Skill UI

This skill generates code to create complex, interactive 3D scenes and visualizations on the web using the Three.js library and WebGL. It covers the entire development lifecycle, including setting up the core components (Scene, Camera, Renderer), defining geometry, applying materials, adding lighting, and implementing animation loops. Ideal for web developers needing to display product mockups, scientific data visualizations, or immersive user experiences.

Automates detection and deep exploratory analysis across 200+ scientific data formats, assessing quality, extracting metadata, and recommending visualizations while generating markdown reports that guide downstream workflows and highlight structure and distributions.

Defines a Markdown/Mermaid-first documentation skill for scientific and technical writing, providing diagram standards, 24 reference types, and templates so every report, README, or analysis stays text-first, versionable, and visualization-ready.

Guides using matplotlib to craft static, animated, and interactive plots through both pyplot and object-oriented APIs, detailing styling, subplots, and export options for publication-ready scientific workflows.

Transforms data into publication-ready figures with multi-panel layouts, precise annotations, colorblind-friendly palettes, and journal formatting using matplotlib, seaborn, and plotly plus export helpers for PDF/EPS/TIFF.

Manim is a powerful Python library used for creating high-quality mathematical and scientific animations. This skill facilitates the generation of educational videos and complex visualizations for presentations. It is ideal for researchers, educators, or content creators who need to visualize complex concepts in an engaging animated format. Note: This specific file is related to localization/translation.

Provides comprehensive tools for academic research, allowing users to search databases like Google Scholar and PubMed. It extracts accurate metadata, validates citations, and generates standard formats like BibTeX. The skill ensures reference accuracy and supports the creation of scientific schematics to enhance document visualization.

A systematic tool for scientific inquiry, guiding users through the entire research process. It helps formulate testable, mechanistic hypotheses from raw observations or preliminary data, following the established scientific method. The workflow includes comprehensive literature review, evidence synthesis, generating competing explanations, and designing experiments, all while mandating the creation of scientific schematics for visualization.

A comprehensive guide to MATLAB and GNU Octave, covering core scientific computing tasks. This skill details capabilities in matrix operations, linear algebra, data visualization (2D/3D), statistical analysis, signal processing, and solving differential equations. It is ideal for users requiring complex numerical simulation, data modeling, and scientific scripting.

Matplotlib is Python's foundational library for creating highly customizable static, animated, and interactive visualizations. It supports various plot types (line, scatter, heatmap, 3D) and offers both pyplot and object-oriented interfaces. Ideal for generating publication-quality scientific charts, complex multi-panel figures, and integrating into notebooks.

This skill provides comprehensive guidance and functionality for creating professional, visually stunning, and academically rigorous slide decks. Designed for research talks, conference presentations, and thesis defenses, it assists in structuring the narrative, integrating complex data visualizations, maintaining consistent design aesthetics, and including proper citations. The recommended output is a combined PDF for maximum visual impact.

A meta-skill dedicated to creating high-quality, publication-ready scientific figures. It guides users on best practices for journal submission, including multi-panel layouts, precise error bar inclusion, colorblind-safe palette usage, and adherence to specific journal styles (Nature, Science). It orchestrates libraries like matplotlib, seaborn, and plotly to ensure optimal resolution and format export (PDF, EPS, TIFF).