Grafana Dashboards
Grafana Dashboards is an data AI skill with a core value of Create and manage production Grafana dashboards for real-time visualization of system and application metrics. It
helps developers solve real-world problems in the data domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational ...
Quick Facts
mkdir -p ./skills/grafana-dashboards && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/grafana-dashboards/SKILL.md -o ./skills/grafana-dashboards/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Grafana Dashboards
Create and manage production-ready Grafana dashboards for comprehensive system observability.
Do not use this skill when
- The task is unrelated to grafana dashboards
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.
Purpose
Design effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.
Use this skill when
- Visualize Prometheus metrics
- Create custom dashboards
- Implement SLO dashboards
- Monitor infrastructure
- Track business KPIs
Dashboard Design Principles
1. Hierarchy of Information
┌─────────────────────────────────────┐
│ Critical Metrics (Big Numbers) │
├─────────────────────────────────────┤
│ Key Trends (Time Series) │
├─────────────────────────────────────┤
│ Detailed Metrics (Tables/Heatmaps) │
└─────────────────────────────────────┘2. RED Method (Services)
- **Rate** - Requests per second
- **Errors** - Error rate
- **Duration** - Latency/response time
3. USE Method (Resources)
- **Utilization** - % time resource is busy
- **Saturation** - Queue length/wait time
- **Errors** - Error count
Dashboard Structure
API Monitoring Dashboard
{
"dashboard": {
"title": "API Monitoring",
"tags": ["api", "production"],
"timezone": "browser",
"refresh": "30s",
"panels": [
{
"title": "Request Rate",
"type": "graph",
"targets": [
{
"expr": "sum(rate(http_requests_total[5m])) by (service)",
"legendFormat": "{{service}}"
}
],
"gridPos": {"x": 0, "y": 0, "w": 12, "h": 8}
},
{
"title": "Error Rate %",
"type": "graph",
"targets": [
{
"expr": "(sum(rate(http_requests_total{status=~\"5..\"}[5m])) / sum(rate(http_requests_total[5m]))) * 100",
"legendFormat": "Error Rate"
}
],
"alert": {
"conditions": [
{
"evaluator": {"params": [5], "type": "gt"},
"operator": {"type": "and"},
"query": {"params": ["A", "5m", "now"]},
"type": "query"
}
]
},
"gridPos": {"x": 12, "y": 0, "w": 12, "h": 8}
},
{
"title": "P95 Latency",
"type": "graph",
"targets": [
{
"expr": "histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))",
"legendFormat": "{{service}}"
}
],
"gridPos": {"x": 0, "y": 8, "w": 24, "h": 8}
}
]
}
}**Reference:** See `assets/api-dashboard.json`
Panel Types
1. Stat Panel (Single Value)
{
"type": "stat",
"title": "Total Requests",
"targets": [{
"expr": "sum(http_requests_total)"
}],
"options": {
"reduceOptions": {
"values": false,
"calcs": ["lastNotNull"]
},
"orientation": "auto",
"textMode": "auto",
"colorMode": "value"
},
"fieldConfig": {
"defaults": {
"thresholds": {
"mode": "absolute",
"steps": [
{"value": 0, "color": "green"},
{"value": 80, "color": "yellow"},
{"value": 90, "color": "red"}
]
}
}
}
}2. Time Series Graph
{
"type": "graph",
"title": "CPU Usage",
"targets": [{
"expr": "100 - (avg by (instance) (rate(node_cpu_seconds_total{mode=\"idle\"}[5m])) * 100)"
}],
"yaxes": [
{"format": "percent", "max": 100, "min": 0},
{"format": "short"}
]
}3. Table Panel
{
"type": "table",
"title": "Service Status",
"targets": [{
"expr": "up",
"format": "table",
"instant":🎯 Best For
- UI designers
- Product designers
- Claude users
- Data professionals
- Analytics teams
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Data pipeline auditing
- Query optimization
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Grafana Dashboards to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
How do I install Grafana Dashboards?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/grafana-dashboards/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.