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dembrandt/dembrandt-skills268 installs

data-display-and-selection

Complex data deserves multiple view modes — grid, list, table — chosen by the user based on their task. Row and item selection should use large hit areas (the whole row or card, not just a checkbox). Selected state is communicated through a subtle background colour shift. Mass actions appear when items are selected. Use when designing data tables, product listings, file browsers, or any multi-item collection.

How do I install this agent skill?

npx skills add https://github.com/dembrandt/dembrandt-skills --skill data-display-and-selection
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill provides design guidelines and UI patterns for displaying and selecting data in web applications. It contains no code or instructions that pose a security risk.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

What does this agent skill do?

Data Display and Selection

Complex data collections — products, files, users, orders, tasks — have no single correct view. Different tasks call for different views. Browsing benefits from grid; comparing details benefits from list or table; bulk management benefits from a dense table with mass actions. Give users the choice.


View Modes

Offer multiple views when the data has both visual and detailed dimensions.

ViewBest forWhen to default
GridVisual items: products, images, files, cardsWhen items are visually distinct and browsing is the primary task
ListModerate detail: tasks, emails, articlesWhen a key piece of text or metadata drives selection
TableDense data: orders, reports, user managementWhen multiple columns of data must be compared

View toggle placement: top-right of the collection, adjacent to sort/filter controls. Use icon buttons with tooltips (grid, list, table). Persist the user's choice in localStorage.

[Filter ▾]  [Sort ▾]          [⊞ Grid]  [☰ List]  [⊟ Table]

On mobile, collapse to the view that works best for the content — grid for visual items, list for text. Do not offer a view toggle on small screens unless both views are genuinely usable.


Selection: Prefer Large Hit Areas

Checkboxes are small targets. Requiring users to hit a 16×16px checkbox to select a row is unnecessary friction — especially on touch devices.

Default: the entire row or card is the selection target.

  • Click anywhere on the row → selects the row (background shifts, checkbox checks)
  • The checkbox is a visual indicator of selection state, not the only way to select
  • Keyboard: Space selects the focused row; Shift+click extends selection; Ctrl/Cmd+click toggles individual items
.row {
  cursor: pointer;
  background: var(--color-surface);
  transition: background 100ms ease-out;
}
.row:hover {
  background: var(--color-grey-50);
}
.row.selected {
  background: var(--color-primary-subtle); /* subtle brand tint */
}

For cards in a grid, the entire card is the selection area — not just a checkbox in the corner.


Selected State Visual Language

Selected items communicate their state through a background colour shift — not just a checkbox tick.

Background: --color-primary-subtle — the brand primary colour heavily desaturated and lightened to ~5–8% opacity. Perceptible but not jarring.

Left border accent (optional): A 3px left border in --color-primary reinforces the selected state for list and table rows.

Checkbox: Checked and filled with --color-primary. The checkbox is a secondary signal, not the primary one.

.row.selected {
  background: var(--color-primary-subtle);    /* e.g. hsl(224, 21%, 94%) */
  border-left: 3px solid var(--color-primary);
}

Do not use a high-contrast or saturated background for selection — it competes with content and makes dense tables hard to read.


Mass Actions

When one or more items are selected, mass actions appear. They disappear when nothing is selected.

Placement: A contextual toolbar that appears at the top of the collection (replacing or supplementing the standard toolbar) when selection is active.

[✓ 3 selected]  [Delete]  [Archive]  [Export]  [Move to ▾]  [× Clear]
  • Lead with the selection count: "3 selected" — confirms the scope before any action
  • Show only actions applicable to the selection — if some actions require a single item, disable them for multi-select
  • "Clear" deselects everything and dismisses the toolbar
  • Destructive mass actions (Delete) always trigger a confirm dialog naming the count: "Delete 3 projects? This cannot be undone."

Select all: A checkbox in the table header selects all items on the current page. A secondary action "Select all 247" extends to the full dataset.

[☑ Select all on page]  →  [Select all 247 results]

Sorting and Filtering

Column sorting (table view)

  • Click a column header to sort ascending; click again for descending; third click clears sort
  • Active sort column shows a directional arrow (↑ ↓)
  • Only sortable columns are clickable — non-sortable columns have no hover state on header

Filters

  • Persistent filters belong in a sidebar or filter bar above the collection
  • Active filters should be visible as chips/tags that can be individually removed
  • "Clear all filters" removes all active filters in one action
  • Filter count badge on the filter button when filters are active: Filter (3)

Empty states

  • No results from filter: "No results for these filters. [Clear filters]" — do not show a generic empty state
  • Genuinely empty collection: show a call to action for the first item: "No projects yet. [Create project]"

Search and Autocomplete

Search is how users find one thing in a large set, so it must feel instant and recognisable.

Suggest from the first keystrokes. Start returning results after 1 character, at most 2–3 — don't make the user finish typing or press enter to see anything. Results appear live in a dropdown as they type.

Make a valid result recognisable at a glance. The whole point of a suggestion list is that the user spots their result in a long list without reading every row. Give each result more than a bare string:

  • a thumbnail/image where the item is visual (products, people, files),
  • the category / area it belongs to, and for typed domains (products, spare parts, services) a category icon and colour so the type is legible before the label is read — find good brand-appropriate icons for these result types (see [[brand-visual-language]]),
  • the matched text highlighted within the result.

This is a soft rule — not every search needs images — but the goal is constant: the user should identify the right result out of many, fast (reading is time — see [[ui-density]]).

Give a way out to the full results. The dropdown is a shortcut, not the whole story. Always offer "See all results for '…'", opening a full listing/results page with filters (the collection patterns above) for when the quick suggestions aren't enough.

Fully keyboard-navigable. Arrow keys move through suggestions, Enter selects, Esc closes — and it must all work by mouse too. Search is a power-user path; don't force the hand off the keyboard.


Table-Specific Patterns

Sticky header

Table column headers stick to the top when scrolling vertically — users must always be able to see what each column means.

Sticky first column

For wide tables that scroll horizontally, the first column (row identifier — name, ID) sticks to the left.

Row actions

Per-row actions (Edit, Delete, View) appear on hover in the rightmost column. Do not show them at rest — they add visual noise.

[Name]  [Status]  [Date]  [Amount]          ← at rest
[Name]  [Status]  [Date]  [Amount]  [Edit] [⋯]  ← on hover

Column resize and reorder

For enterprise data tables: allow columns to be resized by dragging the header border, and reordered by dragging the header. Persist the layout.


Making Numbers Comprehensible

A raw number is hard to judge on its own — "1,240 users" or "€48,900" means little without a reference. Presenting data is not just laying out the figures; it is giving them the context and shape that let a user understand them at a glance.

Give a number a reference. A bare value communicates far less than a value with a baseline: a percentage, an average, a delta, or a comparison. "€48,900 (+12% vs last month)", "72% of target", "avg 3.4 per user" — the comparison is usually the insight, not the absolute figure.

Visualise when the story is a pattern. Reach for a graph when the message is a trend, distribution, comparison, or relationship the eye reads faster than a column of digits. A single KPI can pair with a sparkline; a set of categories reads better as a bar chart than a table. A table is for looking up exact values; a chart is for seeing the shape.

Show time-series for anything that evolves. If a value lives and changes over time — revenue, usage, a status history — present its trajectory, not just the current snapshot. A trend line answers "is this getting better or worse?" that a single number never can. Whenever something is time-dependent, consider showing its history alongside its current value.

Choose familiar, widely-understood chart types. Pick the chart most people already know how to read — bar, line, area, pie/donut, sparkline — over an exotic one (sankey, radar, chord, treemap) that looks impressive but forces the user to learn the chart before they can read the data. Novelty in a chart type is a tax on comprehension; spend it only when a common chart genuinely can't tell the story.

Limited, semantic palette. At most 2–3 colours; each means exactly one thing (see [[status-colors-and-errors]]). Traffic-light or a known convention (brand-primary vs grey). Need more distinctions? Add a legend or tooltips — don't add hues. Chart craft (axes, legends, light/dark): dataviz. Pairing a chart with its table: [[coordinated-data-views]].


Review Checklist

  • Is a view mode toggle offered when data has both visual and detail dimensions?
  • Is the user's preferred view persisted across sessions?
  • Is the entire row or card the selection hit area — not just the checkbox?
  • Does selected state use a subtle background colour shift (--color-primary-subtle)?
  • Does a mass action toolbar appear when items are selected, showing the selection count?
  • Do destructive mass actions require a confirm dialog naming the item count?
  • Does "Select all" work per page, with an option to extend to the full dataset?
  • Are active filters visible as removable chips?
  • Does the empty state differ between "no results" and "genuinely empty"?
  • Are per-row actions shown on hover only, not at rest?
  • Is the table header sticky when the table scrolls vertically?
  • Are key numbers given a reference (%, average, delta, comparison) rather than shown bare?
  • Is a graph used where the story is a trend/distribution/comparison, and is time-evolving data shown as a time-series, not just a snapshot?
  • Are chart types familiar and widely understood (bar/line/area/pie/sparkline) rather than exotic ones that must be learned before they can be read?
  • Does a chart/infographic use a small, semantic palette (≤2–3 colours, traffic-light or a known convention), with each colour meaning one thing — and a legend/tooltips where the encoding isn't self-evident?

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

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