agentleFS
oleg494oleg494/coding-kit/skills/dashboard-design/SKILL.md

dashboard-design

Skill3 starsChanged 11 days agoMITView on GitHub

Use when designing, redesigning or reviewing marketplace, seller, operations, finance, logistics or analytics dashboards: information hierarchy, KPI and metric semantics, filters, chart and table choice, honest data visualization, dense layouts, and verifying dashboard states in the running app. Not for product UI, themes, tokens or landing pages (design-system), nor posters or static illustrations.

17 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use data-visualization and motion-design.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • AnthropicSkill

    data-visualization

    Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.

    Also in 4 projects that use this

  • soilmassSkill

    motion-design

    Create animations and motion graphics using industry standards. Use when asked to animate UI elements, create video content, implement transitions, or build motion systems. Implements W3C Design Tokens, Material Design 3 baseline, and Lottie specification compliance.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 16 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Inspect before proposing: Read the existing routes, components, tokens, data shape and current UI.

    line 24
  2. Distinctive:

    Critique before implementing: Remove decoration, redundant labels, cards, charts or animation where they do not improve comprehension or …

    line 62
  3. Distinctive:

    No removal quota on an interface that is already clear.

    line 64
  4. Distinctive:

    Keep number formats, units, decimal precision and positive/negative conventions consistent.

    line 82
  5. Distinctive:

    No gradients, glass effects, excessive pills, emoji icons or uniform rounded cards as decoration.

    line 87
  6. Distinctive:

    Do not turn every metric into a chart.

    line 89
  7. Distinctive:

    Write a short decision list: primary user and decision.

    line 98

“Common” is measured: kept by at least 6 in 10 of the 16 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Dashboard Design

A dashboard is a decision tool, not a collection of cards. Make data easier to decide from, and verify the states that matter in the running app before calling it done.

Use when

  • Redesigning a marketplace, seller or back-office dashboard
  • Reworking KPI cards, charts, filters, tables, navigation or detail panels
  • Choosing a chart or table form for KPIs, trends, rankings or funnels
  • Verifying a changed dashboard in the running app before calling it done

Workflow

  1. Inspect before proposing. Read the existing routes, components, tokens, data shape and current UI. For every metric find its source definition, unit, aggregation, scope, time zone, freshness and comparison period. Never infer business meaning from a label or fabricate sample values.
  2. Name the primary decision. State who uses the dashboard, what they must decide, and the three to five questions the screen answers. If a visual supports no decision or comparison, a clear value, status or table beats a chart. Remove what serves none of those questions.
  3. Set information hierarchy. Primary status and action first, then KPI context, trend or comparison, details, secondary actions. Keep filters and the active period visible. Use a table when exact values or row-level actions matter.
  4. Choose the least complex visual form. Value for a current KPI, delta for comparison, line for a time series, bars for category comparison or ranking, table for exact values or row actions, funnel only when stages and denominators are defined. Maps, pies, gauges and dual axes only when the data genuinely requires them. Keep title, units, time range, scope, comparison basis and freshness attached; never hide an essential value behind hover.
  5. Use honest scales and accessible encoding. Zero baseline for bars unless a documented exception is clearer; no distorted axes, unexplained smoothing, false precision or truncated labels. Never carry an important difference in color alone — add labels, patterns or direct annotations, and give a text or table alternative for meaningful charts.
  6. Reuse the project's visual system. Color meaning stays stable and the existing chart library and theme are the default; a new visualization dependency needs the case production-first-decisions asks for. Token decisions, component states, responsive breakpoints and accessibility baseline are design-system's; this skill supplies the dashboard-specific questions (metric semantics, density, data states) to answer with it.
  7. Design the data states. Cover loading, no data, insufficient data, error, stale or partial data, permission-limited or disabled actions, long labels and numbers, and values outside the expected range. Each explains the next useful action and keeps the layout stable. Component-level state styling is design-system's.
  8. Reprioritize for small screens. Stack or reorder content before shrinking it; check the primary status and action still come first, long category names and large numbers still fit. Horizontal scrolling is acceptable for genuinely wide data tables, never for the whole page.
  9. Critique before implementing. Remove decoration, redundant labels, cards, charts or animation where they do not improve comprehension or actionability. No removal quota on an interface that is already clear.
  10. Verify in the running app, proportional to the change. Launch the real app (project run instructions; browser/DevTools or Playwright — never a source-only inspection). On dynamic pages wait for observable readiness, not network silence or fixed sleeps: a bounded condition wait on the route or data marker, on the target role/content being visible, or on the loading indicator disappearing, then assert the expected content before reading the DOM, and watch the console and network panel for failed requests. Sample by blast radius: a changed card gets that card's states at the widths it appears in; a changed filter, period control or navigation affects every view it feeds, so check each distinct view it feeds rather than every tab in the product. Exercise the states from step 7 that the change can reach. Record surface, viewport, path/state, observed result and pass|defect, fix confirmed issues and rerun the affected check.

Dashboard defaults

  • Three to six primary KPIs, and only when each supports a real decision.
  • Keep number formats, units, decimal precision and positive/negative conventions consistent; make a negative value's meaning explicit.
  • Status meaning explicit through text and icon, not color alone.
  • Sentence-case labels and action verbs: Export, Filter, View details, Resolve.
  • No gradients, glass effects, excessive pills, emoji icons or uniform rounded cards as decoration.
  • Do not turn every metric into a chart; a number, comparison or table may be the better answer.
  • One clear comparison over many competing series; direct labels when the series count is small; raw values available when decisions depend on exact amounts.
  • Preserve existing product patterns unless there is a documented reason to change them.

Output before coding

Write a short decision list: primary user and decision; retained, moved and removed content; hierarchy and chosen visual forms with the question each answers; token or component changes (or "none, reuse existing"); data states and narrow-width behavior; one risk to check in the running UI. Then implement only that plan. A new or ambiguous flow goes through brainstorming first.

Review checklist

  • each visual answers a named question, with numerator, denominator, unit, period and scope clear where present
  • primary status and next action are visible without hunting
  • active filters, date range, units, comparison period and data freshness are visible whenever such controls exist
  • every meaningful chart has labels plus a non-color-only reading, and its text or table fallback preserves the meaning
  • values are comparable without guessing the scale; the view survives grayscale, zoom and keyboard navigation
  • narrow width keeps the hierarchy and does not overflow the page
  • error and empty states offer a concrete next action
  • the screen is calmer and clearer than before, not merely decorated

References

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.