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azure-monitor-opentelemetry-ts

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

52

Quality

57%

Does it follow best practices?

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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

61%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 skill excels at actionability with comprehensive, executable TypeScript examples covering the full Azure Monitor OpenTelemetry surface area. However, it suffers from being a monolithic reference document with no progressive disclosure structure, and lacks validation/verification steps to confirm instrumentation is working correctly. Some content is redundant (Key Types section, placeholder 'When to Use') and the overall length could be reduced by splitting advanced topics into separate files.

Suggestions

Split advanced sections (Manual Exporter Setup, Custom Span Processor, Custom Logs Ingestion, Sampling) into separate reference files and link to them from the main SKILL.md

Add a verification step after setup, e.g., 'Check telemetry is flowing: look for traces in Azure Portal > Application Insights > Transaction search within 5 minutes'

Remove the 'Key Types' section (it's just import statements already shown in examples) and the placeholder 'When to Use' section

Add a brief troubleshooting section covering common silent failures (wrong connection string, missing ESM loader, import ordering issues)

DimensionReasoningScore

Conciseness

The skill is fairly comprehensive but includes some unnecessary sections for Claude (e.g., 'Key Types' is just a list of imports Claude already knows, 'Best Practices' repeats information already stated in the body, and the 'When to Use' section is a meaningless placeholder). The full configuration block and multiple exporter examples add bulk that could be trimmed or moved to separate files.

3 / 5

Actionability

Every section provides fully executable, copy-paste ready TypeScript code with proper imports, concrete configuration examples, and error handling patterns. The code covers common cases (auto-instrumentation, manual exporters, custom traces/metrics/logs) with specific, runnable examples.

5 / 5

Workflow Clarity

The critical ordering constraint ('call useAzureMonitor() BEFORE importing other modules') is clearly highlighted, and the shutdown process is shown. However, there's no validation workflow — no steps to verify telemetry is actually being sent, no troubleshooting for common failures, and no feedback loop for confirming the setup works. For an instrumentation skill where misconfiguration silently drops data, this is a notable gap.

3 / 5

Progressive Disclosure

All content is inlined in a single monolithic file (~200+ lines) with no references to supporting files. The manual exporter setup, custom span processor, sampling, and logs ingestion sections would be better placed in separate reference files. With no bundle files provided, there's no structure to support progressive discovery.

2 / 5

Total

13

/

20

Passed

Description

53%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 concise and identifies a clear domain (Node.js auto-instrumentation) with three concrete output types, but it lacks a 'Use when...' clause and misses important trigger terms like 'OpenTelemetry', 'observability', and 'APM' that users would naturally use. It is reasonably distinctive but would benefit from explicit trigger guidance and broader keyword coverage.

Suggestions

Add a 'Use when...' clause with trigger phrases like 'when the user asks about adding observability, OpenTelemetry, APM, or monitoring to a Node.js application'.

Include common synonyms and related terms such as 'OpenTelemetry', 'observability', 'APM', 'monitoring', 'telemetry', 'spans', and 'exporters' to improve trigger term coverage.

Expand the specific actions beyond 'auto-instrument' to include details like 'configure trace exporters, set up metric collectors, inject tracing middleware, add structured logging'.

DimensionReasoningScore

Specificity

Names the domain (Node.js applications) and lists three concrete capabilities (distributed tracing, metrics, logs), but doesn't elaborate on specific actions like 'inject middleware', 'configure exporters', or 'set up span collection'. The verb 'auto-instrument' is somewhat specific but singular.

3 / 5

Completeness

Clearly answers 'what' (auto-instrument Node.js apps with tracing, metrics, logs) but has no 'when' clause or trigger guidance. Per rubric rules, a missing 'Use when...' clause caps completeness at 3.

3 / 5

Trigger Term Quality

Includes relevant terms like 'Node.js', 'distributed tracing', 'metrics', and 'logs', but misses common synonyms and natural phrases users might say such as 'OpenTelemetry', 'observability', 'APM', 'monitoring', 'telemetry', or 'instrumentation'.

3 / 5

Distinctiveness Conflict Risk

Fairly distinct due to the specific combination of 'Node.js', 'auto-instrument', and 'distributed tracing'. Minor overlap risk with general monitoring/logging skills, but the focus on auto-instrumentation narrows the niche well.

4 / 5

Total

13

/

20

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

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

Table of Contents

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