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dt-obs-services

Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go. Use when analyzing service health, SLA compliance, or runtime issues. Trigger: "service response time", "error rate", "throughput", "SLA compliance", "service mesh overhead", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines", "service performance", "p95 latency", "request failures", "database response time by name". Do NOT use for explaining existing queries, product documentation questions, infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing).

Quality

87%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

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

Highly actionable content with executable DQL examples, sensible defaults, and exemplary one-level-deep progressive disclosure across seven reference files. The main weakness is redundancy — the request-to-capability mapping appears three times in different forms, inflating token cost without adding guidance.

Suggestions

Collapse the triple-stated use-case mapping (per-capability 'Use Cases' bullets, 'When to Use This Skill', and the 'Understanding User Intent' table) into a single intent-mapping table.

Trim the runtime feature bullet lists (e.g., Java's 'Memory: heap, pools, metaspace') since each reference file already covers its runtime; keep only the link and a one-line scope note.

Add an explicit validation checkpoint to the workflows (e.g., after SLA calculation: verify total > 0 before computing percentages to avoid divide-by-zero noise).

DimensionReasoningScore

Conciseness

The same use-case mapping is stated three times: each capability's "Use Cases" bullets, the "When to Use This Skill" section, and the "Understanding User Intent" table, and the runtime feature bullets (e.g., "Memory: heap, pools, metaspace") preview the reference files. No conceptual padding, but the duplication could be tightened to one mapping. Not 4 because threefold repetition of the same content is more than 'minor instances of over-explanation'.

3 / 5

Actionability

Every capability has a copy-paste-ready DQL example (e.g., the p95/error-rate timeseries and the span-based SLA compliance query), plus a defaults table with concrete values and units ("1000 ms (= 1,000,000 µs)"), named tools (create-dql, static-threshold-analyzer, get-entity-name), and a troubleshooting table with specific fixes like "Use getNodeName(dt.smartscape.service)". Matches the fully-executable anchor.

5 / 5

Workflow Clarity

Four workflows are clearly sequenced (e.g., Service Health Check: RED checks then conditional "If runtime-specific issues suspected → Load runtime-specific reference"), and the Troubleshooting table provides error-recovery guidance for concrete failure modes. Not 5 because workflow steps reference capabilities rather than embedding explicit validation checkpoints; not 3 because this is read-only analysis (no destructive/batch cap) and the troubleshooting table covers most recovery paths.

4 / 5

Progressive Disclosure

The body is a genuine overview: quick examples inline with "→ For detailed queries: See [references/service-metrics.md]", seven real reference files (all verified present), each capability linking to its file, and a consolidated References section. Verified one level deep — no references file points to further references. Matches the clear-overview anchor exactly.

5 / 5

Total

17

/

20

Passed

Description

91%Weight 40%Scale 1-5

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

A strong description that explicitly covers what, when, and when-not with a comprehensive natural-language trigger list and named sibling-skill disambiguation. The only defect is the contradictory "database response time by name" trigger, which both weakens distinctiveness and misleads activation.

Suggestions

Remove the "database response time by name" trigger — it contradicts the body's 'Don't use for database performance' boundary and invites triggering on database questions that belong to another skill.

Replace generic verbs ('monitoring', 'analyzing') with more distinct concrete actions (e.g., 'calculate SLA compliance', 'compare service mesh vs direct response time', 'detect consumer lag') to strengthen specificity.

DimensionReasoningScore

Specificity

Concrete capabilities are stated: "Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go", plus "analyzing service health, SLA compliance, or runtime issues". Not 5 because the action verbs are all variations of monitor/analyze rather than multiple distinct concrete actions; not 3 because the metric framework and six named runtimes give comprehensive, specific coverage.

4 / 5

Completeness

Explicitly answers both: what ("Service performance monitoring with RED metrics... runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go") and when ("Use when analyzing service health, SLA compliance, or runtime issues" plus a concrete trigger list), and adds when-not guidance. Matches the anchor-5 example structure exactly.

5 / 5

Trigger Term Quality

Sixteen natural trigger phrases users would actually say, including technology-specific synonyms: "service response time", "error rate", "throughput", "p95 latency", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines". Matches the comprehensive-synonyms anchor; below-anchor 4 would require missing common variations, which isn't the case.

5 / 5

Distinctiveness Conflict Risk

Clear niche with explicit disambiguation ("infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing)"). Held at 4 rather than 5 because the trigger "database response time by name" contradicts the skill's own boundary against database performance, inviting wrong-skill triggering on database questions.

4 / 5

Total

18

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Dynatrace/dynatrace-for-ai

Path

skills/dt-obs-services/SKILL.md

Reviewed

Table of Contents

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