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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.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add aj-geddes/useful-ai-prompts --skill kpi-dashboard-design -a claude-code
Open on GitHub

What 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-code

2Manually: put the files in place

~/.claude/skills/kpi-dashboard-design/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/kpi-dashboard-design/

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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