Skill UI

Craft competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC by aligning narratives with agency review criteria, detailing budgets, personnel plans, and broader impacts, and incorporating required AI-generated schematics via the scientific-schematics skill.

Assess research claims and experimental rigor by evaluating methodology, statistical validity, evidence quality, and biases using GRADE and Cochrane ROB frameworks, plus supporting schematics for complex concepts.

Use Nano Banana 2 plus Gemini 3.1 Pro Preview to iteratively craft publication-quality scientific schematics—neural nets, pathways, or system diagrams—matching document-type quality thresholds.

scikit-bio provides a Python-native biological data toolkit for reading/writing FASTA/Newick files, manipulating sequences, building alignments and phylogenies, and calculating diversity metrics for microbiome and ecology workflows.

Toolkit for Python-based survival and time-to-event modeling with scikit-survival, supporting Cox models, ensemble learners, SVMs, and evaluation metrics for censored data.

Provide a comprehensive toolkit for RNA velocity inference in single-cell RNA-seq data, modeling unspliced/spliced kinetics to infer differentiation directions, latent time, and driver genes while complementing Scanpy pipelines.

Probabilistic deep-learning framework built on PyTorch for single-cell omics; handles batch correction, integration, multimodal and spatial data, differential expression, and transfer learning with unified APIs.

Seaborn is a powerful Python library for creating publication-quality statistical graphics. It is designed for dataset-oriented plotting, making it ideal for exploratory data analysis, multivariate analysis, and visualizing complex relationships, distributions, and comparisons with minimal code. It builds upon Matplotlib, offering high-level interfaces for functions like scatterplots, heatmaps, and pair plots.

SimPy is a powerful, process-based discrete-event simulation framework written in Python. It is designed for modeling complex systems where entities interact with shared resources and time-based events occur, such as manufacturing lines, service queues, network traffic, or logistics networks. Use this skill to analyze resource contention, simulate process optimization, conduct capacity planning, and model dynamic system behaviors.

Statsmodels is a comprehensive Python library dedicated to advanced statistical modeling and econometrics. It provides tools for rigorous statistical inference, including Ordinary Least Squares (OLS), Generalized Linear Models (GLM), mixed-effects models, and time series analysis (ARIMA). Use this skill for detailed diagnostics, coefficient estimation, hypothesis testing, and producing publication-ready statistical reports in fields like econometrics and biostatistics.

Guides symbolic mathematics work in Python, covering algebraic simplification, calculus, equation solving, linear algebra, physics, number theory, geometry, and code generation to deliver exact symbolic results instead of numeric approximations.

Generates concise 3-4 page LaTeX/PDF treatment plans across medical specialties, embedding SMART goals, evidence-based interventions, HIPAA-compliant formatting, and mandated AI-generated schematics for quick clinical actionability.