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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).

50

Quality

55%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/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

57%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 content is actionable and well-sectioned with executable Java examples across the main operations, but it is a single monolithic file with a stale version pin and lacks explicit upload-validation checkpoints for its batch operations.

Suggestions

Add an explicit validation step after upload, e.g. querying the target table or checking the response, to form a validate->fix->retry feedback loop for batch log uploads.

Move the pinned Maven version out of the main install snippet (or into a version-agnostic BOM-only path) to avoid time-sensitive staleness penalizing conciseness.

Split the detailed Log Entry Model and Error Handling examples into a referenced file (e.g. EXAMPLES.md) and keep SKILL.md as a lean overview to improve progressive disclosure.

DimensionReasoningScore

Conciseness

The body is mostly lean code with brief section intros and assumes Claude's knowledge of the SDK, but it pins a time-sensitive version ('1.2.11') outside any deprecated section and includes a few padded lead-ins ('Handle partial upload failures gracefully'), so it could be tightened.

3 / 5

Actionability

Concrete, import-included Java examples cover the common cases (sync/async client creation, upload, concurrency, error consumer, async reactor, log-entry model), with only minor gaps such as undefined helper methods (getLargeLogs(), getLogs()) and required placeholders.

4 / 5

Workflow Clarity

A rough sequence is present via section ordering (install, env vars, create client, upload, handle errors), and the error consumer offers partial feedback, but there is no explicit validation checkpoint confirming logs landed in the workspace; per the batch-operation guideline this caps workflow clarity at 3.

3 / 5

Progressive Disclosure

Section headers are clear and external reference links are well signaled, but with no bundle files the ~225-line body is monolithic and inlines content (log-entry model, detailed error handling) that could be split into separate referenced files.

3 / 5

Total

13

/

20

Passed

Description

53%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 clearly conveys what the skill does and carves out a distinct niche, but it omits any 'Use when...' trigger guidance and lacks synonym/variation coverage, which caps completeness and trigger quality at the midpoint.

Suggestions

Append a 'Use when...' clause with concrete triggers, e.g. 'Use when sending custom logs to Azure Monitor via the Logs Ingestion API, or when the user mentions DCR, DCE, or ingesting logs into Log Analytics.'

Add natural synonyms and file/extension cues (e.g., 'ingest logs', 'Log Analytics workspace', '.java') to broaden trigger-term coverage.

Mention the key concrete actions (configure DCE/DCR, upload/batch logs, handle partial failures) so the capability list reads as comprehensive rather than a single action.

DimensionReasoningScore

Specificity

Names the domain ('Azure Monitor Ingestion SDK for Java') and a concrete action ('Send custom logs to Azure Monitor via Data Collection Rules (DCR) and Data Collection Endpoints (DCE)'), but only covers a single action rather than a comprehensive list, matching the 'domain + 1-2 concrete actions' anchor.

3 / 5

Completeness

A clear 'what' is stated ('Send custom logs to Azure Monitor via DCR/DCE') but there is no 'Use when...' clause or equivalent trigger guidance, so completeness is capped at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Relevant domain keywords are present ('Azure Monitor ingestion', 'custom logs', 'DCR', 'DCE', 'Java') that practitioners would say, but common variations and synonyms (e.g., 'log analytics', 'ingest logs', file extensions) are missing.

3 / 5

Distinctiveness Conflict Risk

The scope is a clear niche (Java + Azure Monitor ingestion via DCR/DCE) with minimal conflict risk, though minor overlap is possible with closely related Azure Monitor skills such as the referenced azure-monitor-query skill, keeping it just below 5.

4 / 5

Total

13

/

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

Table of Contents

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