Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Dynatrace/dynatrace-for-ai --skill dt-app-dashboardsgit clone --depth 1 https://github.com/Dynatrace/dynatrace-for-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dynatrace/dynatrace-for-ai/dt-app-dashboards)<a href="https://agentmods.dev/skills/dynatrace/dynatrace-for-ai/dt-app-dashboards"><img src="https://agentmods.dev/badge/skills/dynatrace/dynatrace-for-ai/dt-app-dashboards/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dynatrace/dynatrace-for-ai/dt-app-dashboards"><img src="https://agentmods.dev/badge/skills/dynatrace/dynatrace-for-ai/dt-app-dashboards.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.00911 |
| Opus 5 | $0.00019 | $0.00456 |
| Sonnet 5 | $0.00008 | $0.00182 |
| Haiku 4.5 | $0.00004 | $0.00091 |
Grade A, and why
dt-app-dashboards scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
tilesmust match IDs inlayouts - Grid is 24 units wide. Common widths: 24 (full), 12 (half), 6 (quarter)
- Two tile types:
markdown(text content) anddata(DQL query + visualization)
Optional content properties: settings, refreshRate, annotations
Reading & Analyzing
Fetch full content with dtctl get dashboard <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 queries before adding to dashboard
- No time-range filters in queries unless explicitly requested by user
- Set
namebefore deploying - Updating — ALWAYS download first:
dtctl get dashboard <id> -o json --plain > dashboard.json, modify, then deploy the downloaded file. Never reconstruct JSON from scratch or inject anidmanually — both silently overwrite any 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
- 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
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 88 lines · 38 tokens per session scan A 8001ca0d102b
dt-app-dashboards is a skill published in the GitHub repository Dynatrace/dynatrace-for-ai (137 stars, last pushed 2d ago), licensed Apache-2.0. It adds 38 tokens to every session and 911 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
dtctl
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…
dynatrace-managed
Set up and query Dynatrace Managed (self-hosted) through the Dynatrace Managed MCP server - configuring cluster connections and API tokens, choosing the right environment when several are configured, and building entity selectors for logs, metrics, events, problems, security vulnerabilities and SLOs. Use when the user…
netdata-migration
Use when migrating observability from Datadog, New Relic, Dynatrace, or Prometheus to Netdata. Covers SDK replacement, exporter reconfiguration, Prometheus endpoint passthrough, and dashboard parity expectations.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…