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Found 826 Skills
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
Metabase REST API automation and troubleshooting: authenticate (API key preferred, session fallback), export/upsert questions (cards) and dashboards, standardize visualization_settings, and run/export results.
Apple Human Interface Guidelines for content display components. Use this skill when the user asks about "charts component", "collection view", "image view", "web view", "color well", "image well", "activity view", "lockup", "data visualization", "content display", displaying images, rendering web content, color pickers, or presenting collections of items in Apple apps. Also use when the user says "how should I display charts", "what's the best way to show images", "should I use a web view", "how do I build a grid of items", "what component shows media", or "how do I present a share sheet". Cross-references: hig-foundations for color/typography/accessibility, hig-patterns for data visualization patterns, hig-components-layout for structural containers, hig-platforms for platform-specific component behavior.
Best practices for Matplotlib data visualization, plotting, and creating publication-quality figures in Python
Exploratory Data Analysis (EDA): profiling, visualization, correlation analysis, and data quality checks. Use when understanding dataset structure, distributions, relationships, or preparing for feature engineering and modeling.
Implement Syncfusion React Charts component for data visualization. Use this when creating charts, configuring axes and series, or customizing visualization styles. This skill covers chart types, data binding, user interactions, financial indicators, accessibility features, and professional data visualization in React applications.
Implement Syncfusion WPF Bullet Graph (SfBulletGraph) components for performance indicators and KPI visualization. Use this when displaying metrics against targets, creating dashboard gauges, or visualizing performance in qualitative ranges. This skill covers featured measures, comparative measures, qualitative ranges, goal tracking, and compact data visualization for dashboards.
Implement Syncfusion WPF Kanban (SfKanban) control for workflow visualization and task management. Use this when building agile project tracking interfaces, workflow boards, or task management systems. This skill covers card configuration, column management, swim lanes, WIP limits, drag-and-drop functionality, workflows, sorting, and event handling.
Export the Obsidian wiki's knowledge graph to structured formats for use in external tools. Use this skill when the user says "export wiki", "export graph", "export to JSON", "export to Gephi", "export to Neo4j", "graphml", "visualize wiki", "knowledge graph export", or wants to use their wiki data in another tool. Outputs graph.json, graph.graphml, cypher.txt (Neo4j), and graph.html (interactive browser visualization) into a wiki-export/ directory at the vault root.
Generate high-density information graphics, data visualizations, and blueprint-style infographics. Use when: "信息图生成", "数据可视化", "infographic", "蓝图风格", "长图制作", "data visualization", "信息图表", "可视化报告", "vision蓝图", "技术架构图", "思维导图", "知识图谱", "timeline图", "流程图可视化". Creates visually striking, information-dense graphics suitable for technical documentation, architecture diagrams, and knowledge sharing. Part of UniqueClub content toolkit. Learn more: https://uniqueclub.ai
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.
Implement Syncfusion React Sankey Chart to visualize energy flows, process dependencies, and hierarchical relationships between nodes. Use this skill when creating Sankey diagrams, flow visualizations, or node-link networks. Covers installation, nodes and links configuration, labeling, legends, tooltips, events, appearance customization, RTL support, accessibility, and export features.