants from Nanopore data without short-read polishing. tool_type: cli primary_tool: medaka measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Nanopore Methylation--> --- name: bio-long-read-sequencing-nanopore-methylation description: Calls DNA methylation from Oxford Nanopore sequencing data using signal-level analysis. Use when detecting 5mC or 6mA modifications directly from nanopore reads without bisulfite conversion. tool_type: cli primary_tool: modkit measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Structural Variants--> --- name: bio-longread-structural-variants description: Detect structural variants from long-read alignments using Sniffles, cuteSV, and SVIM. Use when detecting deletions, insertions, inversions, translocations, or complex rearrangements from ONT or PacBio data, especially those missed by short-read methods. tool_type: cli primary_tool: sniffles measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Genotype Imputation--> --- name: bio-phasing-imputation-genotype-imputation description: Impute missing genotypes using reference panels with Beagle or Minimac4. Use when increasing variant density for GWAS, harmonizing data across genotyping platforms, or inferring variants not directly typed in array data. tool_type: cli primary_tool: beagle measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Haplotype Phasing--> --- name: bio-phasing-imputation-haplotype-phasing description: Phase genotypes into haplotypes using Beagle or SHAPEIT. Resolves which alleles are inherited together on each chromosome. Use when preparing VCF files for imputation, HLA typing, or population genetic analyses requiring phased haplotypes. tool_type: cli primary_tool: beagle measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Imputation Qc--> --- name: bio-phasing-imputation-imputation-qc description: Quality control of phasing and imputation results. Filter by INFO scores, assess accuracy, and prepare imputed data for downstream analysis. Use when filtering low-quality imputed variants or validating imputation accuracy before GWAS. tool_type: mixed primary_tool: bcftools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Reference Panels--> --- name: bio-phasing-imputation-reference-panels description: Download, prepare, and manage reference panels for phasing and imputation. Covers 1000 Genomes, HRC, and TOPMed panels. Use when setting up imputation infrastructure or selecting appropriate reference panels for target populations. tool_type: cli primary_tool: bcftools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- ScFoundation Model Agent--> --- name: 'scfoundation-model-agent' description: 'Unified agent for leveraging single-cell foundation models (scGPT, scBERT, Geneformer, scFoundation) for cross-species annotation, perturbation prediction, and gene network inference.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **scFoundation Model Agent** provides a unified interface to leverage state-of-the-art single-cell foundation...Votes: 0GitHub stars: 6
- Bone Marrow AI Agent--> --- name: 'bone-marrow-ai-agent' description: 'AI-powered bone marrow morphology analysis, cell classification, and hematologic disorder diagnosis using deep learning on aspirate and biopsy images.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Bone Marrow AI Agent** provides comprehensive AI-driven analysis of bone marrow aspirate and biopsy specimens. It performs automated cell identi...Votes: 0GitHub stars: 6
- CHIC ML Framework Agent--> --- name: 'chic-ml-framework-agent' description: 'Machine learning framework for inferring high-risk clonal hematopoiesis from complete blood count data without sequencing, reducing the number needed to sequence for CHIP screening.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **CHIC (Clonal Hematopoiesis Inference from Counts) ML Framework Agent** uses machine learning to identify indiv...Votes: 0GitHub stars: 6
- CHIP Clonal Hematopoiesis Agent--> --- name: 'chip-clonal-hematopoiesis-agent' description: 'AI-powered clonal hematopoiesis of indeterminate potential (CHIP) detection, risk stratification, and cardiovascular/malignancy risk prediction using genomic and clinical data.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **CHIP Clonal Hematopoiesis Agent** provides comprehensive detection and risk stratification of clonal hemato...Votes: 0GitHub stars: 6
- Coagulation Thrombosis Agent--> --- name: 'coagulation-thrombosis-agent' description: 'AI-powered analysis of coagulation disorders, thrombosis risk prediction, anticoagulation management, and platelet function assessment using machine learning.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Coagulation and Thrombosis Agent** provides AI-driven analysis of hemostatic disorders, thrombosis risk assessment, and anticoag...Votes: 0GitHub stars: 6
- Bead Normalization--> --- name: bio-flow-cytometry-bead-normalization description: Bead-based normalization for CyTOF and high-parameter flow cytometry. Covers EQ bead normalization, signal drift correction, and batch normalization. Use when correcting instrument drift in CyTOF or harmonizing data across batches. tool_type: r primary_tool: CATALYST measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Clustering Phenotyping--> --- name: bio-flow-cytometry-clustering-phenotyping description: Unsupervised clustering and cell type identification for flow/mass cytometry. Covers FlowSOM, Phenograph, and CATALYST workflows. Use when discovering cell populations in high-dimensional cytometry data without predefined gates. tool_type: r primary_tool: CATALYST measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Compensation Transformation--> --- name: bio-flow-cytometry-compensation-transformation description: Spillover compensation and data transformation for flow cytometry. Covers compensation matrix calculation, application, and biexponential/arcsinh transforms. Use when correcting spectral overlap between fluorophores or transforming data for analysis. tool_type: r primary_tool: flowCore measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_comm...Votes: 0GitHub stars: 6
- Cytometry Qc--> --- name: bio-flow-cytometry-cytometry-qc description: Comprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying problematic samples before analysis. tool_type: r primary_tool: flowAI measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Differential Analysis--> --- name: bio-flow-cytometry-differential-analysis description: Differential abundance and state analysis for cytometry data. Compare cell populations between conditions using statistical methods. Use when testing for significant changes in cell frequencies or marker expression between groups. tool_type: r primary_tool: CATALYST measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Fcs Handling--> --- name: bio-flow-cytometry-fcs-handling description: Read and manipulate Flow Cytometry Standard (FCS) files. Covers loading data, accessing parameters, and basic data exploration. Use when loading and inspecting flow or mass cytometry data before preprocessing. tool_type: r primary_tool: flowCore measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Gating Analysis--> --- name: bio-flow-cytometry-gating-analysis description: Manual and automated gating for defining cell populations in flow cytometry. Covers rectangular, polygon, and data-driven gates. Use when identifying cell populations through hierarchical gating strategies. tool_type: r primary_tool: flowWorkspace measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Hemoglobinopathy Analysis Agent--> --- name: 'hemoglobinopathy-analysis-agent' description: 'AI-powered analysis of hemoglobin disorders including sickle cell disease, thalassemias, and variant hemoglobins using HPLC, electrophoresis, and molecular data.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Hemoglobinopathy Analysis Agent** provides comprehensive AI-driven analysis of hemoglobin disorders. It integrates HPLC ch...Votes: 0GitHub stars: 6
- MPN Progression Monitor Agent--> --- name: 'mpn-progression-monitor-agent' description: 'AI-powered myeloproliferative neoplasm monitoring for disease progression prediction, treatment response tracking, and transformation risk assessment in PV, ET, and myelofibrosis.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **MPN Progression Monitor Agent** provides comprehensive monitoring of myeloproliferative neoplasms (PV, ET,...Votes: 0GitHub stars: 6
- Myeloma MRD Agent--> --- name: 'myeloma-mrd-agent' description: 'AI-powered minimal residual disease (MRD) analysis for multiple myeloma using next-generation flow cytometry, NGS, and mass spectrometry approaches.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Myeloma MRD Agent** provides comprehensive AI-driven minimal residual disease assessment for multiple myeloma. It integrates next-generation flow cyt...Votes: 0GitHub stars: 6
- Cell Segmentation--> --- name: bio-imaging-mass-cytometry-cell-segmentation description: Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cell segmentation. Use when extracting single-cell data from IMC or MIBI images after preprocessing. tool_type: python primary_tool: cellpose measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Data Preprocessing--> --- name: bio-imaging-mass-cytometry-data-preprocessing description: Load and preprocess imaging mass cytometry (IMC) and MIBI data. Covers MCD/TIFF handling, hot pixel removal, and image normalization. Use when starting IMC analysis from raw MCD files or preparing images for segmentation. tool_type: python primary_tool: steinbock measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Interactive Annotation--> --- name: bio-imaging-mass-cytometry-interactive-annotation description: Interactive cell type annotation for IMC data. Covers napari-based annotation, marker-guided labeling, training data generation, and annotation validation. Use when manually annotating cell types for training classifiers or validating automated phenotyping results. tool_type: python primary_tool: napari measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_...Votes: 0GitHub stars: 6
- Phenotyping--> --- name: bio-imaging-mass-cytometry-phenotyping description: Cell type assignment from marker expression in IMC data. Covers manual gating, clustering, and automated classification approaches. Use when assigning cell types to segmented IMC cells based on protein marker expression or when phenotyping cells in multiplexed imaging data. tool_type: python primary_tool: scanpy measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_fi...Votes: 0GitHub stars: 6
- Quality Metrics--> --- name: bio-imaging-mass-cytometry-quality-metrics description: Quality metrics for IMC data including signal-to-noise, channel correlation, tissue integrity, and acquisition QC. Use when assessing data quality before analysis or troubleshooting problematic acquisitions. tool_type: python primary_tool: numpy measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Spatial Analysis--> --- name: bio-imaging-mass-cytometry-spatial-analysis description: Spatial analysis of cell neighborhoods and interactions in IMC data. Covers neighbor graphs, spatial statistics, and interaction testing. Use when analyzing spatial relationships between cell types, testing for neighborhood enrichment, or identifying cell-cell interaction patterns in imaging mass cytometry data. tool_type: python primary_tool: squidpy measurable_outcome: Execute skill workflow successfully with valid outpu...Votes: 0GitHub stars: 6
- Armored CART Design Agent--> --- name: 'armored-cart-design-agent' description: 'AI-powered design of armored CAR-T cells with cytokine/chemokine expression for enhanced solid tumor efficacy, including IL-12, IL-15, IL-18, and IL-7 armoring strategies.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Armored CAR-T Design Agent** provides AI-assisted design of next-generation armored CAR-T cells engineered to express ...Votes: 0GitHub stars: 6
- CART Design Optimizer Agent--> --- name: 'cart-design-optimizer-agent' description: 'AI-guided CAR-T cell design for solid tumors using antigen prioritization, safety-by-design architectures, and exhaustion-resistant engineering.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **CAR-T Design Optimizer Agent** provides end-to-end AI-guided design of chimeric antigen receptor T-cells. It integrates antigen prioritization,...Votes: 0GitHub stars: 6
- Cytokine Storm Analysis Agent--> --- name: 'cytokine-storm-analysis-agent' description: 'AI-powered cytokine release syndrome (CRS) and cytokine storm analysis for prediction, monitoring, and management in immunotherapy and infectious disease.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Cytokine Storm Analysis Agent** provides comprehensive AI-driven analysis of cytokine release syndrome (CRS) and hyperinflammatory ...Votes: 0GitHub stars: 6
- Immune Checkpoint Combination Agent--> --- name: 'immune-checkpoint-combination-agent' description: 'AI-powered analysis for predicting optimal immune checkpoint inhibitor combinations based on tumor microenvironment, biomarkers, and molecular profiling.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Immune Checkpoint Combination Agent** analyzes tumor molecular profiles to predict optimal immune checkpoint inhibitor (ICI) c...Votes: 0GitHub stars: 6
- NK Cell Therapy Agent--> --- name: 'nk-cell-therapy-agent' description: 'AI-powered NK cell therapy design for cancer immunotherapy including CAR-NK engineering, memory-like NK generation, and KIR/HLA matching optimization.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **NK Cell Therapy Agent** provides AI-driven design and optimization of natural killer cell therapies for cancer treatment. It covers CAR-NK engi...Votes: 0GitHub stars: 6
- TCR Repertoire Analysis Agent--> --- name: 'tcr-repertoire-analysis-agent' description: 'AI-powered T-cell receptor repertoire analysis for cancer diagnosis, immunotherapy response prediction, and therapeutic TCR selection using deep learning and multi-layer ML approaches.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **TCR Repertoire Analysis Agent** provides comprehensive T-cell receptor repertoire analysis for cancer...Votes: 0GitHub stars: 6
- TCR PMHC Prediction Agent--> --- name: 'tcr-pmhc-prediction-agent' description: 'AI-powered TCR-peptide-MHC interaction prediction using AlphaFold3 and deep learning for therapeutic TCR discovery, neoantigen validation, and T cell immunogenicity assessment.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **TCR-pMHC Prediction Agent** predicts T-cell receptor interactions with peptide-MHC complexes using AlphaFold3-bas...Votes: 0GitHub stars: 6
- TCell Exhaustion Analysis Agent--> --- name: 'tcell-exhaustion-analysis-agent' description: 'AI-powered analysis of T-cell exhaustion states, epigenetic scarring, stem-like T-cell populations, and checkpoint blockade response prediction in cancer immunotherapy.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **T-Cell Exhaustion Analysis Agent** provides comprehensive profiling of T-cell dysfunction states in cancer and chro...Votes: 0GitHub stars: 6
- TME Immune Profiling Agent--> --- name: 'tme-immune-profiling-agent' description: 'Comprehensive AI-powered tumor microenvironment immune profiling integrating bulk deconvolution, single-cell analysis, and spatial transcriptomics for immunotherapy biomarker discovery.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **TME Immune Profiling Agent** provides comprehensive tumor microenvironment (TME) immune profiling by in...Votes: 0GitHub stars: 6
- Epitope Prediction--> --- name: bio-immunoinformatics-epitope-prediction description: Predict B-cell and T-cell epitopes using BepiPred, IEDB tools, and structure-based methods for vaccine and antibody design. Identify immunogenic regions in antigens. Use when designing vaccines, mapping antibody binding sites, or predicting immunogenic peptides. tool_type: python primary_tool: BepiPred measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run...Votes: 0GitHub stars: 6
- Immcantation Analysis--> --- name: bio-tcr-bcr-analysis-immcantation-analysis description: 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. tool_type: r primary_tool: alakazam measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Requires Immcantation sui...Votes: 0GitHub stars: 6
- Immunogenicity Scoring--> --- name: bio-immunoinformatics-immunogenicity-scoring description: Score and prioritize neoantigens and epitopes for immunogenicity using multi-factor models combining MHC binding, processing, expression, and sequence features. Rank candidates for vaccine design. Use when prioritizing epitopes for vaccine development or identifying the most immunogenic neoantigens. tool_type: python primary_tool: mhcflurry measurable_outcome: Execute skill workflow successfully with valid output within 1...Votes: 0GitHub stars: 6
- Mhc Binding Prediction--> --- name: bio-immunoinformatics-mhc-binding-prediction description: Predict peptide-MHC class I and II binding affinity using MHCflurry and NetMHCpan neural network models. Identify potential T-cell epitopes from protein sequences. Use when predicting MHC binding for vaccine design or neoantigen identification. tool_type: python primary_tool: mhcflurry measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_comman...Votes: 0GitHub stars: 6
- Mixcr Analysis--> --- name: bio-tcr-bcr-analysis-mixcr-analysis description: Perform V(D)J alignment and clonotype assembly from TCR-seq or BCR-seq data using MiXCR. Use when processing raw immune repertoire sequencing data to identify clonotypes and their frequencies. tool_type: cli primary_tool: MiXCR measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Neoantigen Prediction--> --- name: bio-immunoinformatics-neoantigen-prediction description: Identify tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient HLA and may elicit T-cell responses. Use when identifying vaccine targets or checkpoint inhibitor response biomarkers from tumor sequencing data. tool_type: python primary_tool: pVACtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes...Votes: 0GitHub stars: 6
- Repertoire Visualization--> --- name: bio-tcr-bcr-analysis-repertoire-visualization description: Create publication-quality visualizations of immune repertoire data including circos plots, clone tracking, diversity plots, and network graphs. Use when generating figures for repertoire comparisons, clonal dynamics, or V(D)J gene usage. tool_type: mixed primary_tool: VDJtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Scirpy Analysis--> --- name: bio-tcr-bcr-analysis-scirpy-analysis description: Analyze single-cell TCR and BCR data integrated with gene expression using scirpy. Use when working with 10x Genomics VDJ data alongside scRNA-seq or when integrating immune receptor information with cell state analysis. tool_type: python primary_tool: scirpy measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Tcr Epitope Binding--> --- name: bio-immunoinformatics-tcr-epitope-binding description: Predict TCR-epitope specificity using ERGO-II and deep learning models for T-cell receptor antigen recognition. Match TCRs to their cognate epitopes or predict TCR targets. Use when analyzing TCR repertoire specificity or identifying antigen-reactive T-cells. tool_type: python primary_tool: ERGO-II measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_sh...Votes: 0GitHub stars: 6
- Vdjtools Analysis--> --- name: bio-tcr-bcr-analysis-vdjtools-analysis description: Calculate immune repertoire diversity metrics, compare samples, and track clonal dynamics using VDJtools. Use when analyzing repertoire diversity, finding shared clonotypes, or comparing immune profiles between conditions. tool_type: cli primary_tool: VDJtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Opentrons Agent--> --- name: 'opentrons-protocol-agent' description: 'Generates executable Python protocols for Opentrons OT-2 and Flex robots from natural language descriptions.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Opentrons Protocol Agent** bridges the gap between experimental design and physical execution by translating instructions into Opentrons Python API scripts.Votes: 0GitHub stars: 6
- MutualInformationFairnessAuditor Agent--> <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE --> --- name: 'mutual-information-fairness-auditor' description: 'Audit and mitigate intersectional, multiclass model fairness by estimating mutual information between prediction-derived variables and sensitive attributes.' 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
- Cellular Senescence Agent--> --- name: 'cellular-senescence-agent' description: 'AI-powered analysis of cellular senescence for aging research, cancer therapy response, and senolytic drug development.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- The **Cellular Senescence Agent** provides comprehensive AI-driven analysis of cellular senescence signatures for aging research, cancer biology, and senolytic therapeutic deve...Votes: 0GitHub stars: 6