otel-instrumentation
Configures trace spans, defines custom metrics, sets up log exporters, and optimizes sampling strategies for OpenTelemetry instrumentation. Use when instrumenting applications with traces, metrics, or logs. Triggers on requests for observability, telemetry, tracing, metrics collection, logging integration, or OTel setup.
100
100%
Does it follow best practices?
Impact
100%
1.23xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
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 clearly articulates specific capabilities, provides comprehensive trigger terms covering natural user language, and explicitly addresses both what the skill does and when it should be used. The description is concise yet thorough, with strong distinctiveness due to its focused OpenTelemetry domain.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Configures trace spans', 'defines custom metrics', 'sets up log exporters', and 'optimizes sampling strategies'. These are precise, actionable capabilities within the OpenTelemetry domain. | 3 / 3 |
Completeness | Clearly answers both 'what' (configures trace spans, defines custom metrics, sets up log exporters, optimizes sampling strategies) and 'when' with explicit trigger guidance ('Use when instrumenting applications...' and 'Triggers on requests for...'). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'observability', 'telemetry', 'tracing', 'metrics collection', 'logging integration', 'OTel setup', 'traces', 'metrics', 'logs'. Includes both formal terms and the common abbreviation 'OTel'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche around OpenTelemetry instrumentation. The specific terms like 'trace spans', 'sampling strategies', 'OTel', and 'OpenTelemetry' make it very unlikely to conflict with generic logging or monitoring skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality skill that serves as an effective entrypoint for OpenTelemetry instrumentation. It excels at progressive disclosure with a well-organized reference table, provides a concrete executable example, and includes genuinely useful decision-making principles (signal density, sampling strategy) that go beyond what Claude would know by default. The only minor limitation is that bundle files weren't provided to verify the referenced paths actually exist, but the structure itself is exemplary.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. It doesn't explain what OpenTelemetry is or how tracing works conceptually — it assumes Claude already knows. The table is a compact navigation aid, the code example is purposeful, and the key principles section adds genuinely useful decision-making heuristics (signal density, sampling strategy) without padding. | 3 / 3 |
Actionability | The getting-started workflow provides concrete steps, the Node.js code example is fully executable and copy-paste ready with proper error handling and span lifecycle, and the sampling guidance gives a specific directive (use AlwaysOn sampler, defer to Collector). References to language-specific rules provide paths to more detailed executable guidance. | 3 / 3 |
Workflow Clarity | The 5-step getting-started workflow is clearly sequenced from SDK selection through validation, with an explicit validation checkpoint at step 5 referencing a dedicated validation checklist. The sampling pipeline diagram clearly shows the data flow. For an overview/entrypoint skill that delegates detailed workflows to sub-files, this is well-structured. | 3 / 3 |
Progressive Disclosure | Excellent progressive disclosure — the SKILL.md serves as a clear overview and navigation hub with a well-organized table linking to 20 one-level-deep references organized by concern (rules, platforms, SDKs). References are clearly signaled with descriptive labels. The inline content is appropriately scoped to quick-start and key principles. | 3 / 3 |
Total | 12 / 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.
- Repository
- dash0hq/agent-skills
- Commit
e73252a
- Reviewed
Table of Contents
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