Dashboard Data Architecture Validator
Validate dashboard layouts and data hierarchy for optimal user task completion
What You Can Do
You can submit dashboard wireframes, layouts, or requirements to Claude, which analyzes the information hierarchy against user mental models and task workflows. Claude identifies architecture problems—missing context, poor metric grouping, illogical component sequencing—and generates optimized layouts with justified positioning that aligns with how users actually think about data.
Features
Evaluate metric grouping, data relationships, and visual priority against user mental models
Test component layouts against primary user tasks and user research scenarios
Identify broken data flows, missing connections, and illogical component sequencing
Define dashboard behavior across breakpoints and device contexts
Generate layout recommendations with evidence-based reasoning for each placement
Pinpoint structural issues causing users to struggle finding metrics or comparing datasets
Design scalable dashboard patterns that work across different user roles and data domains
Receive detailed reports with before/after layouts and implementation priorities
Example Output
Example 1: E-commerce Dashboard Audit
Input: Wireframe with sales metrics scattered across three sections with unclear grouping
Output:
ARCHITECTURE ISSUES FOUND:
- Sales KPIs (revenue, conversion) grouped far from performance drivers (traffic, AOV)
- Inventory alerts buried below fold; operations team checks this first
- Date range selector unclear—three separate filter controls instead of unified one
OPTIMIZED LAYOUT:
1. Top section: Unified filters + primary metric (revenue) + status cards
2. Middle section: KPI drivers (traffic, AOV, conversion) grouped by relationship
3. Bottom section: Deep-dive tables (orders, inventory) linked to metrics above
Example 2: Healthcare Monitoring Dashboard
Input: Layout with patient vitals, alerts, and historical data—nurses report missing critical changes
Output:
HIERARCHY PROBLEMS:
- Current vitals at bottom; alerts at top creates cognitive load
- Historical trends not adjacent to current values (can't spot anomalies)
- Recommendation: Current vitals top-left (scanning entry point), alerts inline, trends right of vitals
What's Included
- SKILL.md: Complete instruction file with validation framework
- Dashboard Audit Template: Structured checklist for evaluating information hierarchy, task flows, and component relationships
- Information Architecture Checklist: Questions for validating metric grouping, data relationships, and visual priority
- User Task Scenario Matrix: Framework for testing layouts against primary user workflows
- Responsive Architecture Worksheet: Planning guide for dashboard behavior across devices and breakpoints
Who It's For
- UI/UX designers — Architecting dashboards before detailed design and development
- Product managers — Validating dashboard requirements and component priorities align with user needs
- Data engineers and analytics teams — Ensuring data presentation matches how stakeholders consume metrics
- Design systems teams — Creating scalable dashboard patterns and templates for enterprise applications
- Design leads — Auditing existing dashboards to identify usability issues rooted in architecture
Best For
- Designing new dashboards from stakeholder requirements or user research
- Redesigning dashboards with documented usability complaints or task completion issues
- Adding new metrics or visualizations while maintaining information hierarchy
- Creating multi-domain or multi-role dashboard templates
- Validating responsive behavior and cross-device dashboard architecture
- Auditing legacy dashboards before migration to new systems
- Planning component priority and layout sequencing during discovery phase
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