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dt-obs-frontends

Real User Monitoring (RUM) on Dynatrace — web, mobile, and hybrid frontends. Core Web Vitals, user sessions, page performance, mobile crashes, frontend errors, and trace correlation. Query via `user.events`, `user.sessions`, and `dt.frontend.*` metrics. Does NOT cover synthetic monitoring (HTTP/browser/network checks) — that's a separate domain.

69

Quality

83%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

85%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured routing skill that efficiently maps RUM workflows to detailed references while keeping the overview lean and navigable. Its main weakness is the absence of any executable DQL example — even one starter query would significantly improve actionability. The data model table, common filters, and performance thresholds are all high-value, token-efficient additions.

Suggestions

Add 1-2 executable DQL starter queries (e.g., a timeseries query for LCP and a fetch user.events query for errors) to make the skill immediately actionable without requiring a reference file lookup.

Consider adding a brief 'first steps' or 'quick start' section showing how to identify the frontend name and verify data is flowing before diving into specific workflows.

DimensionReasoningScore

Conciseness

Every section earns its place — the data model table, common filters, thresholds, and workflow routing are all net-new information Claude wouldn't know. No unnecessary explanations of what RUM is or how DQL works. The 'rule of thumb' line is the only slightly editorial sentence, but it's genuinely useful for decision-making.

3 / 3

Actionability

The skill provides clear routing to workflows and useful filter field names, but contains zero executable DQL queries. A quick-start example query (e.g., fetching LCP from dt.frontend.* or user.events) would make this immediately actionable rather than requiring a reference file lookup first.

2 / 3

Workflow Clarity

The skill functions as a dispatcher: it clearly sequences the decision process (start with metrics for shape, drill into events for why, use sessions for journeys) and maps each workflow to exactly one reference. For a routing/overview skill, this is the appropriate level of workflow clarity — the multi-step details belong in the references.

3 / 3

Progressive Disclosure

Excellent progressive disclosure structure: concise overview with data model, filters, and thresholds inline, then a clean one-level-deep reference table mapping workflows to specific files. The instruction 'Load the reference when you start the workflow, not upfront' is a smart token-saving directive. References are clearly signaled with relative paths.

3 / 3

Total

11

/

12

Passed

Description

82%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong, well-crafted description that excels in specificity, trigger term coverage, and distinctiveness. The explicit exclusion of synthetic monitoring is a smart boundary-setting choice. The main weakness is the lack of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about real user monitoring, frontend performance, Core Web Vitals, user session analysis, mobile app crashes, or Dynatrace RUM data.'

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions and concepts: Core Web Vitals, user sessions, page performance, mobile crashes, frontend errors, trace correlation, and specific query entities like `user.events`, `user.sessions`, `dt.frontend.*` metrics.

3 / 3

Completeness

Clearly answers 'what does this do' with detailed capabilities and even specifies what it does NOT cover. However, there is no explicit 'Use when...' clause or equivalent trigger guidance, which per the rubric caps completeness at 2.

2 / 3

Trigger Term Quality

Excellent coverage of natural terms users would say: 'RUM', 'Real User Monitoring', 'Core Web Vitals', 'user sessions', 'page performance', 'mobile crashes', 'frontend errors', 'Dynatrace', 'web', 'mobile', 'hybrid'. These are terms a user would naturally use when asking about frontend monitoring.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche (RUM on Dynatrace specifically for frontends) and explicitly excludes synthetic monitoring to prevent overlap with a related skill. The specific metric namespaces and domain boundaries make conflicts very unlikely.

3 / 3

Total

11

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
Dynatrace/dynatrace-for-ai
Reviewed

Table of Contents

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