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o11y-dev/opentelemetry-skill

Expert OpenTelemetry guidance for collector configuration, pipeline design, and production telemetry instrumentation across Kubernetes, ECS, serverless, and standalone deployments. Use when configuring collectors, designing pipelines, instrumenting applications, implementing sampling, managing cardinality, securing telemetry, writing OTTL transformations, or setting up AI coding agent observability (Claude Code, Codex, Gemini CLI, GitHub Copilot).

92

1.36x
Quality

90%

Does it follow best practices?

Impact

93%

1.36x

Average score across 18 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Overview
Quality
Evals
Security
Files

Quality

Content

82%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 highly actionable with copy-paste config, concrete commands, and specific attributes, and it is well-structured with checklists and a one-level-deep reference table. Its weaknesses are mild cross-section repetition and a deployment-setup subtree (5 files plus its own nav hub) that has no discovery path from SKILL.md.

Suggestions

Link setup-index.md from SKILL.md (e.g., in the Context Triggers table under a 'Deployment setup, Kubernetes, ECS, Docker, VM' row) so the 5 orphaned setup-* files become discoverable from the entry point.

De-duplicate the memory_limiter-first and cardinality rules: state each once as a principle and reference it from the baseline, eval-critical, and anti-pattern sections rather than restating it.

Inline a short validate→fix→retry loop in the Validation & Error Recovery section instead of only delegating it to validation.md, to satisfy the explicit-feedback-loop anchor.

DimensionReasoningScore

Conciseness

The body largely assumes Claude's competence — it never explains what OpenTelemetry, a collector, or tracing is — but several guardrails are repeated across sections (memory_limiter-first and the cardinality rule each reappear in Core Principles, Eval-Critical Minimums, the baseline key defaults, and Anti-Patterns), so it is efficient with minor instances that could be trimmed rather than fully lean.

4 / 5

Actionability

Provides a copy-paste-ready production baseline YAML, a concrete validation command ('otelcol validate --config <path>'), specific ports (4317/4318), exact env vars ('CLAUDE_CODE_ENABLE_TELEMETRY=1', 'OTEL_EXPORTER_OTLP_METRICS_TEMPORALITY_PREFERENCE=cumulative'), and concrete OTTL attribute names, fully covering the common cases with executable guidance.

5 / 5

Workflow Clarity

Clear checklists structure the work (Pre-Flight Checklist, the 9-item Existing Configuration Review Mode, Anti-Patterns) and an explicit validation checkpoint is required, but the validate→fix→retry feedback loop is delegated to validation.md rather than stated inline, leaving a minor gap versus the anchor that has explicit in-line feedback loops.

4 / 5

Progressive Disclosure

SKILL.md is a well-signaled overview with a one-level-deep 'Context Triggers' table mapping keywords to 14 real reference files, but 5 of the 19 bundle files (setup-docker, setup-ecs, setup-kubernetes, setup-vm, and the setup-index.md nav hub itself) are not reachable from SKILL.md, a moderate organization gap rather than the minor one implied by the top anchor.

4 / 5

Total

17

/

20

Passed

Description

92%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 is strong: it states concrete capabilities, an explicit 'Use when' clause with concrete triggers, a clear OTel niche, and named AI-agent tools. The only gap is missing common synonyms (otel/otelcol) and file extensions that would push trigger-term quality to the top anchor.

Suggestions

Add common synonyms users say ('otel', 'otelcol', 'traces/metrics/logs') to the description so trigger-term quality reaches the comprehensive anchor.

Consider naming one or two representative file types (e.g., 'collector YAML') to match the natural-term-plus-extension coverage of the top anchor.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'collector configuration, pipeline design, and production telemetry instrumentation' plus 'configuring collectors, designing pipelines, instrumenting applications, implementing sampling, managing cardinality, securing telemetry, writing OTTL transformations' — giving comprehensive coverage of the skill's capabilities, matching the anchor that lists several specific concrete actions.

5 / 5

Completeness

Explicitly answers both 'what' ('Expert OpenTelemetry guidance for collector configuration, pipeline design, and production telemetry instrumentation') and 'when' ('Use when configuring collectors, designing pipelines... or setting up AI coding agent observability') with concrete trigger phrases, matching the anchor for clearly answering both what and when.

5 / 5

Trigger Term Quality

Strong natural-term coverage ('opentelemetry', 'collector', 'pipeline', 'sampling', 'cardinality', 'OTTL') plus named AI tools ('Claude Code, Codex, Gemini CLI, GitHub Copilot'), but it omits common synonyms users say ('otel', 'otelcol') and any file extensions, so it falls just short of the comprehensive-with-synonyms/extensions anchor at 5.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear OpenTelemetry/collector niche with distinct, specific triggers (OTTL, collector, cardinality, named AI agents), giving minimal conflict risk with other skills; it is not a level below because the triggers are too specific to fire for unrelated skills.

5 / 5

Total

19

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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