Design dashboards and live visualization systems. Use when the user needs monitoring views, streaming charts, coordinated interactions, downsampling, or performance-aware operational visualization.
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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:
real-time streaming and refresh behavior
layout hierarchy and scan-first dashboard composition
interaction patterns and coordinated views
performance and scale
Default Questions
What is the update model?
append-only stream
periodic polling
event bursts
full snapshot replacement
What latency matters?
sub-second monitoring
near-real-time operational review
asynchronous reporting
What must the user do?
notice anomalies
compare current versus historical
inspect causes
filter and drill down
What are the hard limits?
frame budget
memory budget
network budget
exportability
mobile bandwidth, battery, and thermal budget
How many visualization instances can be visible at once?
single focal chart
a few coordinated panels
many repeated tiles or sparklines
What mobile state must work under interruption?
spotty or offline connection
app backgrounding or tab visibility changes
one-handed use
alert acknowledgment
on-screen keyboard for filters or notes
Real-Time Design Rules
Show time windows clearly.
Distinguish live data from historical context.
Handle missing, late, and out-of-order events explicitly.
Keep the last known good visualization visible during reconnects, with stale, delayed, partial, offline, and error states distinct from normal live data.
Show last updated time and update cadence near the evidence.
Use aggregation, downsampling, or rollups before raw point dumping.
Provide alert thresholds, annotations, and state transitions, not just moving lines.
Use vibration, system notifications, or push-style alerts only for user-requested and meaningful state changes; always provide an in-app visual and accessible alert path.
Keep the most important metric stable in position and encoding.
Keep keys with their charts: direct labels or chart-adjacent keys beat a shared legend parked elsewhere on the screen.
Use sparklines and other microcharts when compact trend context helps scanning, but rely on nearby labels and values to carry meaning.
Design dashboards around situation awareness, not around maximum tile count.
Prefer self-explanatory panels and concise labels over instructional paragraphs scattered across the UI.
Layout and Scanning Defaults
Give the screen a clear focal path: current state first, then supporting context, then controls and secondary diagnostics.
Avoid grids where every tile has equal visual weight unless the user truly needs uniform scanning across peers.
Keep filters and toggles near the views they change instead of collecting everything in a distant control rail.
Reserve callouts and narrative copy for anomalies, caveats, or actions. The normal state should be legible without tutorial text.
Collapse or defer low-value controls so the live state stays visually dominant.
On mobile, do not stack the filter rail or diagnostic controls before the live state. Use bottom sheets, drawers, tabs, or inline controls that return the user to the affected visualization after Apply, Cancel, Reset, or close.
Use mobile landscape for monitoring views when a wide timeline, map, field, route, dense table, or multi-series trace is meaningfully clearer in a handheld wide orientation, but still provide a portrait summary.
Interaction Patterns
overview first, filter or focus, then details on demand
overview plus detail
focus plus context
brush and link
hover for preview, click for commitment
tap/focus for preview, tap again or explicit action for commitment on touch devices
drill-down and drill-through
persistent selections that survive updates
explicit reset and undo paths
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.
Performance Defaults
Budget for 16 ms frames only when truly needed.
Reduce work before optimizing code:
fewer marks
smarter aggregation
smaller repaint regions
lower-frequency updates where appropriate
Choose the renderer intentionally:
SVG for semantics and annotation
Canvas2D for dense 2D raster workloads
WebGL, deck.gl, PixiJS, Sigma.js, or Three.js for GPU-scale marks, maps, particles, graph rendering, or true 3D
Use ring buffers, viewport culling, and multi-resolution summaries for long-running live views.
Separate interaction state from render state so updates remain predictable.
Use particles or glow in dashboards only for active flow, alert state, focus, or recency. Avoid ambient motion that competes with monitoring.
Output Expectations
Describe the update model and failure modes.
Describe mobile reconnect, stale-data, offline/partial-data, and low-bandwidth behavior.
Explain what a user should understand at first scan before touching any controls.
Explain what the mobile user sees first and how the main visualization remains visible around controls and keyboard input.
Define the interaction contract before building widgets.
State how the system degrades when data rate or mark count rises.
Include a technical design section for new work covering simultaneous chart count, per-instance and page-level budgets, and maintenance implications of the chosen rendering strategy.
"Build a real-time operations dashboard from a WebSocket feed."
"Keep this live chart smooth with 100 updates per second."
"Design brushing, cross-filtering, and annotations for this monitoring UI."
"Tell me if this should be a dashboard or a report."
"Critique this monitoring screen using operational dashboard principles."
How to use it
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Take openai/dashboards-and-real-time-visualization from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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