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dt-app-dashboards

Generate and validate Dynatrace dashboards from dashboard JSON.

2|1|Updated Apr 15, 2026
Search Tags:#validation#queries#skills#mcp#dashboard#dql#dynatrace
One-click install
npx skills add https://github.com/israel-salgado/dt-mcp-server --skill dt-app-dashboards-israel-salgado
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dt-app-dashboards
Source: https://github.com/israel-salgado/dt-mcp-server/tree/main/.agents/skills/dt-app-dashboards
Command: npx skills add https://github.com/israel-salgado/dt-mcp-server --skill dt-app-dashboards-israel-salgado

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jq, dtctl, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Plan, build, and validate Dynatrace dashboards using a skills-driven workflow with centralized references and assets.

Core Features & Use Cases

  • Skill-based query generation and validation to ensure correct data sources and field names in tile queries.
  • Guided dashboard assembly including tiles, layouts, and variables with built-in validation and deployment checks.
  • Progressive loading of references and assets to guide users without overwhelming context. Real-world example: create an executive dashboard with tiles for uptime, error rate, and latency across critical services.

Quick Start

Create a new dashboard by specifying a title, tiles, and a layout, then validate and deploy.

Frequently Asked Questions about dt-app-dashboards

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

FAQPage Schema
How do I validate DQL queries before deploying a Dynatrace dashboard?▼

To validate DQL queries in Dynatrace dashboards, this Skill applies strict validation scripts to check data sources, field names, and variable definitions. It ensures query correctness and deployment readiness before dashboard JSON is pushed to production.

What is the best way to generate and assemble Dynatrace dashboard layouts and tiles?▼

Generating Dynatrace dashboard layouts is handled through a guided assembly workflow that orchestrates skills and assets to build tiles and variables. It applies built-in validation checks to maintain layout consistency across the dashboard structure.

Do I need jq and dtctl to create production-ready Dynatrace dashboards in MCP environments?▼

Yes, jq and dtctl are required dependencies to execute dashboard creation and deployment workflows in MCP-enabled environments. These tools facilitate JSON processing and control operations needed for strict validation and deployment readiness.

Can I extract structural insights from existing Dynatrace dashboard JSON files?▼

Yes, extracting structural insights from existing Dynatrace dashboard JSON is supported by parsing tile configurations and variable definitions. This workflow validates layout consistency and query correctness to update existing dashboards effectively.

Why does my Dynatrace dashboard deployment fail validation checks?▼

Dashboard deployment validation fails when DQL queries, variable definitions, or layout configurations contain errors. This Skill enforces strict validation rules to ensure data sources and field names are correct before approving the dashboard for production.

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