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Claude Skills by MarieLynneBlock
github.com/MarieLynneBlock304 skills3 installs300 views
- PyopenmsComplete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.Votes: 0GitHub stars: 4
- PysamGenomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.Votes: 0GitHub stars: 4
- 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: 4
- Pytorch LightningDeep learning framework (PyTorch Lightning). Organise 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: 4
- PyzoteroInteract with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.Votes: 0GitHub stars: 4
- QiskitIBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimisation 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: 4
- 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: 4
- 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, specialised algorithms.Votes: 0GitHub stars: 4
- 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: 4
- 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: 4
- Research LookupLook up current research information using the Parallel Chat API (primary) or Perplexity sonar-pro-search (academic paper searches). Automatically routes queries to the best backend. Use for finding papers, gathering research data, and verifying scientific information.Votes: 0GitHub stars: 4
- RowanCloud-based quantum chemistry platform with Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimisation, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2). Use when tasks involve quantum chemistry calculations, molecular property prediction, DFT or semiempirical methods, neural network potentials (AIMNet2), protein-ligand binding predictions, or automated co...Votes: 0GitHub stars: 4
- ScanpyStandard single-cell RNA-seq analysis pipeline. Use for QC, normalisation, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualisation. 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: 4
- 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: 4
- 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: 4
- 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: 4
- Scientific SchematicsCreate publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialised in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualisations.Votes: 0GitHub stars: 4
- 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: 4
- 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: 4
- 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: 4
- Scikit SurvivalComprehensive toolkit for survival analysis and time-to-event modelling 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: 4
- ScveloRNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.Votes: 0GitHub stars: 4
- 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 modelling, batch effects, multimodal data. For standard analysis pipelines use scanpy.Votes: 0GitHub stars: 4
- 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: 4
- 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: 4
- 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: 4
- 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: 4
- 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: 4
- 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: 4
- TiledbvcfEfficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.Votes: 0GitHub stars: 4
- Timesfm ForecastingZero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.Votes: 0GitHub stars: 4
- 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: 4
- TorchdrugPyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modelling, 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: 4
- 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, summarisation, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.Votes: 0GitHub stars: 4
- 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. Prioritises brevity and clinical actionability.Votes: 0GitHub stars: 4
- 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: 4
- UsfiscaldataQuery the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or ...Votes: 0GitHub stars: 4
- 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: 4
- VaexUse this skill for processing and analysing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualisation 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 visualisations of big data, or build ML pipelines that do not fit in memory.Votes: 0GitHub stars: 4
- 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: 4
- What If OracleRun structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like "what if...", "what would happen if...", "what are the possibilities", "explore scenarios", "scenario analysis", "possibility space", "what could go wrong", "best case / worst case", "risk analysis", "contingency planning", "strategic options", or any question about uncertain futures. Also trigger when the user faces a fork-in-the-road decision, want...Votes: 0GitHub stars: 4
- WritingUse this skill to create high-quality academic papers, literature reviews, grant proposals, clinical reports, and other research and scientific documents backed by comprehensive research and real, verifiable citations. Use this skill whenever the user asks for written output such as a report, paper...etc.Votes: 0GitHub stars: 4
- 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: 4
- 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: 4
- Data Breach Blast RadiusPre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/sources.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast...Votes: 0GitHub stars: 4
- Gdpr CompliantApply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, bre...Votes: 0GitHub stars: 4
- Security ReviewAI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for SQL injection, XSS, command injection, exposed API keys, hardcoded secrets, insecure dependencies, access control issues, or any request like "is my code secure?", "review for security issues", "a...Votes: 0GitHub stars: 4
- Threat Model AnalystFull STRIDE-A threat model analysis and incremental update skill for repositories and systems. Supports two modes: (1) Single analysis — full STRIDE-A threat model of a repository, producing architecture overviews, DFD diagrams, STRIDE-A analysis, prioritised findings, and executive assessments. (2) Incremental analysis — takes a previous threat model report as baseline, compares the codebase at the latest (or a given commit), and produces an updated report with change tracking (new, resolved...Votes: 0GitHub stars: 4
- Code To CoachDeconstruct code into bite-sized, logical chunks from a coaching perspective. Remove abstraction, explain the "why" behind each concept, identify best practices, code smells, and cognitive load issues. Use structured frameworks to provide thorough, pedagogical analysis that teaches *how to think* about code, not just what it does.Votes: 0GitHub stars: 4
- Exam ReadyFor each syllabus topic, extract from the provided material: - What it is (1 line definition — exam-ready) - 3–5 key points an examiner expects - Important keywords to use in the answer (bold them) - Any important diagram or figure — describe what it shows in 2 lines - 1–2 sentences the student can directly write in their exam answer (or MCQ trick if exam type is MCQ) - 1 examiner-style practice question to test recallVotes: 0GitHub stars: 4