grafana-dashboards
Helps your agent create and manage Grafana dashboards for comprehensive system monitoring.
What it does
This tool helps create and manage visual dashboards to monitor systems. It transforms complex data into easy-to-understand charts and tables.
When to use it
- ✓When you need to see an application's performance.
- ✓To monitor resource usage like CPU and memory.
- ✓To track important business metrics.
Example of what to ask your AI
“Create a dashboard to monitor our API's error rate and latency.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You describe what information you want to see and how it should be presented (charts, numbers, etc.). The tool uses this information to generate the necessary code for the dashboard.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill grafana-dashboardsOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/grafana-dashboards/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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 inline example
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": true
}],
"transformations": [
{
"id": "organize",
"options": {
"excludeByName": {"Time": true},
"indexByName": {},
"renameByName": {
"instance": "Instance",
"job": "Service",
"Value": "Status"
}
}
}
]
}
4. Heatmap
{
"type": "heatmap",
"title": "Latency Heatmap",
"targets": [{
"expr": "sum(rate(http_request_duration_seconds_bucket[5m])) by (le)",
…
FAQ
What are 'dashboards'?
They are visual panels that display important system information in an organized way, using charts, numbers, and tables.
What are metrics?
They are data collected about a system's performance and operation, such as access counts or CPU usage.
What is observability?
It's the ability to understand what's happening inside a complex system by observing its output data.
Details
Original description by the author
Create and manage production-ready Grafana dashboards for comprehensive system observability.
Popularity
- GitHub stars
- 48k
- Ranking position
- #3167
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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