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Claude Skills by infometa
github.com/infometa1,636 skills21 installs5,293 views
- PytdcTherapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.Votes: 0GitHub stars: 279
- Pytorch LightningDeep 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.Votes: 0GitHub stars: 279
- QiskitIBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.Votes: 0GitHub stars: 279
- QutipQuantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.Votes: 0GitHub stars: 279
- RdkitCheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.Votes: 0GitHub stars: 279
- Reactome DatabaseQuery Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.Votes: 0GitHub stars: 279
- Research GrantsWrite competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.Votes: 0GitHub stars: 279
- Research LookupLook up current research information using Perplexity Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter. Automatically selects the best model based on query complexity. Search academic papers, recent studies, technical documentation, and general research information with citations.Votes: 0GitHub stars: 279
- ScanpyStandard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.Votes: 0GitHub stars: 279
- Scholar EvaluationSystematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.Votes: 0GitHub stars: 279
- Scientific BrainstormingCreative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.Votes: 0GitHub stars: 279
- Scientific Critical ThinkingEvaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.Votes: 0GitHub stars: 279
- Scientific SchematicsCreate publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.Votes: 0GitHub stars: 279
- Scientific SlidesBuild slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.Votes: 0GitHub stars: 279
- Scientific VisualizationMeta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.Votes: 0GitHub stars: 279
- Scientific WritingCore skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.Votes: 0GitHub stars: 279
- Scikit BioBiological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.Votes: 0GitHub stars: 279
- Scikit LearnMachine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.Votes: 0GitHub stars: 279
- Scikit SurvivalComprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.Votes: 0GitHub stars: 279
- Scvi ToolsDeep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.Votes: 0GitHub stars: 279
- SeabornStatistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.Votes: 0GitHub stars: 279
- ShapModel interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box mo...Votes: 0GitHub stars: 279
- SimpyProcess-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.Votes: 0GitHub stars: 279
- Stable Baselines3Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.Votes: 0GitHub stars: 279
- Statistical AnalysisGuided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.Votes: 0GitHub stars: 279
- StatsmodelsStatistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.Votes: 0GitHub stars: 279
- String DatabaseQuery STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.Votes: 0GitHub stars: 279
- SympyUse this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rath...Votes: 0GitHub stars: 279
- Torch GeometricGraph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.Votes: 0GitHub stars: 279
- TorchdrugPyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis. For pre-trained models and diverse featurizers use deepchem; for benchmark datasets use pytdc.Votes: 0GitHub stars: 279
- TransformersThis skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.Votes: 0GitHub stars: 279
- Treatment PlansGenerate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.Votes: 0GitHub stars: 279
- Umap LearnUMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.Votes: 0GitHub stars: 279
- Uniprot DatabaseDirect REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.Votes: 0GitHub stars: 279
- Uspto DatabaseAccess USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.Votes: 0GitHub stars: 279
- VaexUse this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.Votes: 0GitHub stars: 279
- Venue TemplatesAccess comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.Votes: 0GitHub stars: 279
- Zarr PythonChunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.Votes: 0GitHub stars: 279
- Zinc DatabaseAccess ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.Votes: 0GitHub stars: 279
- Competitive LandscapeThis skill should be used when the user asks to "analyze competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces", or requests competitive strategy analysis.Votes: 0GitHub stars: 279
- BrowsingUse when you need direct browser control - teaches Chrome DevTools Protocol for controlling existing browser sessions, multi-tab management, form automation, and content extraction via use_browser MCP toolVotes: 0GitHub stars: 279
- Ui Ux Pro MaxAI-powered UI/UX design intelligence with 57 UI styles, 95+ color palettes, 56 font pairings, 25 chart types, and 100+ industry-specific reasoning rules across 12 tech stacks. Use when designing, building, creating, implementing, reviewing, fixing, or improving UI/UX code for websites, landing pages, dashboards, SaaS, e-commerce, portfolios, and mobile apps.Votes: 0GitHub stars: 279
- Agent BrowserUse this skill when the user needs browser automation, including opening web pages, taking screenshots, extracting page content, clicking elements, filling forms, or testing web flows. This skill uses the open source vercel-labs/agent-browser CLI and supports macOS, Linux, and Windows x64.Votes: 0GitHub stars: 279
- CloudbaseCloudBase AI Development - Complete toolkit for building Web, Mini Program, and Native App projects with CloudBase. Includes authentication, database (NoSQL/MySQL), cloud functions, CloudRun, storage, AI models, and UI design guidelines.Votes: 0GitHub stars: 279
- Codebuddy Md ImproverAudit and improve CODEBUDDY.md files in repositories. Use when user asks to check, audit, update, improve, or fix CODEBUDDY.md files. Scans for all CODEBUDDY.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CODEBUDDY.md maintenance" or "project memory optimization".Votes: 0GitHub stars: 279
- Find SkillsHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.Votes: 0GitHub stars: 279
- Commands查看插件内置的 Skill 列表与各自职责Votes: 0GitHub stars: 279
- Godot Debug仅当用户明确报告 Godot 项目**已经出错**（报错 / 崩溃 / 编译失败 / 脚本错误 / fix this error / 帮我看下这个 bug），或 build_godot_scene 执行后返回了错误日志时激活。调用 get_debug_errors / get_script_errors / get_editor_output 三个 MCP 单元查询工具并美化呈现。 用户在做新内容开发、部署、新建项目时**不要**激活本 Skill。Votes: 0GitHub stars: 279
- Godot Deploy仅当用户**只关心部署/重连本身**（部署 godot mcp / 安装 godot-mcp / setup mcp / godot mcp 连不上 / 端口 9080 没监听 / 重新连接 godot）， 或被 godot-dev 因 godot-editor 缺失而让位过来时激活。执行 5 步部署 （Node 检查 → server build → .mcp.json 校验 → 下载 godot-editor → 9080 探测）。 用户提到任何具体游戏内容（做贪吃蛇/做平台跳跃/加玩法/改场景）时 **不要**激活本 Skill，应由 godot-dev 决定是否需要部署。Votes: 0GitHub stars: 279
- Godot Dev**Godot 游戏开发统一入口（4.23 三场景分流总 Skill）**。当用户用自然语言提出 任何与「做游戏 / 开发游戏 / 加玩法 / 写 Godot 脚本 / 改场景 / 改节点 / 做关卡 / 做 UI / 做角色 / 做敌人 / 做菜单 / 做 2D / 做 3D / 做 RPG / 做平台跳跃 / 做贪吃蛇 / make a game / build a game / add gameplay / godot script / godot scene」相关的请求时激活。 本 Skill **必须自己执行环境检测、意图判别、流程编排**（4.23.md 明确规定 Skill 负责所有匹配/流程/资源/命令逻辑，不能甩给 MCP），并按照 4.23.md 的 三个场景把控制权分别移交给 [godot-deploy](../godot-deploy/SKILL.md) / [godot-new](../godot-new/SKILL.md) 子流程，或直接用唯一的 MCP 编辑器单元 工具 `build_godot_scene` 完成场景修改。 —— 仅当用户「只想部署...Votes: 0GitHub stars: 279