Plugin · 13 included skills
Data Visualization Toolkit
What should a reader learn from your data? Data Visualization Toolkit helps you choose and build a chart, map, diagram or dashboard that answers that question, then inspect the rendered result.
Start with the reader's question, not the chart type.
What can you do with it?
- 01
Choose and build the clearest chart
Pick the smallest truthful form for your question and data, then build it with readable labels and honest caveats.
- 02
Catch misleading visuals
Review charts and dashboards for distorted scales, hidden uncertainty, accessibility gaps and export problems.
- 03
Explain structure, place and time
Make diagrams, maps, schedules and visual stories that stay faithful to the underlying data.
Start with one question.
Share your data or values, the question the reader needs answered, the reader and where the visual will appear. Ask a specialist directly for a known job, or let the router choose for a broader request.
Here's a CSV and the question our team needs to answer: [question]. Choose and build the clearest chart for a one-page report. Label it for [audience], note any caveats in the data and check the exported result.
Bring: Your data, the reader's question and where it will appear. Expect: A chart with readable labels, caveats and a checked export.
Explore 9 example prompts →Add it to your AI app.
Download the plugin ZIP, then follow the setup for your host. Start a fresh session and try one task.
SHA-256 checksum file for this plugin ZIP.
Uploading a ZIP into an ordinary web chat does not install the plugin.
The methods work with your AI app's own chart and document tools. The included Data Explorer app needs Python 3.12 with its declared dependencies, and showing its widget needs a host that supports MCP Apps. Check the requirements.
Technical details, checksums and historyChoose a skill for your task.
Use Data Visualization for broad requests or chart choice. Ask a specialist directly when you know the job.
Choose and check
Data Visualization
Choose the right visual for a question, data shape and delivery surface.
See this skillStatistical Evidence
Show distributions, estimates, intervals and missing data without distortion.
See this skillVisualization Verification
Test visuals for correctness, regressions, accessibility, interaction and export.
See this skill
Build charts and dashboards
Web Chart Engineering
Build standard or custom browser charts with declarative grammars, D3, TypeScript or React.
See this skillLive Dashboards
Design operational dashboards with update cadence, stale and offline states, and performance limits.
See this skillDense and GPU Rendering
Design dense Canvas, WebGL or 3D visuals when ordinary SVG can't keep up.
See this skillGantt and Schedules
Design or critique Gantt and schedule views with dependencies, baselines and resources.
See this skill
Explain structure, place and story
Structural Diagrams
Make UML, C4, ERD, BPMN, architecture and dependency diagrams that fit the question.
See this skillMaps and Cartography
Choose, build or critique maps where geography changes the answer.
See this skillVisual Stories
Design scrollytelling and staged stories where scrolling carries the evidence.
See this skillInteractive Explanations
Build interactive charts, explorers and simulations in a conversation or as standalone HTML.
See this skill
Publish and export
Automatic guidance: hooks
Version 0.2.5 registers no automatic hooks. You can use the included skills by asking your assistant for the task you want to complete.
Included app and optional sources
This plugin includes one local MCP app, Data Explorer. Some specialist procedures can also use optional provider sources that you configure separately.
Learn to frame a request
Get comfortable explaining what you want an assistant to produce. This beginner course teaches prompting and draft revision through a social-media project.
Learning Studio course: ChatGPT for Beginners: Learning to Prompt →Setup and compatibility
- Your AI host
- Use a host with file tools and the chart, document or web tools your output needs. The methods guide work in those real tools. Read setup details
- Data Explorer runtime
- Python 3.12 with the declared dependencies in a dedicated environment. A host that supports MCP Apps is needed to show its widget. Read setup details
- What's not included
- Proprietary Visualize and unlicensed Scientific source libraries are excluded. Complete MIT web, statistical and export methods are included. Read setup details