Coordinated Data Views logo

Coordinated Data Views

Organization
dembrandt
coordinated-data-views

Show a table and its map, diagram, timeline or chart together, with selection synced both ways. Use when data appears in two representations at once.

Overview

Publisherdembrandt
Repositorydembrandt-skills
Skill namecoordinated-data-views
Stars
169
Forks
21
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dembrandt on GitHub. Read the source before you install it.

Installation

Install the Coordinated Data Views AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dembrandt/dembrandt-skills/tree/main/skills/coordinated-data-views
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dembrandt/dembrandt-skills.git /tmp/dembrandt-skills
mkdir -p .claude/skills
cp -r /tmp/dembrandt-skills/skills/coordinated-data-views .claude/skills/coordinated-data-views
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Coordinated Data Views in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Coordinated Data Views on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Coordinated Data Views is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Coordinated Data Views

Some data has more than one natural representation. A set of locations has both a map and a list. A dependency network has both a diagram and a node table. A dataset has both a chart and a raw table. When both representations are genuinely useful for different tasks, show them simultaneously and keep them synchronized — this is called a coordinated view.

The core rule: any selection or highlight made in one view is immediately reflected in the other.


When to Use Coordinated Views

Use coordinated views when:

  1. The two representations serve different tasks — the table is for finding/scanning; the visual view is for understanding arrangement or relationships
  2. Users will frequently move between the two — not just glance at one occasionally
  3. The dataset is large enough that the visual view alone doesn't identify individual items, and the table alone doesn't communicate how they relate

Do not add a coordinated view purely for visual richness. If users only ever look at the table and ignore the visual view, it adds complexity without benefit.


The Synchronized Selection Model

Selection state is owned by a single shared store, not by either view. Both views read from and write to the same state.

Table row clicked → shared highlight state updated → both views re-render

Visual element clicked → shared highlight state updated → both views re-render

What synchronization covers:

InteractionEffect in tableEffect in visual view
Click rowRow highlightsCorresponding element highlighted
Click visual elementCorresponding row highlighted, scrolled into viewElement highlighted
Hover rowSubtle row highlightSubtle element highlight
Hover visual elementSubtle row highlightSubtle element highlight
Clear selectionRow returns to defaultElement returns to default

Scroll-into-view: When a visual element is clicked, the table must scroll to bring the corresponding row into view. A row that is highlighted but off-screen is useless.


Consistent Colour Coding

Colour meaning must be identical in both views. If a category is orange in the table badge, it is orange in the visual view. Never use different colour assignments for the same data in different representations.

Define colours centrally:

ts
const CATEGORY_COLORS = {
  groupA: 'hsl(24, 80%, 55%)',
  groupB: 'hsl(210, 70%, 55%)',
} as const;

Both renderers import from the same source. A shared legend appears once in the layout, not in each view.

Colour encodes state, the label encodes identity. When every item already shows its own name, give all items of one kind the same colour and spend colour on state alone: planned, partly used, free, unavailable. Tints of one hue read as magnitude, not as different things, and a grey item collides with the grey that means empty. Show that one item recurs by highlighting all its occurrences on hover or selection. The legend then explains states and never lists items, because the labels already do.


Layout

The split between views depends on which is primary:

Table-primary (exploration, data management): Table takes 60–70% of the width; visual view is a companion panel on the right or bottom.

Visual-primary (understanding arrangement and relationships): Visual view takes 60–70%; table is a supporting panel.

Equal weight: A 50/50 split with a draggable divider. Persist the user's preferred split.

┌─────────────────────┬────────────────┐
│                     │                │
│   Table (primary)   │  Visual view   │
│                     │                │
└─────────────────────┴────────────────┘

On mobile, show one view at a time with a tab or toggle to switch. Do not attempt to show both on a small screen.

Timelines and Calendar Grids

Place every mark on a time axis by the time it covers, never by a count of units. When units per day vary, give each day the same width and divide the day among the units it actually has, so a mark that ends with the day's last unit ends on the day seam. A width derived from a share of the unit count drifts as soon as days hold different numbers, and the bar then contradicts the grid beside it, so the reader trusts neither.

Build a calendar or matrix from one unit, a square cell plus one gap, and put every row on that pitch, labels included. When the window changes, change how many columns show, not the size of the cell. Keep the grid packed against its row labels and leave the spare width at the far end; a flexible label column on a wide screen pushes the grid away from what it names.


Visual View Controls

Controls that affect only the visual representation belong in the visual view panel, not in the table area.

Common visual-specific controls:

  • Zoom / pan — navigation (usually handled by the rendering library)
  • Layer opacity — reveal overlapping regions on a dense map or diagram
  • Layer toggle — show/hide categories or types
  • Reset view — fit all elements into view; extent reset for maps

These controls do not affect the table. Do not put them in the table toolbar.

Controls that affect the shared data (filters, time range, category selection) belong outside both views, above or beside the layout, since they affect what appears in both.


Highlighting vs. Selection

These are distinct states:

Highlight (hover): Transient, shown while the pointer is over an element. Does not persist. Both views show a subtle version (e.g. 50% opacity overlay, or a faint row background). No interaction required to clear it — moving the pointer clears it.

Selection (click): Persistent until explicitly cleared. Both views show a strong, unambiguous visual (e.g. bright border, saturated colour, selected row background). Cleared by clicking elsewhere or pressing Escape.

Do not conflate these. A hover highlight that persists after the pointer leaves is confusing.


Analysis Beside the Data

A panel that explains or summarises the data on screen is a coordinated view, not a dialog. Open it beside the table, non-modal, page still scrollable. The user checks each claim against the rows it came from. A modal hides exactly those rows.


Performance Considerations

Coordinated views can trigger expensive re-renders if not carefully managed.

  • Debounce hover highlights — do not update on every pointer-move event, only when the target element changes
  • Use stable identity for items (a consistent ID) so React (or equivalent) can reconcile without re-creating elements
  • For large datasets (1000+ items), virtualize the table regardless of the visual view
  • For canvas- or WebGL-rendered views, avoid re-creating elements on each highlight — update style properties on the existing ones instead

Review Checklist

  • Is selection state shared between views via a single store — not duplicated?
  • Does clicking a row highlight the corresponding visual element, and vice versa?
  • Does clicking a visual element scroll the table to the corresponding row?
  • Are colour assignments identical in both views, defined from a single source?
  • Is the shared legend shown once, not duplicated per view?
  • Are visual-specific controls (zoom, transparency, layer toggle) in the visual panel, not the table?
  • Does any analysis or summary panel sit beside the data, non-modal, with the page still scrollable?
  • Are hover highlight and click selection visually distinct states?
  • On mobile, is there a clear way to switch between views?
  • Are hover events debounced to avoid unnecessary re-renders?

Frequently asked questions

What does the Coordinated Data Views AI skill do?

Show a table and its map, diagram, timeline or chart together, with selection synced both ways. Use when data appears in two representations at once.

Why use Coordinated Data Views on TypingMind?

Because you install it once and use it with any model. Coordinated Data Views is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Coordinated Data Views in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dembrandt/dembrandt-skills/tree/main/skills/coordinated-data-views. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Coordinated Data Views?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Coordinated Data Views?

As many as you like. As long as a model supports skills, you can use Coordinated Data Views with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Coordinated Data Views AI skill free?

Yes. It is published on GitHub by dembrandt under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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