dynatrace/dynatrace-for-ai

dt-app-dashboards

Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations.

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/dynatrace/dynatrace-for-ai --skill dt-app-dashboards

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

Dynatrace Dashboard Skill

Overview

Dynatrace dashboards are JSON documents stored in the Document Store containing tiles (content/visualizations), layouts (grid positioning), and variables (dynamic query parameters).

When to use: Creating, modifying, querying, or analyzing dashboards.

Dashboard JSON Structure

json
{
  "name": "My Dashboard",
  "type": "dashboard",
  "content": {
    "version": 21,
    "variables": [],
    "tiles": { "<id>": { "type": "data|markdown", ... } },
    "layouts": { "<id>": { "x": 0, "y": 0, "w": 24, "h": 8 } }
  }
}
  • Tile IDs in tiles must match IDs in layouts
  • Grid is 24 units wide. Common widths: 24 (full), 12 (half), 6 (quarter)
  • Two tile types: markdown (text content) and data (DQL query + visualization)

Optional content properties: settings, refreshRate, annotations

Reading & Analyzing

Fetch full content with dtctl get dashboard <id> -o json (describe returns metadata only), then inspect the JSON to discover its available properties. Carefully read references/analyzing.md before analyzing.

Create/Update Workflow (Mandatory Order)

Carefully follow the workflow described in references/create-update.md.

Key rules:

  • Load domain skills BEFORE generating queries — do not invent DQL
  • Validate ALL queries before adding to dashboard
  • No time-range filters in queries unless explicitly requested by user
  • Set name before deploying
  • Updating — ALWAYS read the current state first: dtctl get dashboard <id> -o json, save it as dashboard.json, modify that file, then deploy it. Never reconstruct JSON from scratch or inject an id manually — both silently overwrite any UI edits the user made since last deployment.
  • Deploy with `dtctl apply` — validation runs automatically. If it fails, fix all reported errors before re-applying.

Visualization Types

  • Time-series (require timeseries/makeTimeseries): lineChart, areaChart, barChart, bandChart
  • Categorical (summarize ... by:{field}): categoricalBarChart, pieChart, donutChart
  • Single value/gauge (single numeric record): singleValue, meterBar, gauge
  • Tabular (any data shape): table, raw, recordList
  • Distribution/status: histogram, honeycomb
  • Maps: choroplethMap, dotMap, connectionMap, bubbleMap
  • Matrix: heatmap, scatterplot

Required field types per visualization: references/tiles.md

Variables Quick Reference

json
{ "version": 2, "key": "Service", "type": "query", "visible": true,
  "editable": true, "input": "smartscapeNodes SERVICE | fields name",
  "multiple": false }
  • Single-select: filter service.name == $Service
  • Multi-select: filter in(service.name, array($Service))
  • Types: query (DQL-populated), csv (static list), text (free-form)

Full variable reference: references/variables.md

References

FileWhen to Load
create-update.mdCreating/updating dashboards
tiles.mdTile types, visualization field requirements, settings
variables.mdVariable types, replacement strategies, patterns
analyzing.mdReading dashboards, extracting queries, health assessment

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