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dt-obs-log-semantic-mapping

Suggest and validate semantic dictionary (SD) mappings for audit log integrations using raw vendor log payloads or live ingested events. Use when: mapping a vendor audit log feed, authentication logs, user activity logs to the Dynatrace SD; checking required semantic fields; proposing OpenPipeline processor extraction rules based on DQL; running runtime validation (fetches live logs by log.source, then applies static validation).

68

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

75%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.

The body is a well-organized, mostly lean overview that points to real reference files and provides executable snippets plus clear workflow sequencing with validation gates. The main defect is two referenced sample JSON files that are absent from the bundle, slightly undermining navigation.

Suggestions

Add the missing referenced sample files (samples/audit-logs.json, samples/http-logs.json) or remove their References entries so all cited paths resolve.

Consider showing one tiny inline mapped-record example in the body so the reader can sanity-check a mapping without opening a reference.

DimensionReasoningScore

Conciseness

The body is dense and largely efficient, using tables and tight prose to convey a lot without explaining concepts Claude already knows; only minor phrasing could be trimmed.

4 / 5

Actionability

Concrete executable DQL/OpenPipeline snippets (e.g. the parse content / fieldsAdd block) and clear templates, with minor gaps where some guidance is deferred to references rather than shown inline.

4 / 5

Workflow Clarity

Workflows A, B1, and B2 are clearly sequenced with explicit validation checkpoints and a Phase 1 approval gate ("Stop here. Do not produce Phase 2 until the user approves"); minor checkpoint gaps keep it just below a 5.

4 / 5

Progressive Disclosure

Well-structured overview with clearly signaled one-level-deep references to real reference files; however, the body references two sample files (samples/audit-logs.json, samples/http-logs.json) that do not exist in the bundle, a navigation gap that prevents a 5.

4 / 5

Total

16

/

20

Passed

Description

87%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.

The description is strong, clearly stating both what the skill does and when to use it with concrete trigger phrases across multiple workflows. It is largely in third person, though the second-person "Use when:" phrasing is a standard trigger convention rather than a voice violation. Trigger-term coverage is good but slightly technical.

Suggestions

Add a few user-natural synonyms or vendor names alongside the technical phrasing in the trigger clause to broaden keyword reach.

Confirm the description stays third-person voice throughout; the "Use when:" construct is an acceptable trigger convention, but rephrase any remaining second-person framing if present.

DimensionReasoningScore

Specificity

Names several concrete actions ("Suggest and validate semantic dictionary (SD) mappings", "checking required semantic fields", "proposing OpenPipeline processor extraction rules", "running runtime validation") covering the domain comprehensively with only minor gaps.

4 / 5

Completeness

Explicitly answers both what ("Suggest and validate semantic dictionary mappings for audit log integrations") and when ("Use when: mapping a vendor audit log feed..." with concrete trigger phrases), matching the top anchor.

5 / 5

Trigger Term Quality

Good natural keyword coverage ("audit log feed", "authentication logs", "user activity logs", "mapping", "validation") and a concrete "Use when" list, though it leans slightly technical and omits common synonyms a user might say.

4 / 5

Distinctiveness Conflict Risk

Clear niche (Dynatrace semantic dictionary + audit log mapping) with distinct, specific triggers and minimal realistic overlap with other skills.

5 / 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
Reviewed

Table of Contents

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