Skill UI

Plotly is a powerful Python graphing library designed to create highly interactive, publication-quality visualizations. It supports over 40 chart types, including scatter plots, heatmaps, candlestick charts, and geographical maps. Ideal for building sophisticated dashboards, conducting deep exploratory data analysis, and creating rich, web-embeddable presentations with features like zooming, panning, and hover tooltips.

This skill provides a comprehensive workflow to transform raw data into professional visual charts. It intelligently analyzes data features (e.g., trends, comparisons, flows) to select the optimal chart type (line, bar, pie, etc.). Users provide data and specifications, and the skill generates a high-quality, detailed chart image using a structured JavaScript process.

This skill enables users to generate high-quality videos using structured JSON prompts and optional reference images. It supports automated Python script execution for video creation, allowing detailed control over content, style, and technical specifications. Ideal for creating cinematic clips, animations, or visual storytelling with AI assistance.

Expert skill for generating production-quality Python scripts specifically for the FreeCAD CAD application. This includes automating complex 3D modeling tasks, creating parametric FeaturePython objects, performing advanced geometric operations (Boolean, Fillet, Loft), building custom GUI tools using PySide, and handling mesh/FEM analyses via the FreeCAD Python API. Ideal for CAD automation and engineering visualization.

Defines Salesforce Lightning Web Component, Aura, and Visualforce quality/security standards covering SLDS 2 styling, accessibility (WCAG 2.1 AA), data access patterns, component communication rules, XSS/CSRF protections, view state management, and Jest testing requirements for guided UI development and reviews.

DeepTools is a comprehensive Python command-line toolkit for processing and analyzing high-throughput sequencing data. It supports quality control, normalization, sample comparison, and generating publication-quality visualizations for ChIP-seq, RNA-seq, and ATAC-seq experiments. Key features include converting BAM to bigWig, assessing sequencing depth, creating heatmaps around genomic features, and performing correlation analysis. Ideal for bioinformatics workflows requiring robust genomic data processing and visualization.

Matplotlib is a foundational Python library for creating static, animated, and interactive plots with full customization. It supports various plot types like line, scatter, bar, and heatmaps, suitable for scientific and statistical visualizations. Users can customize appearance, create multi-panel figures, and export to PNG, PDF, or SVG. Ideal for publication-quality graphics and integrating with Jupyter notebooks.

This specialized skill automates the process of converting visual designs (from Stitch) into high-quality, modular React and Vite components. It adheres to modern frontend best practices, enforcing logic isolation via custom hooks, data decoupling using mock data files, and ensuring type safety with TypeScript interfaces. The workflow includes automated asset fetching, style mapping (Tailwind), and rigorous validation cycles to produce production-ready, maintainable code.

Scanpy is a scalable Python toolkit for single-cell RNA-seq analysis, covering quality control, normalization, dimensionality reduction, clustering, and visualization. It supports converting R formats to h5ad and includes ready-to-run CLI scripts for end-to-end workflows, making it ideal for exploratory scRNA-seq analysis and publication-quality plotting.

Seaborn is a Python visualization library built on matplotlib for creating statistical graphics. It integrates with pandas for dataset-oriented plotting, offering publication-quality defaults for distributions, relationships, and categorical comparisons. Ideal for exploratory data analysis, multivariate analysis, and complex multi-panel figures. Supports various plot types like box plots, violin plots, and heatmaps.

A comprehensive tool for creating high-quality training datasets for custom object detection and segmentation models. It supports multiple advanced annotation methods including BBox drawing, SAM2 pixel-perfect segmentation, and DINOv3 visual grounding. Features include AI auto-detection, object tracking, and standardized COCO format export, streamlining the entire data pipeline from capture to training.

AI design studio for high-fidelity HTML prototypes, presentations, animations, infographics, and expert design critiques. For every new visual project it first presents three distinct directions to choose from, uses verified brand assets, and aims for studio-quality output indistinguishable from human design.