Dt Migration logo

Dt Migration

Organization
Dynatrace
dt-migration

Migrate Dynatrace classic and Gen2 entity-based DQL to Smartscape equivalents. Covers three scenarios. (1) mass data queries filtered by classic entity conditions — migrate to direct dimension filters first, Smartscape only as fallback; (2) mass data queries using entity subqueries for filtering — same dimension-first strategy; (3) pure entity list queries — migrate fetch dt.entity.* to smartscapeNodes. Also handles entityName, entityAttr, classicEntitySelector, and classic relationship patterns.

Overview

PublisherDynatrace
Repositorydynatrace-for-ai
Skill namedt-migration
Stars
156
Forks
30
Bundled files
16
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Dynatrace on GitHub. Read the source before you install it.

Installation

Install the Dt Migration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Dynatrace/dynatrace-for-ai.git /tmp/dynatrace-for-ai
mkdir -p .claude/skills
cp -r /tmp/dynatrace-for-ai/skills/dt-migration .claude/skills/dt-migration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dt Migration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dt Migration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dt Migration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Smartscape Migration Skill

This skill migrates Dynatrace classic and Gen2 entity-based DQL queries and query patterns to Smartscape-based equivalents.

Load the dt-dql-essentials skill before writing final DQL so the translated query also follows current DQL syntax rules.

This skill focuses on Smartscape-oriented DQL migration only. It does not cover asset-level migration workflows.

Query Purpose Classification

Start here. The correct migration strategy depends on what the query is actually trying to do — not just which classic constructs it uses.

There are three distinct situations:

#SituationClassic anti-patternMigration strategy
1Mass data query filtered by entity conditionsclassicEntitySelector(...) inline in filter: of a timeseries, logs, or metrics queryResolve entity conditions to raw data dimensions first. Smartscape is a fallback, not the default.
2Mass data query using entity subquery for filteringfetch dt.entity.* inside in [...], lookup [...], or join [...] to filter the outer mass data querySame dimension-first strategy. Rewrite as raw dimension filter or in [smartscapeNodes ...] subquery.
3Pure entity list queryfetch dt.entity.* used standalone or as the primary result sourcesmartscapeNodes is the only valid path. No raw dimension alternative exists.

Decision:

  • Situations 1 or 2 — load references/mass-data-filtering-strategy.md and complete all steps including field discovery (Step 2) and equivalence verification (Step 4). Do not skip the fieldsSnapshot gates — they determine which approach is viable. Only fall back to the Migration Workflow below when the entity-type mapping or relationship traversal is needed to complete a Smartscape subquery.
  • Situation 3 — continue with the Migration Workflow and entity mapping table below.

Note: Situation 3 has a sub-case where classicEntitySelector is used to filter the entities returned by fetch dt.entity.*. This is rare and follows the same smartscapeNodes path — resolve the selector conditions using references/mass-data-filtering-strategy.md Step 1B, then apply them as node filters in smartscapeNodes.

Migration Workflow

Follow this order for Situation 3 (pure entity list queries) and for constructing Smartscape subqueries in Situations 1 and 2:

  1. Identify the classic input pattern:
    • fetch dt.entity.*
    • classicEntitySelector(...)
    • relationship field access such as belongs_to[...], runs[...], instance_of[...]
    • signal or event queries using dt.entity.*
  2. Identify the involved classic entity types.
  3. Look up the Smartscape replacement in the core entity mapping table below.
  4. Check which classic DQL constructs need explicit migration.
  5. Rewrite the query using Smartscape primitives:
    • smartscapeNodes
    • smartscapeEdges
    • traverse
    • references
    • getNodeName()
    • getNodeField()
  6. Check for special cases, unsupported entities, or ID assumptions.
  7. Load the matching detailed references for the specific entity family or migration pattern.

For the full migration process and output expectations, load references/migration-workflow.md.

Core Entity Mapping Table

Use this compact table first for common migrations. For the full mapping set, load references/type-mappings.md.

Classic / Gen2 entitySmartscape fieldSmartscape node typeNotes
dt.entity.hostdt.smartscape.hostHOSTStandard host mapping
dt.entity.servicedt.smartscape.serviceSERVICEStandard service mapping
dt.entity.process_group_instancedt.smartscape.processPROCESSProcess instance maps directly
dt.entity.container_group_instancedt.smartscape.containerCONTAINERContainer-group instance maps directly
dt.entity.kubernetes_clusterdt.smartscape.k8s_clusterK8S_CLUSTERKubernetes cluster
dt.entity.kubernetes_nodedt.smartscape.k8s_nodeK8S_NODEKubernetes node
dt.entity.kubernetes_servicedt.smartscape.k8s_serviceK8S_SERVICEKubernetes service
dt.entity.cloud_applicationmultiple workload fieldsmultiple K8S workload node typesMaps to multiple workload types; load the cloud-application guide
dt.entity.cloud_application_instancedt.smartscape.k8s_podK8S_PODClassic cloud app instance becomes pod
dt.entity.cloud_application_namespacedt.smartscape.k8s_namespaceK8S_NAMESPACENamespace mapping
dt.entity.applicationdt.smartscape.frontendFRONTENDFrontend application mapping
dt.entity.aws_lambda_functiondt.smartscape.aws.lambda_functionAWS_LAMBDA_FUNCTIONCloud-function entity mapping

DQL Constructs to Inspect During Migration

These classic constructs usually need explicit rewriting:

Classic constructTypical Smartscape replacementNotes
entityName(x)name or getNodeName(x)Prefer name when querying nodes directly
entityAttr(x, "...")direct node field or getNodeField(x, "...")Prefer direct fields when available
classicEntitySelector(...)node filters plus traverseStart from the constrained side; for mass data queries see mass-data-filtering-strategy.md first
dt.entity.* in signal queriesdt.smartscape.*Applies to by, filter, fieldsAdd, expand, and related clauses
belongs_to[...], runs[...], instance_of[...]traverse or references[...]references works only for static edges
classic entity ID filtersSmartscape idDo not reuse classic IDs blindly
affected_entity_ids and affected_entity_typessmartscape.affected_entitiesOne record array replaces the two parallel arrays; each record has id, type, and name

For the detailed function-by-function guide, load references/dql-function-migration.md.

Special Cases

Do not translate these patterns literally:

  • Host group — no standalone Smartscape entity; use fields on HOST
  • Process group — no standalone Smartscape entity; use fields on PROCESS
  • Container group — no standalone Smartscape entity; preserve output shape with placeholders if needed
  • Classic IDs — classic entity IDs do not carry over to Smartscape automatically
  • Planned, missing, or not-planned mappings — check the full mapping table before assuming direct support

Load references/special-cases.md before migrating these patterns.

Entity-Focused Guides

When a migration centers on a specific entity family, load the matching detailed guide:

Each guide explains:

  • what the classic entity represented
  • what the Smartscape replacement is
  • which fields usually change
  • how relationships are migrated
  • common examples and pitfalls

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dt Migration AI skill do?

Migrate Dynatrace classic and Gen2 entity-based DQL to Smartscape equivalents. Covers three scenarios. (1) mass data queries filtered by classic entity conditions — migrate to direct dimension filters first, Smartscape only as fallback; (2) mass data queries using entity subqueries for filtering — same dimension-first strategy; (3) pure entity list queries — migrate fetch dt.entity.* to smartscapeNodes. Also handles entityName, entityAttr, classicEntitySelector, and classic relationship patterns.

Why use Dt Migration on TypingMind?

Because you install it once and use it with any model. Dt Migration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dt Migration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dynatrace/dynatrace-for-ai/tree/main/skills/dt-migration. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dt Migration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dt Migration?

As many as you like. As long as a model supports skills, you can use Dt Migration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dt Migration AI skill free?

Yes. It is published on GitHub by Dynatrace under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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