Add OpenTelemetry observability (traces, logs, metrics) to a Node.js/TypeScript app with Liteverge. Use when the user asks to add observability, tracing, logging, or metrics to an Express, Fastify, or similar Node.js backend — or to add custom spans, logs, and instrumentation to an already-instrumented app.
94
92%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that hits all the marks. It provides specific concrete actions, includes comprehensive natural trigger terms that developers would actually use, explicitly states both what the skill does and when to use it, and carves out a clear distinctive niche with the Liteverge + OpenTelemetry + Node.js combination.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Add OpenTelemetry observability (traces, logs, metrics)', 'add custom spans, logs, and instrumentation'. Clearly names the technology stack (Node.js/TypeScript, Liteverge) and specific frameworks (Express, Fastify). | 3 / 3 |
Completeness | Clearly answers both what ('Add OpenTelemetry observability to a Node.js/TypeScript app with Liteverge') and when ('Use when the user asks to add observability, tracing, logging, or metrics...'). Includes explicit 'Use when' clause with specific trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'observability', 'tracing', 'logging', 'metrics', 'Express', 'Fastify', 'Node.js backend', 'custom spans', 'instrumentation'. These are terms developers naturally use when seeking this functionality. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche: specifically targets OpenTelemetry + Liteverge + Node.js/TypeScript stack. The combination of technology-specific terms (Liteverge, OpenTelemetry) and framework mentions (Express, Fastify) makes it unlikely to conflict with generic logging or monitoring skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured routing skill that efficiently directs Claude to the appropriate detailed guide based on user intent. The decision criteria are clear and the progressive disclosure is exemplary. The only weakness is that the overview itself contains no executable content, relying entirely on referenced files for actionability.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, providing only decision logic and navigation without explaining what OpenTelemetry is or how tracing works. Every line serves a purpose. | 3 / 3 |
Actionability | The skill provides clear decision criteria and file references, but no executable code or concrete commands are present in this overview file. The actionability depends entirely on the referenced files. | 2 / 3 |
Workflow Clarity | For a routing/decision skill, the workflow is crystal clear: determine mode based on user request, check package.json if unsure, then follow the appropriate guide. The decision tree is unambiguous. | 3 / 3 |
Progressive Disclosure | Excellent structure with a clear overview and well-signaled one-level-deep references to init.md and instrument.md. The decision logic is appropriately in the main file while detailed instructions are delegated. | 3 / 3 |
Total | 11 / 12 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 — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
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Table of Contents
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