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Grok Bot+18 agentsDashboard UX Auditor
Audit dashboard interfaces to identify hierarchy issues, reduce cognitive load, and prioritize actionable UX fixes.
$8.99
Dashboard UX Auditor
Example session with this skill installed
Audit this admin dashboard description: It has 12 KPI cards at the top, a sidebar with 15 nested items, and a central table with 20 columns. Users say they can't find the 'Export' button.
- Read your context and instructions
- Compiled the dashboard ux auditor
I have completed the UX audit of your admin dashboard. The primary friction points are extreme information density in the data table and a fragmented navigation structure that exceeds typical cognitive limits.
Dashboard UX Audit
1. Executive Summary
- Top Strength: High data density allows power users to see many records at once.
- Top Problem: KPI overload (12 cards) creates a "wall of numbers" without clear hierarchy or status indicators.
- Highest Priority: Consolidate navigation and implement progressive disclosure for the table columns.
2. Prioritized UX Backlog
| Priority | Issue | Impact | Effort | Recommended Change |
|---|---|---|---|---|
| Critical | Hidden Export Action | Task Failure | Low | Move 'Export' from the bottom of the 20-column table to a fixed top-right utility bar. |
| High | Navigation Fatigue | Discovery | Medium | Group the 15 sidebar items into 4-5 logical categories with collapsible sections. |
| Medium | KPI Dilution | Comprehension | Low | Reduce top-level cards to the 4 most critical metrics; move others to a 'Details' view. |
| Medium | Horizontal Scrolling | Efficiency | Medium | Set default visibility for only the 8 most essential columns; add a column picker. |
3. Redesigned Layout Recommendation
- Global Sidebar: 4 categorized groups (e.g., Operations, Finance, User Management, Settings).
- Utility Header: Search, Notifications, and Primary Actions (Export, Add New).
- KPI Ribbon: 4 High-impact cards with sparklines and % change vs. previous period.
- Primary View: Data table with 8 default columns, sticky headers, and inline row actions.
- Secondary Details: Slide-out panel for viewing the full 20-column data set without losing context.
Next steps
- Interview 3 users to identify which 4 KPIs are truly "must-see" on login.
- Implement the column picker to allow users to customize their table view.
- Relocate the Export button to the global utility header for immediate visibility.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Dashboards often suffer from high cognitive load, buried KPIs, and cluttered layouts that prevent users from making fast, data-driven decisions. Developers frequently build for data availability rather than user intent, leading to friction and low adoption.
What it does
- Identifies information hierarchy failures and visual noise that distract users from primary goals.
- Audits KPI visibility to ensure critical metrics have the necessary context, trends, and status indicators.
- Evaluates navigation, filter discoverability, and action placement to streamline user workflows.
- Prioritizes UX debt into a backlog categorized by severity, impact, and implementation effort.
- Provides a redesigned layout hierarchy optimized for scanability and decision-making.
Why this beats prompting it yourself
General LLMs often provide vague aesthetic advice or generic design principles. This skill applies a specific audit framework tailored for SaaS and internal tools, focusing on functional hierarchy and cognitive load rather than just visual trends. It delivers a structured, developer-ready backlog that balances user impact against engineering effort.
Use cases
- Reviewing a new SaaS analytics panel before moving from mockup to frontend development.
- Identifying why users are struggling to find specific reports or filters in a legacy admin console.
- Optimizing mobile responsiveness for operations dashboards used in the field.
- Refactoring high-density data tables to improve readability and actionability.
Known limitations
Cannot guarantee full accessibility compliance from images alone. Requires clearly labeled assumptions if user behavioral data or business goals are not provided.
Cannot guarantee full accessibility compliance from images alone. Requires clearly labeled assumptions if user behavioral data or business goals are not provided.
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