dashboard-design
Design dashboards that drive decisions — clear hierarchy, the right metrics, guided exploration, and trustworthy definitions. Use when building executive, operational, or self-serve analytical dashboards.
- License 许可
- MIT
- 最近更新
- 2026-07-22
- Stars
- ★ 7
- Forks
- 1
01 前言 Front Matter
- name
- dashboard-design
- description
- Design dashboards that drive decisions — clear hierarchy, the right metrics, guided exploration, and trustworthy definitions. Use when building executive, operational, or self-serve analytical dashboards.
03 SKILL.md 正文
Dashboard Design
Overview
Dashboards fail when they are data dumps. Good dashboards answer known questions quickly and support safe drill-down without misleading.
When to Use
- Executive and operational dashboards
- Self-serve analytics portals
- Migrating reports from spreadsheets to BI tools
- Redesigning ignored or distrusted dashboards
Core Practices
- Start from decisions and questions, not available fields
- Put the most important metrics first with context (targets, trends)
- Use consistent definitions from the metrics dictionary
- Design hierarchy: summary → drivers → detail
- Limit charts per page; progressive disclosure for complexity
- Test with real users for comprehension time
Principles
- If nothing would change based on the dashboard, cut it
- Distrusted numbers kill adoption permanently until fixed
- Interactivity is not a substitute for structure
- Mobile and print needs sometimes matter — know the audience
Verification
- [ ] Primary questions are answerable in seconds
- [ ] Metrics match agreed definitions
- [ ] Users can explain the main takeaway
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