Route web data visualization work. Use when the user needs chart choice, visual critique, dashboards, maps or geospatial views, Gantt timelines, UML/software diagrams, scrollytelling, reports or exports, testing, accessibility, browser implementation, or concept-first visual design.
npx skills add https://github.com/openai/plugins --skill data-visualization
Use this skill as the implicit orchestrator for the plugin. Classify the task, choose the smallest useful specialist skill set, and route before doing deep chart, renderer, testing, accessibility, or export work. Specialist skills stay explicit-only unless this router hands off to them.
Default stance: the best visualization is the simplest truthful view that answers the user's question with the least decoding burden. Preserve evidence quality first: correct task abstraction, trustworthy data treatment, visible caveats, direct labels, accessible encodings, mobile viability, shareable state, and QA. Do not default to dashboards, 3D, animation, generated imagery, particles, or WebGL unless they carry analytical meaning.
Contextual imagery, atmospheric marks, and motion must be evidence-bearing. Do not use broad translucent brush strokes, wispy ribbons, bokeh/orbs, cinematic wallpaper, stock-photo haze, or decorative gradients as substitutes for data layers. When motion, flow, density, intensity, or spread appears, encode it with measured or clearly schematic contours, sampled fields, trajectories, particles with a defined unit or meaning, or annotated layers.
Mobile is a primary surface. Unless the user explicitly excludes it, treat large-screen and mobile portrait as sibling states. Add mobile landscape when a wide substrate, AR/camera/motion, two-handed interaction, or keyboard-heavy workflow needs it.
../../references/foundations/embedded-visualization-self-use.md, inventory the layers, assign owners, and use specialist passes for substantial layers.../../references/foundations/meaning-preserving-visual-design-workflow.md and ../../references/foundations/mobile-first-responsive-visualization.md; generate large-screen and mobile concepts, pause for approval, and treat approved concepts as semantic contracts.When routing is unclear, read ./references/route-by-problem.md or ./references/prompt-routing-examples.md. When stack choice is unclear, read ./references/default-stack-selection.md.
../../references/foundations/sensitive-geopolitical-and-humanitarian-stories.md; distinguish measured, estimated, disputed, dated, and schematic layers.../../references/foundations/fictional-data-story-simulation.md; require enough deterministic simulated data to support the visual density../references/route-by-problem.md, ./references/default-stack-selection.md, ./references/prompt-routing-examples.md.../../references/foundations/task-abstraction-and-chart-selection.md, ../../references/foundations/perception-color-and-encoding.md, ../../references/foundations/shareable-state-and-persistence.md, ../../references/foundations/mobile-first-responsive-visualization.md, ../../references/foundations/layout-hierarchy-and-self-explanatory-ux.md, ../../references/foundations/implementation-design-and-tradeoffs.md.../../references/foundations/editorial-infographic-system.md, ../../references/foundations/art-directed-interactive-visual-stories.md, ../../references/foundations/meaning-preserving-visual-design-workflow.md, ../../references/foundations/embedded-visualization-self-use.md, ../../references/foundations/fictional-data-story-simulation.md, ../../references/foundations/sensitive-geopolitical-and-humanitarian-stories.md, ../../references/foundations/operational-visualization-workspaces.md.../../assets/templates/advanced-interactive-visualization-contract.md, ../../assets/templates/visual-design-contract.md, ../../assets/templates/chart-brief.md, ../../assets/templates/visualization-test-plan.md.Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Take openai/data-visualization from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.