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dynatrace/dynatrace-for-ai1.3k installs

dt-app-notebooks

Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON including sections, DQL queries, and visualizations.

How do I install this agent skill?

npx skills add https://github.com/dynatrace/dynatrace-for-ai --skill dt-app-notebooks
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill, developed by Dynatrace, provides a set of tools for managing Dynatrace notebooks, enabling users to create, update, and analyze their structure and content. It utilizes common command-line utilities such as jq for data manipulation. The primary security considerations include a surface for indirect prompt injection when processing notebook data from external sources and the generation of script-based notebook sections, both of which are common for this type of technical tool.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

Dynatrace Notebook Skill

Overview

Dynatrace notebooks are JSON documents stored in the Document Store containing an ordered array of sections — markdown blocks for narrative and dql blocks for DQL queries with visualizations. Sections render top-to-bottom in array order.

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

Notebook JSON Structure

{
  "name": "My Notebook",
  "type": "notebook",
  "content": {
    "version": "7",
    "defaultTimeframe": { "from": "now()-2h", "to": "now()" },
    "sections": [
      { "id": "1", "type": "markdown", "markdown": "# Title" },
      {
        "id": "2", "type": "dql", "title": "Query Section", "showInput": true,
        "state": {
          "input": { "value": "fetch logs | summarize count()" },
          "visualization": "table",
          "visualizationSettings": { "autoSelectVisualization": true, "chartSettings": {} },
          "querySettings": {
            "maxResultRecords": 1000, "defaultScanLimitGbytes": 500,
            "maxResultMegaBytes": 1, "defaultSamplingRatio": 10, "enableSampling": false
          }
        }
      }
    ]
  }
}
  • Sections render in array order.
  • Section types: markdown, dql. (function exists but is rare.)
  • Use string-int IDs ("1", "2", …); UUIDs are also accepted.
  • content.defaultTimeframe sets the default timeframe; each section can override via section.state.input.timeframe. Hardcoded time filters in DQL are allowed.

Optional content properties: defaultSegments.

Reading & Analyzing

Fetch full content with dtctl get notebook <id> -o json --plain (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 section queries before adding to the notebook.
  • Set name before deploying.
  • Prefer autoSelectVisualization: true in visualizationSettings unless the user requested a specific visualization type — when false, state.visualization must be set explicitly.
  • Updating — ALWAYS download first: dtctl get notebook <id> -o json --plain > notebook.json, modify, then deploy the downloaded file. Never reconstruct JSON from scratch or inject an id manually — both silently overwrite UI edits the user made since last deployment.
  • Deploy with dtctl apply — validation runs automatically, and the local file is deleted on success.

Visualization Types

Notebooks support a subset of Dynatrace visualizations:

  • Time-series (require timeseries/makeTimeseries): lineChart, areaChart, barChart, bandChart
  • Categorical (summarize ... by:{field}): categoricalBarChart, pieChart, donutChart
  • Single value / gauge / meter: singleValue, meterBar, gauge
  • Tabular (any data shape): table, raw, recordView
  • Distribution/status: histogram, honeycomb
  • Geographic maps: choropleth, dotMap, connectionMap, bubbleMap
  • Matrix/correlation: heatmap, scatterplot

Required field types per visualization: references/sections.md.

References

FileWhen to Load
create-update.mdCreating/updating notebooks
sections.mdSection types, visualization field requirements, settings
analyzing.mdReading notebooks, extracting queries, purpose identification

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/dynatrace/dynatrace-for-ai/dt-app-notebooks">View dt-app-notebooks on skillZs</a>