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Found 412 Skills
Build ETL pipelines and analytics dashboards using Harvard Art Museums API with SQL and Streamlit
Create SVG graphics through programmatic code generation. Use this skill when the user asks to create icons, logos, illustrations, diagrams, data visualizations, generative art, patterns, fractals, or any vector graphics. Provides executable Python scripts for grids, radial patterns, fractals, waves, particles, charts, icons, and optimization.
State-of-the-art data visualization for React/Next.js/TypeScript with Tailwind CSS. Creates compelling, tested, and accessible visualizations following Tufte principles and NYT Graphics standards. Activate on "data viz", "chart", "graph", "visualization", "dashboard", "plot", "Recharts", "Nivo", "D3". NOT for static images, print graphics, or basic HTML tables.
Guide for creating Observable Notebooks 2.0, the open-source notebook system for interactive data visualization and exploration. Use this skill when creating, editing, or building Observable notebooks.
Knowledge about pyecharts chart creation, HTML report generation, and visualization best practices
Intelligent recommendation system analysis tool that provides implementations of multiple recommendation algorithms, evaluation frameworks, and visual analysis. It requires user behavior data, product information, or rating data for use, supports recommendation algorithms such as collaborative filtering and matrix factorization, and generates personalized recommendation results and evaluation reports.
Kpi Definition Helper - Auto-activating skill for Data Analytics. Triggers on: kpi definition helper, kpi definition helper Part of the Data Analytics skill category.
Expert guide for LayerChart, a Svelte component library for building diverse data visualizations (Cartesian, radial, hierarchical, geo, graph) with unopinionated building blocks, motion primitives, and advanced interactions.
Research tool for visually exploring BLS Occupational Outlook Handbook data with an interactive treemap, LLM-powered scoring pipeline, and data scraping/parsing utilities.
Use when the user needs ML pipelines, statistical analysis, data preprocessing, feature engineering, model selection, experiment tracking, or data visualization. Triggers: dataset exploration, model training, feature engineering, hyperparameter tuning, experiment tracking setup, statistical hypothesis testing, visualization creation.
Review football data code and visualisations for correctness. Use after building a chart, data pipeline, or analysis. Dispatches specialised reviewers for data correctness, chart conventions, visual inspection, and interactive edge cases.
NYT-newsroom Layout + Staggered Reveal Animation + Editorial-grade Charts (Line/Bar/Range Band)