Agent Skill
2/7/2026

dtctl

Use dtctl CLI tool for querying observability data in Dynatrace via DQL (logs, metrics, traces, ...) and to manage Dynatrace platform resources (workflows, dashboards, notebooks, SLOs, settings, buckets, lookup tables).

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npx skills add dynatrace-oss/dtctl

SKILL.md

Namedtctl
DescriptionUse dtctl CLI tool for querying observability data in Dynatrace via DQL (logs, metrics, traces, ...) and to manage Dynatrace platform resources (workflows, dashboards, notebooks, SLOs, settings, buckets, lookup tables).

name: dtctl description: Manage Dynatrace environments using dtctl - install/update the CLI, configure authentication with OS keyring tokens, and run kubectl-style operations (get/describe/edit/apply/delete/query/exec/commands) for workflows, dashboards, notebooks, DQL, SLOs, settings, buckets, lookups, OpenPipeline, and Davis AI. Use when the user wants to control Dynatrace resources via dtctl.

Dynatrace Control with dtctl

Operate dtctl, the kubectl-style CLI for Dynatrace. This skill teaches core dtctl command patterns and operations.

Recommended Initialization

At the start of a task, run these checks to establish context and permissions:

# Discover all available commands, flags, and resources
dtctl commands --brief -o json

# Show current context
dtctl config current-context

# Show context details
dtctl config describe-context $(dtctl config current-context) --plain

# Show authenticated user
dtctl auth whoami --plain

This displays:

  • Current context name and environment URL
  • Safety level (readonly, readwrite-mine, readwrite-all, dangerously-unrestricted)
  • Authenticated user identity (name, email, UUID)

DQL Reference Usage

Before writing, modifying, or executing any DQL that fetches Dynatrace data (for example via dtctl query, dtctl wait query, or query files), you MUST consult references/DQL-reference.md and follow its documented syntax and templates.

If there is any conflict between memory/assumptions and the reference, prefer the reference.

Prerequisites

If dtctl is not installed or not working, see references/troubleshooting.md for installation and setup.

Resources & Commands

Available Resources

dtctl uses a uniform pattern for all resource types. Discover schema from actual output with dtctl describe <resource> <id> -o json --plain.

ResourceAliases
analyzeranalyzers
appapps
bucketbkt
copilot-skillcopilot-skills
dashboarddash
edgeconnectec
functionfn, func
groupgroups
intentintents
lookuplookups, lkup
notebooknb
notificationnotifications
sdk-versionsdk-versions
settingssetting
settings-schemaschema
slo-
slo-templateslo-templates
trashdeleted
userusers
workflowwf
workflow-executionwfe

Use IDs whenever possible instead of names to avoid ambiguity.

Command Verbs

VerbDescriptionExample
getList resourcesdtctl get workflows --mine
describeShow resource detailsdtctl describe workflow <id>
editEdit resource interactivelydtctl edit dashboard <id>
applyCreate/update from filedtctl apply -f workflow.yaml --set env=prod
deleteDelete resourcedtctl delete workflow <id>
execExecute workflow/function/analyzer/copilotdtctl exec workflow <id>
queryRun DQL querydtctl query "fetch logs | limit 10"
logsPrint resource logsdtctl logs workflow-execution <id>
waitWait for conditionsdtctl wait query "fetch logs" --for=any
historyShow document historydtctl history dashboard <id>
restoreRestore document versiondtctl restore dashboard <id> --version 3
shareShare documentdtctl share dashboard <id> --user email@example.com
unshareRemove sharingdtctl unshare dashboard <id> --user email@example.com
findDiscover resourcesdtctl find intents --data trace.id=abc
openOpen in browserdtctl open intent <app/intent> --data key=value
diffCompare resourcesdtctl diff -f workflow.yaml
verifyValidate without executingdtctl verify query 'fetch logs' --fail-on-warn
commandsList all commands (machine-readable)dtctl commands --brief -o json

Key Concepts for AI Agents

Output Modes

# Agent envelope mode (auto-detected in AI environments)
-A, --agent      # Structured JSON envelope with ok/result/error/context
--no-agent       # Opt out of auto-detected agent mode

# Machine-readable formats (use these for AI agents)
-o json          # JSON output
-o yaml          # YAML output
-o csv           # CSV output
-o chart         # ASCII chart (for time series)
-o sparkline     # ASCII sparkline (for time series)
-o barchart      # ASCII bar chart (for time series)

# Human-readable formats
-o table         # Table format (default)
-o wide          # Wide table with more columns

# Always use --plain flag for AI consumption (implied by --agent)
--plain          # Strips colors and prompts, best for parsing

For AI agents, prefer: dtctl <command> --agent (auto-detected) or dtctl <command> -o json --plain

The --agent envelope provides structured metadata alongside results:

{
  "ok": true,
  "result": [ ... ],
  "context": {
    "verb": "get", "resource": "workflow",
    "total": 5, "has_more": false,
    "suggestions": ["Run 'dtctl describe workflow <id>' for details"]
  }
}

Template Variables

In YAML/DQL files, use Go template syntax:

# workflow.yaml
title: "{{.environment}} Deployment"
owner: "{{.team}}"
trigger:
  schedule:
    cron: "{{.schedule | default "0 0 * * *"}}"
# query.dql
fetch logs
| filter host.name == "{{.host}}"
| filter timestamp > now() - {{.timerange | default "1h"}}

Execute with: dtctl apply -f file.yaml --set environment=prod --set team=platform

Copilot, Functions, Analyzers

# Copilot skills
dtctl get copilot-skills -o json --plain

# Functions
dtctl get functions -o json --plain
dtctl exec function <id-or-name> --payload '{"key":"value"}' --plain

# Analyzers
dtctl get analyzers -o json --plain
dtctl exec analyzer <id-or-name> --input '{"timeframe":"now-2h"}' --plain

Prefer get ... -o json --plain first, then describe/exec with explicit IDs.

Authentication & Permissions

# Check current user and permissions
dtctl auth whoami --plain
dtctl auth can-i create workflows
dtctl auth can-i delete dashboards

Use can-i to verify permissions before attempting operations.

Quick Reference: DQL Queries

Required workflow for DQL data fetching:

  1. First consult references/DQL-reference.md
  2. Build/validate the query using the documented patterns
  3. Execute with dtctl query ... -o json --plain (or dtctl wait query ... when waiting for results)
# Inline query
dtctl query "fetch logs | filter status='ERROR' | limit 100" -o json --plain

# Query from file with variables
dtctl query -f query.dql --set host=h-123 --set timerange=2h -o json --plain

# Wait for query results
dtctl wait query "fetch spans | filter test_id='test-123'" --for=count=1 --timeout 5m

# Query with chart output
dtctl query "timeseries avg(dt.host.cpu.usage)" -o chart --plain

Dashboards

For full examples and field-level gotchas, see references/resources/dashboards.md.

Create/update: dtctl apply -f dashboard.yaml --plain. Export for reference: dtctl get dashboard <id> -o yaml --plain.

YAML skeleton

name: "Dashboard Name"
type: dashboard
content:
  annotations: []
  importedWithCode: false
  settings:
    defaultTimeframe:
      enabled: true
      value: { from: now()-2h, to: now() }
  layouts:
    "1":                    # string key, must match a tile key
      x: 0                 # 24-column grid (full=24, half=12, third=8)
      "y": 0               # MUST quote "y" to avoid YAML boolean parse
      w: 12
      h: 6
  tiles:
    "1":
      title: "Tile Title"
      type: data            # data | markdown
      query: |
        fetch logs | limit 10
      visualization: lineChart
      visualizationSettings:
        autoSelectVisualization: false
      davis: { enabled: false, davisVisualization: { isAvailable: true } }

Tile types & visualizations

  • type: data — DQL tile with query + visualization: singleValue, lineChart, areaChart, barChart, pieChart, table, honeycomb, scatterplot
  • type: markdown — static text via content field (supports markdown)

For detailed visualizationSettings (singleValue, charts, tables, thresholds, unit overrides), see references/resources/dashboards.md.

Gotchas

  • Always set davis.enabled: false on data tiles.
  • Use makeTimeseries for log/span time series; timeseries for metrics.
  • version field warning on create is benign.
  • No id field → creates new; with id field → updates existing.

Common Issues

Name resolution ambiguity:

  • If a name matches multiple resources, dtctl will fail
  • Solution: Use IDs instead of names
  • Find ID: dtctl get <resource> -o json --plain | jq -r '.[] | "\(.id) | \(.name)"'

Permission denied:

Context/safety blocks:

  • Destructive operations may be blocked by safety level
  • Switch context: dtctl config use-context <name>
  • Adjust safety level when creating context

Additional Resources

Safety Reminders

  • Use --plain for machine/AI consumption
  • Confirm context + safety level before destructive ops; prefer get/describe first
  • Use --mine flag to filter resources you own
  • For multi-tenant work, see references/config-management.md
Skills Info
Original Name:dtctlAuthor:dynatrace