Search scholarly literature in OpenAlex by topic, author, or institution. Explore citation counts and publication trends, find freely accessible papers, and export research records to CSV for further analysis.
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Keep existing Bayesian modeling requests working through a compatibility alias that routes to the local pymc skill. Reuses the canonical instructions, templates, references, and diagnostic scripts while preserving the name used in existing calls and catalog entries.
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Write MATLAB or GNU Octave scripts for matrix calculations, statistics, signal processing, and scientific plots. Get help with language syntax, import and export data, or convert code between MATLAB and Python for numerical analysis tasks.
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Deploy web projects to Netlify with its command-line tool. The skill checks authentication and project settings, links or creates a site, and publishes a preview or production version with deployment URLs and log links.
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Develop healthcare prediction models from electronic health records and physiological signals. Use PyHealth to prepare data, train models for tasks such as mortality or readmission prediction, and evaluate accuracy, fairness, and how predictions can be explained.
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Calculate defined business, statistical, or quality metrics from available data and test results. It provides formulas and reproducible calculation steps, with checks on units, denominators, and which records are included in each calculation.
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Turn academic papers in LaTeX or PDF format into interactive research websites, narrated presentation videos, and print-ready conference posters. Use existing paper content and figures to prepare materials for conferences, lab websites, and research outreach.
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Organize complex tasks using three Markdown files for plans, findings, and progress. The skill keeps decisions, discoveries, errors, and test results in project files that an agent can consult when making decisions or resuming work.
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Process and compare mass spectra, measurements used to study chemical compounds, with matchms. Clean peak data, standardize metadata, calculate similarity scores, and search reference libraries for candidate compounds in metabolomics research.
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Perform arithmetic, algebra, calculus, matrix operations, number theory, and statistics with SymPy, a symbolic mathematics library. Return exact expressions, numerical values, and LaTeX notation for checking calculations or using results in other work.
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Create scientific and statistical charts in Python, including line plots, scatter plots, heatmaps, and multi-panel figures. Adjust colors, labels, and layouts, then export figures as PNG, PDF, or SVG for papers and presentations.
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Connect external services and databases to Claude Code plugins through MCP, a protocol for exposing tools to agents. The skill guides server configuration, connection choices, authentication, tool permissions, and testing so plugins can use those services.
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Screen compound collections for drug discovery using established drug-likeness rules, structural warnings, and molecular complexity measures. Detect relevant chemical groups, apply property limits, and generate filtering results to support compound selection and prioritization.
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Search NIH Metabolomics Workbench for metabolite structures, study details, and experimental data. Standardize metabolite names with RefMet, find candidate compounds from mass spectrometry measurements, and filter studies by disease, sample source, or analytical method.
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Reviews machine learning preprocessing, features, and data splits for data leakage: information unavailable when making a real prediction. Identifies risky statistics, future data, and validation setups, then suggests corrections using only appropriate training information.
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Analyze Neuropixels neural recordings from raw data through quality review. Supports preprocessing, motion correction, spike sorting to separate signals by neuron, quality metrics, visual inspection, reports, and exports for further review or data sharing.
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Audit Node.js processes started by VCO, identify which are managed and still active, and report stale processes eligible for cleanup. Produce Markdown or JSON reports and simulate cleanup while keeping external and unknown processes outside the candidate set.
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Apply NOWAIT to shorten reasoning model outputs by suppressing reflection words during generation. Includes integration examples for HuggingFace Transformers and vLLM, with guidance on model suitability and potential accuracy loss in distilled models.
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Find current official documentation for building with OpenAI products and APIs. Provides source-linked guidance on Codex, APIs, SDKs, and model capabilities or limits, using dedicated documentation tools before searching official OpenAI websites.
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Supports pathology image analysis in Python, from loading whole-slide images to normalizing stain colors, identifying cell nuclei, mapping spatial relationships, and training machine learning models. It also covers multiplex imaging and marker measurements.
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Write structured reviews of scientific manuscripts and grant proposals. Assess methods, statistics, reproducibility, ethics, and reporting completeness, then organize strengths, major concerns, minor issues, and specific suggestions into constructive feedback.
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Measure indicator calculation speed with BenchmarkDotNet, a benchmarking tool for .NET. Compare batch, incremental, and streaming implementations, detect slowdowns against saved results, and evaluate changes intended to reduce processing time and memory allocations.
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Handle equations, calculus, matrices, unit conversions, and mathematical explanations through one entry point. The skill selects a suitable calculation tool or topic guide, including symbolic math tools that work directly with expressions.
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Estimate intervention effects from existing data using causal analysis methods. Set up models, compare observed outcomes with estimates of what would have happened without intervention, check robustness, and interpret fitted results.
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