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dt-alerting

End-to-end Dynatrace alerting lifecycle — anomaly detector setup and model selection (static threshold, adaptive baseline, seasonal baseline), alert event storage in Grail, problem grouping and denoising by root cause analysis, and workflow-based notification routing (email, Slack, ServiceNow, webhook). Use when configuring alerting, choosing between detector types, querying alert event history, understanding why alerts merged into a problem, or setting up problem-triggered notifications.

70

Quality

86%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

72%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.

A well-structured, actionable skill body with strong progressive disclosure and concrete DQL examples. The main weakness is workflow clarity: batch detector/notification configuration lacks explicit validation checkpoints, and the consolidation advice is restated a few times.

Suggestions

Add explicit validation checkpoints to destructive/batch flows (e.g. after creating a combined detector, verify it fires once via a short fetch dt.davis.events window before wiring the workflow; after editing a notification filter, confirm the workflow still matches) so workflow clarity can exceed 3.

De-duplicate the 'combine into one detector + one workflow' guidance: state it once in Agent Instructions or Best Practices and reference it from the other, rather than restating it in the example block and Best Practice #7.

Inline the minimal detector-creation payload (the Settings 2.0 schema snippet or a minimal config object) alongside the DQL example so detector setup is copy-paste ready without requiring anomaly-detectors.md.

DimensionReasoningScore

Conciseness

The body is mostly lean — an ASCII lifecycle diagram, compact tables, and tight best-practice bullets — but repeats the consolidation/combine guidance in three places (Agent Instructions, an example block, and Best Practice #7) and re-states alert-source categories twice, adding some redundancy that could be trimmed.

4 / 5

Actionability

Provides copy-paste-ready DQL (fetch dt.davis.events, timeseries with by/filter) and concrete config steps like setting dt.alert_group and filtering workflows via matchesPhrase; minor gaps are that several detector-config steps point to a reference rather than giving the exact Settings v2 payload inline.

4 / 5

Workflow Clarity

The intent-mapping table gives a clear first-step routing and the consolidation guidance is sequenced, but destructive/batch detector and notification changes lack explicit validate-then-proceed checkpoints or feedback loops, which caps workflow clarity at 3 per the rubric's batch-operation guidance.

3 / 5

Progressive Disclosure

SKILL.md is a clear overview with a Knowledge Base Structure table and inline links to three real, one-level-deep references (anomaly-detectors.md, davis-events.md, workflow-notifications.md) plus explicit cross-skill pointers, all of which exist in the bundle and are well-signaled.

5 / 5

Total

16

/

20

Passed

Description

100%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, specific description that concisely covers the full alerting lifecycle and pairs it with an explicit, scenario-rich 'Use when' clause. It distinguishes itself clearly from neighboring Dynatrace skills via concrete trigger phrasing.

DimensionReasoningScore

Specificity

Lists multiple concrete actions spanning the full lifecycle — 'anomaly detector setup and model selection', 'alert event storage in Grail', 'problem grouping and denoising by root cause analysis', and 'workflow-based notification routing' — covering detector, event, problem, and notification stages comprehensively.

5 / 5

Completeness

It explicitly answers both 'what' (the four lifecycle capabilities) and 'when' via an explicit 'Use when ...' clause enumerating concrete triggering scenarios.

5 / 5

Trigger Term Quality

Natural user phrasing is well covered with multiple synonyms and concrete trigger phrases — 'configuring alerting', 'choosing between detector types', 'querying alert event history', 'understanding why alerts merged into a problem', and 'setting up problem-triggered notifications'.

5 / 5

Distinctiveness Conflict Risk

The Dynatrace alerting-lifecycle niche is specific and the trigger phrases (anomaly detector setup, alert event history query, alert-merge investigation, problem-triggered notifications) are clearly distinct from the related dt-obs-problems and dt-platform skills it references.

5 / 5

Total

20

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Dynatrace/dynatrace-for-ai
Reviewed

Table of Contents

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