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dt-app-dashboards

dt-app-dashboards

github.com/dynatraceData & databases1692.8k installsUpdated today
Repository

About dt-app-dashboards

Dynatrace Dashboard Skill is for people creating, updating, querying, or analyzing Dynatrace dashboards. It documents dashboard JSON, visualizations, and variables, and sets out a workflow that reads existing state before updates.

Key features

  1. 01Dashboard JSON structure
  2. 02Visualization types and requirements
  3. 03Variable types and usage
  4. 04Create and update workflow

Use cases

  1. 01Create dashboards with DQL charts
  2. 02Modify an existing dashboard
  3. 03Inspect dashboard queries and settings
  4. 04Analyze dashboard content

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/dynatrace/dynatrace-for-ai --skill dt-app-dashboards

After installing, type/dt-app-dashboardsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

assets/
ExampleDashboard.json
visualization-settings.reference.jsonc
references/
analyzing.md
create-update.md
tiles.md
variables.md

Details

From the project README

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

{
  "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

{ "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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