skills/dtctl/SKILL.md
Investigate incidents, debug performance issues, analyze logs, and manage observability resources in Dynatrace using the dtctl CLI. Use this skill whenever the user asks about error rates, latency spikes, service health, crash-looping pods, web vitals, SLO status, open problems, root cause analysis, log patterns, trace analysis, or building dashboards — even if they don't mention Dynatrace by name. Also covers DQL queries, workflow management, notebook and dashboard creation, settings configuration, and any operations against a Dynatrace environment.
npx skillsauth add dynatrace-oss/dtctl dtctlInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Operate dtctl, the kubectl-style CLI for Dynatrace. This skill teaches core dtctl command patterns and operations.
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:
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.
If dtctl is not installed or not working, see references/troubleshooting.md for installation and setup.
dtctl uses a uniform pattern for all resource types. Discover schema from actual output with dtctl describe <resource> <id> -o json --plain.
| Resource | Aliases | |----------|---------| | analyzer | analyzers | | app | apps | | aws connection | - | | aws monitoring | - | | azure connection | - | | azure monitoring | - | | bucket | bkt | | copilot-skill | copilot-skills | | dashboard | dash | | edgeconnect | ec | | extension | ext, extensions | | extension-config | extcfg, extension-configs | | function | fn, func | | gcp connection | - | | gcp monitoring | - | | group | groups | | intent | intents | | lookup | lookups, lkup | | notebook | nb | | notification | notifications | | sdk-version | sdk-versions | | settings | setting | | settings-schema | schema | | slo | - | | slo-template | slo-templates | | trash | deleted | | user | users | | workflow | wf | | workflow-execution | wfe |
Use IDs whenever possible instead of names to avoid ambiguity.
| Verb | Description | Example |
|------|-------------|---------|
| get | List resources | dtctl get workflows --mine |
| describe | Show resource details | dtctl describe workflow <id> |
| edit | Edit resource interactively | dtctl edit dashboard <id> |
| apply | Create/update from file | dtctl apply -f workflow.yaml --set env=prod |
| delete | Delete resource | dtctl delete workflow <id> |
| exec | Execute workflow/function/analyzer/copilot | dtctl exec workflow <id> |
| query | Run DQL query | dtctl query "fetch logs \| limit 10" |
| logs | Print resource logs | dtctl logs workflow-execution <id> |
| wait | Wait for conditions | dtctl wait query "fetch logs" --for=any |
| history | Show document history | dtctl history dashboard <id> |
| restore | Restore document version | dtctl restore dashboard <id> --version 3 |
| share | Share document | dtctl share dashboard <id> --user [email protected] |
| unshare | Remove sharing | dtctl unshare dashboard <id> --user [email protected] |
| find | Discover resources | dtctl find intents --data trace.id=abc |
| open | Open in browser | dtctl open intent <app/intent> --data key=value |
| diff | Compare resources | dtctl diff -f workflow.yaml |
| verify | Validate without executing | dtctl verify query 'fetch logs' --fail-on-warn |
| commands | List all commands (machine-readable) | dtctl commands --brief -o json |
# 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"]
}
}
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 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.
# 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.
Required workflow for DQL data fetching:
references/DQL-reference.mddtctl 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
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.
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 } }
type: data — DQL tile with query + visualization: singleValue, lineChart, areaChart, barChart, pieChart, table, honeycomb, scatterplottype: markdown — static text via content field (supports markdown)For detailed visualizationSettings (singleValue, charts, tables, thresholds, unit overrides), see references/resources/dashboards.md.
davis.enabled: false on data tiles.makeTimeseries for log/span time series; timeseries for metrics.version field warning on create is benign.id field → creates new; with id field → updates existing.Name resolution ambiguity:
dtctl get <resource> -o json --plain | jq -r '.[] | "\(.id) | \(.name)"'Permission denied:
dtctl auth can-i <verb> <resource>dtctl config describe-context $(dtctl config current-context) --plainContext/safety blocks:
dtctl config use-context <name>dtctl --help, dtctl <command> --help--plain for machine/AI consumptionget/describe first--mine flag to filter resources you owntesting
Ship a new dtctl release — bump version, write changelog entries, run tests, commit, tag, push, and write GitHub release notes. Use this skill whenever the user says "release", "ship it", "cut a release", "new version", "bump version", "publish", or asks about the dtctl release process. Also use when the user wants to update CHANGELOG.md for a release or write GitHub release notes.
tools
Use when work should span one or more detached tasks but still behave like one job with a single owner context. TaskFlow is the durable flow substrate under authoring layers like Lobster, ACPX, plugins, or plain code. Keep conditional logic in the caller; use TaskFlow for flow identity, child-task linkage, waiting state, revision-checked mutations, and user-facing emergence.
tools
# Lobster Lobster executes multi-step workflows with approval checkpoints. Use it when: - User wants a repeatable automation (triage, monitor, sync) - Actions need human approval before executing (send, post, delete) - Multiple tool calls should run as one deterministic operation ## When to use Lobster | User intent | Use Lobster? | | ------------------------------------------------------ | --------------------------
tools
# Lobster Lobster executes multi-step workflows with approval checkpoints. Use it when: - User wants a repeatable automation (triage, monitor, sync) - Actions need human approval before executing (send, post, delete) - Multiple tool calls should run as one deterministic operation ## When to use Lobster | User intent | Use Lobster? | | ------------------------------------------------------ | --------------------------