Machine Learning Claude Skills
1 780 machine learning skills from 282 authors. They train and fine-tune models, build embeddings, run RAG and measure quality. Half of them fit into 2 252 tokens or less — that is what one costs your context window when the agent loads it. 424 ship runnable scripts rather than instructions alone. 10 of them cannot work without an MCP server, most often rube. We also found 397 copies of these same skills sitting in other people's repositories — counted once here, not 397 times.
1 780 unique 282 authors 5 updated this month 189 from vendors
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
Walk through omicverse's single-cell preprocessing tutorials to QC PBMC3k data, normalise counts, detect HVGs, and run PCA/embedding pipelines on CPU, CPU–GPU mixed, or GPU stacks.
Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.
Guide users through omicverse's spatial transcriptomics tutorials covering preprocessing, deconvolution, and downstream modelling workflows across Visium, Visium HD, Stereo-seq, and Slide-seq datasets.
Retrieves gene expression and omics datasets from ArrayExpress and BioStudies with gene disambiguation, experiment quality assessment, and structured reports. Creates comprehensive dataset profiles with metadata, sample information, and download links. Use when users need expression data, omics datasets, or mention ArrayExpress (E-MTAB, E-GEOD) or BioStudies (S-BSST) accessions.
Analyze metabolomics data including metabolite identification, quantification, pathway analysis, and metabolic flux. Processes LC-MS, GC-MS, NMR data from targeted and untargeted experiments. Performs normalization, statistical analysis, pathway enrichment, metabolite-enzyme integration, and biomarker discovery. Use when analyzing metabolomics datasets, identifying differential metabolites, studying metabolic pathways, integrating with transcriptomics/proteomics, discovering metabolic biomarkers, performing flux balance analysis, or characterizing metabolic phenotypes in disease, drug response, or physiological conditions.
Integrate and analyze multiple omics datasets (transcriptomics, proteomics, epigenomics, genomics, metabolomics) for systems biology and precision medicine. Performs cross-omics correlation, multi-omics clustering (MOFA+, NMF), pathway-level integration, and sample matching. Coordinates ToolUniverse skills for expression data (RNA-seq), epigenomics (methylation, ChIP-seq), variants (SNVs, CNVs), protein interactions, and pathway enrichment. Use when analyzing multi-omics datasets, performing integrative analysis, discovering multi-omics biomarkers, studying disease mechanisms across molecular layers, or conducting systems biology research that requires coordinated analysis of transcriptome, genome, epigenome, proteome, and metabolome data.
Production-ready single-cell and expression matrix analysis using scanpy, anndata, and scipy. Performs scRNA-seq QC, normalization, PCA, UMAP, Leiden/Louvain clustering, differential expression (Wilcoxon, t-test, DESeq2), cell type annotation, per-cell-type statistical analysis, gene-expression correlation, batch correction (Harmony), trajectory inference, and cell-cell communication analysis. NEW: Analyzes ligand-receptor interactions between cell types using OmniPath (CellPhoneDB, CellChatDB), scores communication strength, identifies signaling cascades, and handles multi-subunit receptor complexes. Integrates with ToolUniverse gene annotation tools (HPA, Ensembl, MyGene, UniProt) and enrichment tools (gseapy, PANTHER, STRING). Supports h5ad, 10X, CSV/TSV count matrices, and pre-annotated datasets. Use when analyzing single-cell RNA-seq data, studying cell-cell interactions, performing cell type differential expression, computing gene-expression correlations by cell type, analyzing tumor-immune communication, or answering questions about scRNA-seq datasets.
Computational analysis framework for spatial multi-omics data integration. Given spatially variable genes (SVGs), spatial domain annotations, tissue type, and disease context from spatial transcriptomics/proteomics experiments (10x Visium, MERFISH, DBiTplus, SLIDE-seq, etc.), performs comprehensive biological interpretation including pathway enrichment, cell-cell interaction inference, druggable target identification, immune microenvironment characterization, and multi-modal integration. Produces a detailed markdown report with Spatial Omics Integration Score (0-100), domain-by-domain characterization, and validation recommendations. Uses 70+ ToolUniverse tools across 9 analysis phases. Use when users ask about spatial transcriptomics analysis, spatial omics interpretation, tissue heterogeneity, spatial gene expression patterns, tumor microenvironment mapping, tissue zonation, or cell-cell communication from spatial data.
Analyze spatial transcriptomics data to map gene expression in tissue architecture. Supports 10x Visium, MERFISH, seqFISH, Slide-seq, and imaging-based platforms. Performs spatial clustering, domain identification, cell-cell proximity analysis, spatial gene expression patterns, tissue architecture mapping, and integration with single-cell data. Use when analyzing spatial transcriptomics datasets, studying tissue organization, identifying spatial expression patterns, mapping cell-cell interactions in tissue context, characterizing tumor microenvironment spatial structure, or integrating spatial and single-cell RNA-seq data for comprehensive tissue analysis.
Perform statistical modeling and regression analysis on biomedical datasets. Supports linear regression, logistic regression (binary/ordinal/multinomial), mixed-effects models, Cox proportional hazards survival analysis, Kaplan-Meier estimation, and comprehensive model diagnostics. Extracts odds ratios, hazard ratios, confidence intervals, p-values, and effect sizes. Designed to solve BixBench statistical reasoning questions involving clinical/experimental data. Use when asked to fit regression models, compute odds ratios, perform survival analysis, run statistical tests, or interpret model coefficients from provided data.
| dataset understanding + smart downsampling + train/test splits, algorithmic selection (HVG/DE/RF/scGeneFit/SpaPROS), optimal sub-panel discovery (ARI vs size), biological completion with a stability gate (Completion Rule), consensus scoring and completion (only if there is still room), and benchmarking on test splits (ARI/NMI/Silhouette + UMAP similarity).
| annotation, and trajectory inference. These are high-priority actionable workflows — load them first for common single-cell tasks.
Protein language models (ESM3, ESM C) for sequence generation, structure prediction, inverse folding, and embeddings. Design novel proteins, extract ML features, or fold sequences. Local GPU or EvolutionaryScale Forge API. Use AlphaFold for traditional folding; RDKit for small molecules.
Open-source FAIR biology data framework. Version artifacts (AnnData, DataFrame, Zarr), track lineage, validate via ontologies (Bionty), query datasets. Integrates with Nextflow, Snakemake, W&B, scVI. For scRNA-seq use scanpy; for ontology lookups use bionty.
Molecular featurization hub (100+ featurizers) for ML. SMILES to fingerprints (ECFP, MACCS, MAP4), descriptors (RDKit 2D, Mordred), pretrained embeddings (ChemBERTa, GIN, Graphormer), pharmacophores. Scikit-learn compatible with parallelization/caching. For QSAR, virtual screening, similarity, and molecular DL.
> AI autonomous research agent for LLM training optimization using opencode as the agent. The agent autonomously modifies train.py, runs experiments, evaluates val_bpb, "start experiment", "train model", "autonomous research", "optimize LLM training".
Expert agricultural extension professional with 15+ years in farmer training, technology transfer, and rural development. Specializes in adult learning, Farmer Field Schools, participatory approaches, and behavior change communication. Use when: extension programs, farmer-training, technology-transfer, rural-development.
> Expert-level AgentScope developer skill for building production-ready LLM agents. Transforms AI into an experienced AgentScope architect with deep knowledge of ReAct agents, multi-agent orchestration, memory modules, voice agents, MCP/A2A multi-agent, voice agent, MCP, A2A, memory, fine-tuning.
Expert-level AI Application Engineer with deep knowledge of RAG systems, LangChain, LlamaIndex, vector databases, prompt engineering, LLM API integration, and agent frameworks
Expert AI Compute Platform Engineer with 10+ years building and operating large-scale GPU clusters for AI training
Expert LLM Training Engineer with 6+ years of experience in large-scale model pre-training, fine-tuning, alignment, and efficient inference. Use when building, training, or optimizing large language models. Triggers: "llm training", "pre-training", "fine-tuning", "RLHF", "loss spike", "LoRA", "FSDP". Works with Claude Code, OpenAI Codex, Kimi Code, OpenCode, Cursor, Cline, OpenClaw.
Expert-level LLM Research Scientist with deep knowledge of transformer architectures, RLHF, DPO, Constitutional AI, alignment research, evaluation benchmarks, and scaling laws
Elite NLP Engineer skill with expertise in transformer architectures (BERT, GPT, T5), text processing pipelines, LLM fine-tuning, RAG systems, and production NLP deployment. Transforms AI into a principal NLP engineer capable of building state-of-the-art language understanding systems. Use when: nlp, llm, transformers, bert, gpt, text-processing, rag, fine-tuning.
Expert-level Prompt Engineer skill. Transforms AI into a specialist who designs, evaluates, and optimizes prompts for LLMs, RAG pipelines, and agent workflows. Covers prompt patterns (zero-shot, few-shot, CoT, ReAct, Tree-of-Thought), RAG context injection and chunking strategies, agent tool-calling and multi-agent coordination, LLM-as-judge evaluation pipelines, and prompt injection
Expert-level End-to-End Autonomous Driving Researcher specializing in UniAD/VAD/DriveLM architectures, BEV perception, transformer-based world models, and rigorous closed-loop evaluation on nuScenes and Waymo Open Dataset benchmarks. Use when: e2e-autonomous, bev-perception, imitation-learning, world-model, nuScenes.
Expert-level Brain-Computer Interface Engineer specializing in neural signal acquisition, spike sorting, LFP/ECoG decoding, closed-loop neurofeedback systems, and implantable BCI device development from electrode array design through FDA regulatory pathways. Use when: bci, neural-decoding, eeg-ecog, spike-sorting, closed-loop-neurofeedback.
Master calligraphy instructor with 20+ years in Chinese calligraphy (楷书、行书、草书、隶书、篆书) and brush painting. Trained under renowned calligraphers, with expertise in stroke mechanics, character composition, and the philosophical foundations of the art. Use when: education, teaching, calligraphy, chinese-calligraphy, brush-painting.
Expert-level Civil Service Exam Trainer with deep knowledge of government recruitment systems, competitive exam strategies, interview techniques, and career pathway planning for public sector positions
Expert-level Continuing Education Coordinator with deep knowledge of adult learning theory (Andragogy), professional development standards, workforce training regulations, and CE accreditation requirements
Expert-level Corporate Internal Trainer with deep knowledge of instructional design, employee development frameworks, training delivery methodologies, and organizational learning systems
A professional corporate trainer specializing in employee training program design, skill development workshops, and organizational learning. Designs and delivers engaging learning experiences that drive measurable behavior change and business impact. Use when: education, teaching, corporate, training, learning-design.
Expert-level E-commerce Livestream Trainer with deep knowledge of live selling techniques, platform operations (TikTok Shop, Taobao Live, JD Live), audience engagement, and sales conversion
Expert-level IT Training Instructor with deep knowledge of coding bootcamps, software development curricula, programming pedagogy, and technical skill development. Transforms AI into a seasoned IT educator with 10+ years of technical training experience. Use when: it-training, coding-courses, software-education, technical-training, programming-instructor.
Expert-level Language Test Trainer with deep knowledge of IELTS, TOEFL, GRE, PTE academic testing formats, scoring rubrics, and test-taking strategies. Transforms AI into a seasoned language instructor with 10+ years of test preparation experience. Use when: ielts, toefl, language-test, test-preparation, esl.
Expert Maternity Nurse Trainer with 15+ years training new mothers and healthcare professionals in newborn care, postpartum recovery, and lactation consulting. Specializes in practical skills training, certification preparation, and mother-baby bonding Use when: education, maternity, newborn-care, maternal-health, professional-certification.
Expert-level Language Trainer with deep knowledge of second language acquisition (SLA), TEFL/TESOL methodology, pronunciation training, fluency development, and communicative language teaching
Expert Outward Bound Trainer with 15+ years of experience in adventure-based learning, leadership development, and team building
Expert-level Sports Coach with deep knowledge of athletic training methodology, sport-specific skill development, periodization programming, injury prevention, sports psychology, and team dynamics
Expert Training Class Advisor with 10+ years managing K12 and adult training classes. Specializes in student progress tracking, parent communication, classroom management, and student psychological development
Expert Training Manager specializing in corporate learning, talent development, training program design, and organizational capability building. Expert in needs assessment, training delivery, learning technologies, and measuring training effectiveness. Use when: training-management, corporate-learning, talent-development, training-design, organizational-development, learning-and-development.
Expert Training School Principal with deep knowledge of educational operations, business development, instructor management, curriculum oversight, and regulatory compliance for private training institutions
Expert Tutoring Center Manager specializing in educational business operations, tutor recruitment and training, student enrollment, and quality assurance. Expert in curriculum delivery, customer service, and learning outcome optimization. Use when: tutoring-center, education-business, tutor-management, student-enrollment, learning-outcomes, educational-operations.
Expert Vocational Trainer with deep knowledge of competency-based education, industry certifications, workforce development, and career coaching
Break LLM name defaults with external entropy. Use when character names cluster around statistical medians (Chen, Patel, Maya, Marcus), when cast has collision risks, or when fantasy cultures need phonologically consistent naming.
Guide competency framework development and operation. Use when building training that produces capability, when existing training doesn't produce competence, when structuring knowledge for multiple audiences, or when setting up feedback loops to surface gaps.
通过 reasoning_effort、Magic String、组合推理题和离线日期题快速检测当前 API 是否为真实 Claude 模型，并在需要时升级到身份、工具、元数据与嵌套层级的深度审查。用于怀疑模型真假、来源异常、被第三方包装，或需要输出模型真实性检测报告时。
【已废弃并合并】此技能已迁移至新版酒店查询、预订技能rollinggo-hotel-booking。如果是下载过程，请直接选择 rollinggo-hotel-booking。触发此技能后大模型会引导用户迁移到新版。