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Design & UX

Dashboard Designer

Design dashboards that show the right metrics to the right audience with clear hierarchy and actionable layout.

# Drop into ~/.claude/skills/dashboard-designer/
curl -L https://github.com/sunnyyang-hicks/pm-skills-for-claude/raw/main/dashboard-designer/SKILL.md \
  -o ~/.claude/skills/dashboard-designer/SKILL.md

Overview

A dashboard isn't a place to dump every metric you have. It's an information radiator that answers a specific set of questions for a specific audience. If the viewer has to think about what they're looking at, the dashboard has failed.

Before You Start

Ask the user:

  1. Who's the audience? — Execs, PMs, engineers, ops, customers. Each needs different views.
  2. What questions should it answer? — 3-5 specific questions, not "show everything."
  3. What decisions does it support? — What will someone DO after looking at it?
  4. Data available — What metrics exist and what needs to be built?
  5. Refresh cadence — Real-time, hourly, daily, weekly.

Design Process

Step 1: Define the Information Hierarchy

Level 1 (Glance — 3 seconds): Am I on track? Is anything on fire? → 3-5 headline metrics with trend indicators (up/down/flat)

Level 2 (Scan — 30 seconds): What's driving the numbers? → Key breakdowns, top-line charts, segment comparisons

Level 3 (Analyze — 5 minutes): Where should I dig deeper? → Detailed tables, drill-down views, time series

Step 2: Layout Design

┌─────────────────────────────────────────────────┐
│  LEVEL 1: Headline Metrics (3-5 KPIs)           │
│  [Metric] [Trend]  [Metric] [Trend]  [Metric]  │
├──────────────────────┬──────────────────────────┤
│  LEVEL 2: Primary    │  LEVEL 2: Secondary      │
│  Chart/Breakdown     │  Chart/Breakdown          │
│                      │                           │
├──────────────────────┴──────────────────────────┤
│  LEVEL 3: Detailed Table / Drill-down            │
│                                                   │
└─────────────────────────────────────────────────┘

Step 3: Metric Selection per Audience

| Audience | Key Questions | Metrics | Cadence | |----------|-------------|---------|---------| | Exec | Are we growing? Are we profitable? | MRR, growth rate, burn | Weekly | | PM | Is the product healthy? What needs attention? | Activation, retention, feature adoption | Daily | | Engineering | Is the system healthy? | Uptime, latency, error rate | Real-time | | Support | What are users struggling with? | Ticket volume, resolution time, top issues | Daily | | Customers | Am I getting value? | Usage, ROI, team activity | On-demand |

Step 4: Visualization Principles

  • Time series for trends (line chart)
  • Bar charts for comparison across categories
  • Single numbers for current state with trend arrows
  • Tables for detailed drill-down data
  • Heatmaps for patterns across two dimensions
  • Never use pie charts for more than 3 segments

Color coding:

  • Green = on track / improving
  • Yellow = watch / declining
  • Red = needs action / below threshold

Step 5: Alert and Threshold Design

Every headline metric needs:

  • Green threshold: [metric] > [value] — all good
  • Yellow threshold: [value] > [metric] > [value] — investigate
  • Red threshold: [metric] < [value] — action required

Output

# Dashboard Design — [Name] for [Audience]

## Purpose
[What questions this dashboard answers]

## Metrics Inventory
| Metric | Definition | Source | Refresh | Threshold (R/Y/G) |
|--------|-----------|--------|---------|-------------------|
| [metric] | [how calculated] | [data source] | [cadence] | [thresholds] |

## Layout Specification
[Wireframe with metric placement and chart types]

## Interaction Design
- [Filters available]
- [Drill-down paths]
- [Date range controls]
- [Export capabilities]

## Technical Requirements
- Data sources: [list]
- Refresh frequency: [cadence]
- Access control: [who sees what]
- Tool recommendation: [Looker/Tableau/Metabase/custom]

Save as DASHBOARD-DESIGN-[name].md.