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azure-monitor-opentelemetry-ts

Auto-instrument Node.js applications with distributed tracing, metrics, and logs.

55

Quality

63%

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SecuritybySnyk

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

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

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.

The body is highly actionable, with comprehensive copy-paste-ready code across all major Azure Monitor OpenTelemetry scenarios. Its main weaknesses are a missing verification checkpoint in the workflow and a monolithic single-file structure with no progressive disclosure to separate reference material.

Suggestions

Add a verification step after setup (e.g. 'Generate a request, then confirm traces/metrics appear in Application Insights') to give the workflow an explicit validation checkpoint.

Move bulk reference content (Key Types, Manual Exporter Setup, Custom Span Processor, Custom Logs Ingestion) into separate reference files and link to them from a concise overview to improve progressive disclosure.

Remove the vacuous 'When to Use' placeholder line or replace it with concrete guidance on when this skill applies versus manual OpenTelemetry setup.

DimensionReasoningScore

Conciseness

The body is mostly lean, executable code with headers and almost no concept explanation, but the verbatim repeat of the description under the H1 and the vacuous 'When to Use' placeholder ('This skill is applicable to execute the workflow or actions described in the overview.') are minor padding that keeps it just below a 5.

4 / 5

Actionability

Every section provides complete, copy-paste-ready TypeScript/bash covering installation, quick start, full configuration, custom traces/metrics, manual exporters, log ingestion, span processors, sampling, and shutdown, satisfying the 'fully executable, specific examples cover common cases' anchor.

5 / 5

Workflow Clarity

The Quick Start gives a clear ordering checkpoint (call useAzureMonitor() before importing other modules), but there is no validation or verification step (e.g. confirming telemetry appears in Azure Portal) and the remaining sections are parallel recipes rather than a sequenced workflow, fitting the anchor with a sequence present but checkpoints missing or implicit.

3 / 5

Progressive Disclosure

Section headers organize the content well, but with no bundle files and no references to separate files, large reference material (Key Types, Manual Exporter Setup, Custom Span Processor) is fully inlined in a 300+ line SKILL.md, matching the anchor where structure exists but content that should be separate remains inline.

3 / 5

Total

15

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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 states a clear capability in third person but is missing an explicit 'Use when' trigger clause and the key OpenTelemetry/Azure keywords users would naturally say. It is specific enough to be mostly distinct, yet incomplete as trigger guidance.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers, e.g. 'Use when instrumenting a Node.js app for Azure Monitor / Application Insights or when the user mentions OpenTelemetry, tracing, metrics, or logs.'

Include the keywords 'OpenTelemetry', 'Azure Monitor', and 'Application Insights' so the description matches the natural phrases users actually say.

List a couple more distinct actions (e.g. 'configure exporters', 'ingest custom logs') to lift specificity from a single auto-instrument action to several concrete capabilities.

DimensionReasoningScore

Specificity

Names the domain (Node.js applications) and the three telemetry signals (distributed tracing, metrics, logs) under one concrete action ('Auto-instrument'), matching the anchor that lists a domain with 1-2 concrete actions rather than the several distinct actions needed for a 4.

3 / 5

Completeness

It clearly answers 'what' (auto-instrument Node.js apps with tracing/metrics/logs) but provides no 'Use when...' clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 3.

3 / 5

Trigger Term Quality

Includes relevant natural terms ('Node.js applications', 'distributed tracing', 'metrics', 'logs') but omits the most common synonyms a user would actually say, namely 'OpenTelemetry', 'Azure Monitor', and 'Application Insights', so it stops at 'some relevant keywords but missing common variations'.

3 / 5

Distinctiveness Conflict Risk

The Node.js + distributed-tracing/metrics/logs niche is mostly distinct and would only minorly overlap with closely related general telemetry skills; it is not a 5 because the missing OpenTelemetry/Azure branding leaves slight ambiguity versus other instrumentation skills.

4 / 5

Total

13

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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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