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-obs-servicesgit 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-obs-services)<a href="https://agentmods.dev/skills/dynatrace/dynatrace-for-ai/dt-obs-services"><img src="https://agentmods.dev/badge/skills/dynatrace/dynatrace-for-ai/dt-obs-services/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-obs-services"><img src="https://agentmods.dev/badge/skills/dynatrace/dynatrace-for-ai/dt-obs-services.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 197 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00173 | $0.03020 |
| Opus 5 | $0.00086 | $0.01510 |
| Sonnet 5 | $0.00035 | $0.00604 |
| Haiku 4.5 | $0.00017 | $0.00302 |
Grade A, and why
dt-obs-services 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 11d 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 — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Application Services Skill
Monitor application service performance, health, and runtime-specific metrics using DQL.
Core Capabilities
1. Service Performance (RED Metrics)
Monitor service Rate, Errors, Duration using metrics-based timeseries queries.
Key Metrics:
dt.service.request.response_time- Response time (microseconds)dt.service.request.count- Request countdt.service.request.failure_count- Failed request count
Common Use Cases:
- Response time monitoring (avg, p50, p95, p99)
- Error rate tracking and spike detection
- Traffic analysis (throughput, peaks, growth)
- Performance degradation detection
- Multi-cluster comparison
Quick Example:
timeseries {
p95 = percentile(dt.service.request.response_time, 95),
total_requests = sum(dt.service.request.count),
failures = sum(dt.service.request.failure_count)
}, by: {dt.service.name}
| fieldsAdd p95_ms = p95[] / 1000, error_rate_pct = (failures[] * 100.0) / total_requests[]
→ For detailed queries: See references/service-metrics.md
2. Advanced Service Analysis
Span-based queries for complex scenarios requiring flexible filtering and custom aggregations.
Use Cases:
- SLA compliance tracking with custom thresholds
- Service health scoring (multi-dimensional)
- Operation/endpoint-level performance analysis
- Custom error classification
- Failure pattern detection with error details
Quick Example:
fetch spans, from: now() - 1h | filter request.is_root_span == true
| fieldsAdd meets_sla = if(request.is_failed == false AND duration < 3s, 1, else: 0)
| summarize total = count(), sla_compliant = sum(meets_sla), by: {dt.service.name}
| fieldsAdd sla_compliance_pct = (sla_compliant * 100.0) / total
→ For detailed queries: See references/service-metrics.md
3. Service Messaging Metrics
Monitor message-based service communication (queues, topics).
Key Metrics:
dt.service.messaging.publish.count- Messages sent to queues or topicsdt.service.messaging.receive.count- Messages received from queues or topicsdt.service.messaging.process.count- Messages successfully processeddt.service.messaging.process.failure_count- Messages that failed processing
What ships with it
7 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.
- 11d ago First seen · 338 lines · 173 tokens per session scan A c37a0b78a2ff
dt-obs-services is a skill published in the GitHub repository Dynatrace/dynatrace-for-ai (137 stars, last pushed today), licensed Apache-2.0. It adds 173 tokens to every session and 3,020 once invoked, about $0.0009 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
compiler-review
Review Rust port code for port fidelity, convention compliance, and error handling. Compares against the original TypeScript source.
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…
extendr-bindings
extendr conventions for exposing a Rust core to R: extendr macros and module registration, Robj type mapping, NA handling, rextendr builds, R package scaffolding, and CRAN compliance. Load when generating or reviewing extendr R bindings for a Rust library.
r-conventions
R code conventions covering R 4.1+, tidyverse/base style, styler/lintr, roxygen2, testthat, error handling, input validation, C/C++/Rust interop, and CRAN compliance. Load when writing or reviewing R code.
python-packaging-license-finder
Use this skill to deterministically find license information for Python packages by checking PyPI metadata first, then falling back to Git repository LICENSE files using shallow cloning.
compliance-check
Compliance pre-flight for a feature, campaign, or initiative — maps the data and activity involved, checks applicable regimes (privacy/GDPR-style, consumer protection, marketing rules, sector-specific), lists required approvals and notices, builds a gap list with remediation owners, and ends in a go/no-go…