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Found 411 Skills
Design and generate accessible, cohesive data visualizations, SVG charts, metric cards, and dashboard tiles with theme-adaptive styling and verified viewports. Use when creating SVG charts, rendering metrics plots, designing dashboard visuals, or visualizing performance trends — even if the user does not explicitly say "fable-dataviz" (e.g. "make a chart of this data", "plot these benchmarks", "create an SVG graph", "visualize these metrics"). Do NOT use for non-visual text-only data summaries or generic code edits.
Data visualization with Recharts 3.x including responsive charts, custom tooltips, animations, and accessibility for React applications. Use when building charts or dashboards with Recharts.
Generate interactive graph visualizations in the browser from any data - codebases, infrastructure, relationships, knowledge maps
Create interactive chart visualizations (bar, line, pie) from data.
Guide for creating data visualizations in Shopify Apps using the Polaris Viz library. Use this skill when building charts, graphs, dashboards, or any data visualization components that need to integrate with the Shopify Admin aesthetic. Covers BarChart, LineChart, DonutChart, SparkLineChart, and theming.
Comprehensive guide for implementing Syncfusion WPF Sparkline (SfSparkline) controls in Windows Presentation Foundation applications. Use this when working with sparklines, mini charts, or trend visualization. This skill covers sparkline types (line, column, area, WinLoss), markers, track ball, range bands, axis controls, and segment customization for compact data visualization in WPF applications.
Use when building research dashboards, annotation tools, data browsers, paper-supporting demos, SOTA explorers, experiment viewers, or frontend interfaces for academic projects.
Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a callable local Origin/OriginPro installation on physical Windows 10/11 x64. Use for beginner “drop in a file and draw it” requests; XPS, XRD, XAS, PL/TRPL, DSC, NMR, FTIR/IR, UV-Vis, electrochemistry, medical/AI evidence, distribution, relationship, error-bar, bar, stacked, pie, Sankey, radar, heatmap, or verified 3D workflows; project-local Python setup; palette selection; and OPJU/PNG/PDF/TIF verification. Do not use on macOS, Linux, WSL, Wine/CrossOver, Parallels, or other VMs; to install or modify Origin; to redistribute reference images; or to claim an unverified Origin route.
Design, audit, or reframe data-heavy dashboards, admin tools, operations consoles, analytics products, and enterprise interfaces as decision interfaces rather than metric collections. Use when a user asks to build or improve a dashboard, KPI page, BI view, analytics UI, operational console, monitoring interface, data visualization, or other screen where a person must prioritize, diagnose, compare, decide, or act.
Start here for Yandex DataLens when the task has not yet settled on a tool, or when the question is about DataLens itself rather than about carrying something out in it: what DataLens is and what it can do; which installation is in play — Yandex Cloud, on-premise, or the internal Yandex Team one — and how they differ in hosts, auth, and capabilities; what a collection, workbook, connection, dataset, chart, or dashboard is and how they relate; and whether to reach for the MCP server, the Python SDK, the HTTP API, or the web UI. Use it to orient and to route to the skill that does the work. NOT for doing the work once the approach is chosen — that is `datalens-sdk` for Python and `datalens-html-pages` for standalone HTML reports — and not for interpreting what business metric values mean.
生成专业信息图，包含 21 种布局类型和 20 种视觉风格。分析内容，推荐布局×风格组合，生成可发布的信息图。当用户要求创建"信息图"、"可视化"、"高密度信息大图"、"visual summary"时使用。
Search and use visualizations that already exist in the project to provide fast and curated data answers.