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grafana-dashboard

Create and manage Grafana dashboards with SQL-based visualization panels.

1.5k|222|Updated Jul 4, 2025
Search Tags:#metrics#dashboard#sql#visualization#grafana#panels#bi
One-click install
npx skills add https://github.com/Datus-ai/Datus-agent --skill grafana-dashboard-datus-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: grafana-dashboard
Source: https://github.com/Datus-ai/Datus-agent/tree/main/datus/resources/skills/grafana-dashboard
Command: npx skills add https://github.com/Datus-ai/Datus-agent --skill grafana-dashboard-datus-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually building and maintaining Grafana dashboards is time-consuming and prone to layout or query errors for data teams that need to visualize metrics from existing datasources without moving underlying data.

Core Features & Use Cases

  • Automated Dashboard & Panel Creation: Build Grafana dashboards and SQL-based visualization panels directly against pre-existing tables in registered Grafana datasources, with no data movement or transformation required.
  • Enforced Layout Best Practices: Follows proven dashboard reading flows (KPI overview → trends → breakdowns → detail) to create intuitive, business-facing visualizations without manual layout tweaking.
  • Use Case: A data analyst can use this skill to quickly spin up a sales performance dashboard with KPI cards for total revenue, time-series line charts for monthly sales trends, and bar charts for top-performing regions, all querying an existing sales metrics table in their Grafana instance.

Quick Start

Use the grafana-dashboard skill to build a new sales performance dashboard with KPI cards, monthly trend lines, and regional breakdown charts from the existing sales_metrics table.

Frequently Asked Questions about grafana-dashboard

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create Grafana dashboards with SQL visualization panels from existing tables?▼

To create Grafana dashboards, you can automate building SQL-based visualization panels directly against pre-existing tables in registered datasources. This requires no underlying data movement or transformation, allowing you to build scoped, read-only business intelligence visualizations quickly.

Can I build read-only BI dashboards in Grafana without moving or transforming my underlying data?▼

Yes, you can build read-only BI dashboards in Grafana without data movement. The process queries pre-existing tables directly registered in your Grafana datasources, eliminating the need for underlying data transformation while generating business-facing visualizations.

What is the best way to structure Grafana dashboard layouts for business intelligence metrics?▼

The best way to structure Grafana dashboard layouts is to follow proven reading flows: KPI overview, then trends, then breakdowns, and finally detail. This enforced layout best practice ensures intuitive, readable business-facing visualizations without manual tweaking.

Why does my Grafana time series chart require a time column alias when creating panels?▼

Your Grafana time series chart requires a time column alias because of Grafana-specific technical constraints for panel creation. Aliasing the time column is a mandatory requirement to render time series charts properly within your dashboard visualization.

Do I need a mandatory dashboard ID before creating visualization panels in Grafana?▼

Yes, you need a mandatory dashboard ID before creating visualization panels in Grafana. Grafana-specific technical constraints enforce that a dashboard ID must exist first to successfully generate and attach SQL-based visualization panels to your business intelligence dashboards.

What are the limitations of building Grafana panels against pre-existing datasource tables?▼

A limitation of building Grafana panels this way is that it only works against pre-existing tables registered in Grafana datasources. It applies to scoped, read-only business intelligence workflows and does not support underlying data movement or transformation processes.

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