Design dashboards and live visualization systems. Use when the user needs monitoring views, streaming charts, coordinated interactions, downsampling, or performance-aware operational visualization.
npx skills add https://github.com/openai/plugins --skill dashboards-and-real-time-visualization
Use this skill when the visualization is a system, not a screenshot. That means update cadence, latency, interaction design, observability, and rendering budgets matter as much as chart choice.
If the main request is about how to test a live dashboard, freeze streams, mock refresh behavior, or cover alerting and stale states end to end, route first to ../testing-data-visualizations/SKILL.md.
Mobile operational use is default unless explicitly excluded. Use ../../references/foundations/mobile-first-responsive-visualization.md to plan the mobile portrait dashboard, optional landscape mode, touch interaction, on-screen keyboard behavior, spotty connection handling, and alerting or vibration strategy.
This skill covers three tightly related problems:
Interactivity should reduce cognitive load, not hide essential context behind constant mouse movement.
For mobile dashboards, add step-through controls, search, or nearest-item selection for dense marks; do not rely on hover, pixel-perfect taps, or one-finger chart panning that traps page scroll.
../../references/foundations/storytelling-annotation-and-critique.md../../references/foundations/layout-hierarchy-and-self-explanatory-ux.md../../references/foundations/interaction-models-and-progressive-disclosure.md../../references/foundations/mobile-first-responsive-visualization.md../../references/foundations/implementation-design-and-tradeoffs.md./references/monitoring-vs-analysis.md./references/streaming-data-pipelines.md./references/interaction-patterns.md./references/performance-and-degradation.md../testing-data-visualizations/SKILL.mdComprehensive 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/dashboards-and-real-time-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.