kpi-dashboard-design · aj-geddes — Claude Code skill: KPI dashboards
Walks an agent through picking metrics and building a dashboard that shows goal progress. Useful for leadership reporting or process monitoring.
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a claude-codeWhat kpi-dashboard-design does
The skill drives the agent through dashboard design in order: map business goals, select metrics, visualize, then communicate findings to stakeholders. It ships KPI criteria — relevant, measurable, actionable, timely, bounded, simple. Goals get broken into concrete numbers: revenue growth maps to MRR, ARR, CLV and ARPU, customer acquisition to CAC, conversion rate and traffic-to-lead rate.
Most of the material lives in references/: a KPI selection framework, dashboard design, implementation, and monitoring with governance. SKILL.md holds a short Python starter with a KPI selection class and a table linking those guides. The DO and DON'T sections set the boundaries: start from goals rather than data, keep 5–7 core metrics, add context and benchmarks, document metric definitions.
The skill advises capping a dashboard at 5–7 metrics and not changing them often, because teams stop trusting a board that keeps shifting. If your dashboard already has dozens of tiles, that is a reason to check which ones anyone can actually move.
What it helps with
- pick metrics that match a business goal
- build a dashboard for leadership reporting
- set up operational monitoring
- track project progress with measurable indicators
- assign an owner to every metric
Example prompts for the agent
- Design a KPI dashboard for the sales team: start from goals, then pick metrics
- Review my metric list against the skill's criteria and cut the extras
- Lay out a dashboard with leading and lagging indicators plus drill-down
How to install kpi-dashboard-design
1Skills CLI (Vercel)
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a claude-code2Manually: put the files in place
~/.claude/skills/kpi-dashboard-design/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/kpi-dashboard-design/
1Skills CLI (Vercel)
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a codex2Manually: put the files in place
.agents/skills/kpi-dashboard-design/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a cursor2Manually: put the files in place
.cursor/skills/kpi-dashboard-design/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install aj-geddes/useful-ai-prompts kpi-dashboard-design2Manually: put the files in place
.github/skills/kpi-dashboard-design/SKILL.md1Skills CLI (Vercel)
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a gemini-cli2Platform CLI
gemini skills install https://github.com/aj-geddes/useful-ai-prompts --path skills/kpi-dashboard-designManually: put the files in place
.devin/skills/kpi-dashboard-design/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about kpi-dashboard-design
How do I install kpi-dashboard-design in Claude?
Run npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a claude-code. The skill file then lands at ~/.claude/skills/kpi-dashboard-design/SKILL.md.
What does kpi-dashboard-design do?
It guides the agent through KPI selection, dashboard design, implementation and ongoing monitoring. It leans on a references/ directory with four guides.
How many metrics does the skill recommend?
Keep dashboards to 5–7 core metrics, and include both leading and lagging indicators.
Source text
SKILL.md · MIT
---
name: kpi-dashboard-design
description: >
Design and build dashboards that track key performance indicators. Select
relevant metrics, visualize data effectively, and communicate insights to
stakeholders.
---
# KPI Dashboard Design
## Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
## Overview
Effective KPI dashboards make performance visible, enable data-driven decisions, and help teams align around shared goals.
## When to Use
- Creating performance measurement systems
- Leadership reporting and visibility
- Operational monitoring
- Project progress tracking
- Team performance management
- Customer health monitoring
- Financial reporting
## Quick Start
Minimal working example:
```python
# Select relevant, measurable KPIs
class KPISelection:
KPI_CRITERIA = {
'Relevant': 'Directly aligned with business strategy',
'Measurable': 'Can be quantified and tracked',
'Actionable': 'Team can influence the metric',
'Timely': 'Measured frequently (daily/weekly)',
'Bounded': 'Has clear target/threshold',
'Simple': 'Easy to understand'
}
def identify_business_goals(self):
"""Map goals to KPIs"""
return {
'Revenue Growth': [
'Monthly Recurring Revenue (MRR)',
'Annual Recurring Revenue (ARR)',
'Customer Lifetime Value (CLV)',
'Average Revenue Per User (ARPU)'
],
'Customer Acquisition': [
'Customer Acquisition Cost (CAC)',
'Conversion Rate',
'Traffic to Lead Rate',
// ... (see reference guides for full implementation)
```
## Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents |
|---|---|
| [KPI Selection Framework](references/kpi-selection-framework.md) | KPI Selection Framework |
| [Dashboard Design](references/dashboard-design.md) | Dashboard Design |
| [Dashboard Implementation](references/dashboard-implementation.md) | Dashboard Implementation |
| [KPI Monitoring & Governance](references/kpi-monitoring-governance.md) | KPI Monitoring & Governance |
## Best Practices
### ✅ DO
- Start with business goals, not data
- Limit dashboards to 5-7 core metrics
- Include both leading and lagging indicators
- Assign clear metric ownership
- Update dashboards regularly
- Make drill-down available
- Use visual hierarchy effectively
- Test with actual users
- Include context and benchmarks
- Document metric definitions
### ❌ DON'T
- Create dashboards without clear purpose
- Include too many metrics (analysis paralysis)
- Forget about data quality
- Build without stakeholder input
- Use confusing visualizations
- Leave dashboards stale
- Ignore mobile viewing experience
- Skip training on dashboard usage
- Create metrics no one can influence
- Change metrics frequently
© aj-geddes · MIT · aj-geddes/useful-ai-prompts
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