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azure-monitor-ingestion-java

Azure Monitor Ingestion SDK for Java. Send custom logs to Azure Monitor via Data Collection Rules (DCR) and Data Collection Endpoints (DCE).

56

Quality

65%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/azure-monitor-ingestion-java/SKILL.md

The canonical home for this skill is azure-monitor-ingestion-java in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

65%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 highly actionable with complete executable Java examples across the main operations, but it is a monolithic single file with mild redundancy and no explicit post-upload verification step for a batch operation.

Suggestions

Add an explicit verification checkpoint after upload (e.g., query the ingested rows via azure-monitor-query or check the response) to lift workflow clarity above the batch-operation cap of 3.

Move the per-variant code examples and the log entry model into a bundled reference file (e.g., references/examples.md) and link to it, with only a quick-start snippet inline, to improve progressive disclosure.

Remove the redundant Key Concepts table and the filler 'When to Use' sentence, and replace the pinned version with a note to use the latest release, to tighten conciseness.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete code, but the Key Concepts table re-explains DCE/DCR already stated in Prerequisites, a pinned version (1.2.11) and a {bom_version} placeholder add time-sensitive noise, and the 'When to Use' line is filler; not a 4 because several sections could be trimmed.

3 / 5

Actionability

Provides copy-paste-ready Java for sync/async client creation, basic and concurrent upload, error handling, async Reactor usage, and a log entry model, covering the common cases with executable code.

5 / 5

Workflow Clarity

Steps are implied (install, configure env, create client, upload, handle errors) but there is no explicit verify-after-upload checkpoint, and the rubric caps batch operations without validation at 3.

3 / 5

Progressive Disclosure

Content is a single well-sectioned file with no bundled reference files to defer detail into; structure is present but content that could be split (e.g., per-variant examples, model definition) is inlined, fitting the 3 anchor rather than 4.

3 / 5

Total

14

/

20

Passed

Description

65%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 specific, in third person, and occupies a well-distinguished niche, but it omits an explicit "Use when..." trigger clause, which caps its completeness and leaves trigger guidance implicit.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers, e.g. 'Use when sending custom logs to Azure Monitor, configuring DCR/DCE ingestion, or working with the azure-monitor-ingestion Java SDK.'

Broaden action coverage beyond a single 'send' verb (e.g., mention batching, concurrent upload, or error handling) to lift specificity above 3.

Include natural synonyms or file/dependency cues (e.g., 'Logs Ingestion API', 'azure-monitor-ingestion') to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain (Azure Monitor ingestion for Java) and one concrete action ("Send custom logs to Azure Monitor via Data Collection Rules (DCR) and Data Collection Endpoints (DCE)"), but does not list several distinct actions, matching the 1-2 concrete actions anchor; not a 4 because coverage is not broad.

3 / 5

Completeness

Has a clear "what" but no "Use when..." trigger clause in the description field, and the rubric caps completeness at 3 when explicit trigger guidance is missing.

3 / 5

Trigger Term Quality

Includes natural terms a user would say ("Azure Monitor", "custom logs", "Data Collection Rules", "DCR", "Java") with good keyword coverage; a 5 would require synonyms and file extensions which are absent.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (Azure Monitor Logs Ingestion API for Java via DCR/DCE) with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

15

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

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