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kopai/otel-instrumentation

Instrument applications with the OpenTelemetry SDK and prove the telemetry is good by validating it against a local Kopai backend. Use when setting up observability, adding tracing/logging/metrics, deciding what to instrument or which attributes to add, retrofitting OTel into an existing codebase, threading context through call chains, configuring sampling, or when traces/logs/metrics aren't appearing after setup. Also use when users say things like "my traces aren't showing up", "I don't see any data", or "how do I add observability to my app". Do NOT use to investigate existing telemetry for a root cause (use root-cause-analysis), to build dashboards (use create-dashboard), or to instrument LLM and agent calls (use otel-genai-instrumentation).

75

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Overview
Quality
Evals
Security
Files

Quality

Content

85%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.

A well-architected skill body: a validated workflow loop with explicit checkpoints, actionable code and commands, and disciplined progressive disclosure into a verified reference bundle. Minor conciseness trims in the package-manager guidance would push it to the top anchor.

Suggestions

Tighten the 'Picking instrumentation packages' section — the package-manager detection and deprecation-warning prose can be condensed into a short rule plus the existing commands without losing the actionable detail.

Consider inlining a one-line minimal span example for a second language (e.g. Python) in 'The core pattern' so the common case is executable without immediately opening a lang-* reference.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's OTel knowledge (e.g. it defines only project jargon like 'wide event'), but the package-manager detection and deprecation prose could be trimmed slightly. It sits above the 'mostly efficient' anchor but short of perfectly lean.

4 / 5

Actionability

Provides copy-paste-ready TypeScript for the core pattern plus concrete commands (npx start, the curl readiness check, npm view ... deprecated) and a two-question decision rule; the only gap is that language-specific implementation is deferred to the lang-* references rather than inlined.

4 / 5

Workflow Clarity

A six-step workflow table pairs each step with an explicit 'Done when' validation checkpoint, and steps 4–6 form an explicit feedback loop ('Never stop on a red assertion', re-drive after fixing), matching the top anchor for sequenced validation with error recovery.

5 / 5

Progressive Disclosure

SKILL.md is a clear overview with well-signaled, one-level-deep references grouped by purpose (Setup, Language SDKs, What to instrument, Prove it, Fix it, References); every referenced file under references/ was verified to exist, so navigation is clean and shallow.

5 / 5

Total

18

/

20

Passed

Description

100%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.

An exemplary description: concrete capabilities, comprehensive natural trigger phrases, explicit when-guidance, and clear boundary routing to neighboring skills. Every dimension lands at the top anchor.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Instrument applications with the OpenTelemetry SDK', 'validating it against a local Kopai backend', 'adding tracing/logging/metrics', 'retrofitting OTel', 'threading context', 'configuring sampling' — giving comprehensive coverage of what the skill does.

5 / 5

Completeness

Explicitly answers 'what' (instrument with OTel SDK and validate against a Kopai backend) and 'when' (a detailed 'Use when...' clause with concrete trigger phrases), satisfying both halves with explicit triggers.

5 / 5

Trigger Term Quality

Includes natural user phrases ('my traces aren't showing up', 'I don't see any data', 'how do I add observability to my app') alongside technical synonyms (tracing/logging/metrics, observability, sampling), covering the ways users actually ask for this.

5 / 5

Distinctiveness Conflict Risk

An explicit 'Do NOT use' clause routes three adjacent tasks to distinct skills (root-cause-analysis, create-dashboard, otel-genai-instrumentation), giving a clear niche with minimal conflict risk.

5 / 5

Total

20

/

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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