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health-check-endpoints

Health check endpoints for liveness, readiness, dependency monitoring. Use for Kubernetes, load balancers, auto-scaling, or encountering probe failures, startup delays, dependency checks, timeout configuration errors.

74

Quality

93%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

100%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 body is an exemplary skill document: lean and executable, with a clear probe taxonomy, working code for the common case, concrete K8s configuration, explicit best-practice guardrails, and a well-signaled one-level-deep reference for alternate stacks. No weaknesses identified.

DimensionReasoningScore

Conciseness

The body is lean: a probe-type table, executable code, K8s YAML, and terse bullet lists ("Keep liveness checks minimal (no external deps)"). It never explains concepts Claude already knows, and every section earns its place, matching anchor 5.

5 / 5

Actionability

The Express snippet (HealthChecker class plus /health/live and /health/ready handlers) and the complete Kubernetes YAML (paths, ports, initialDelaySeconds, failureThreshold) are copy-paste ready and cover the common cases, matching anchor 5; undefined db/redis/app bindings are the expected surrounding app context, not pseudocode.

5 / 5

Workflow Clarity

This is a single-purpose pattern skill under 50 lines of prose, so the simple-skill exception applies: the single action (implement health check endpoints) is unambiguous, the probe table defines each check's failure action, and the "Never Do" section provides explicit guardrails.

5 / 5

Progressive Disclosure

The single reference (references/implementations.md — verified to exist, one level deep, containing the promised Flask, Spring Boot Actuator, and Kubernetes sections) is well-signaled with an itemized preview, while the primary pattern stays inline. Content is appropriately split with easy navigation, matching anchor 5.

5 / 5

Total

20

/

20

Passed

Description

83%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.

A strong description that explicitly states both what the skill does and when to use it, with natural, domain-appropriate trigger terms. Minor gaps: some common synonyms (healthz, unhealthy, 503) are missing and broad infra terms create slight overlap risk.

Suggestions

Add common synonyms and endpoint conventions users mention naturally, e.g. healthz, ping endpoints, unhealthy/503 responses.

Narrow trigger terms slightly (e.g. 'Kubernetes probe failures' rather than bare 'Kubernetes, load balancers') to reduce overlap with general deployment skills.

DimensionReasoningScore

Specificity

"Health check endpoints for liveness, readiness, dependency monitoring" names several concrete capability areas, matching anchor 4 (several specific actions, minor gaps). It falls short of anchor 5 because coverage is not comprehensive — startup probes, deep checks, and alerting are absent.

4 / 5

Completeness

Explicitly answers both: what ("Health check endpoints for liveness, readiness, dependency monitoring") and when ("Use for Kubernetes, load balancers, auto-scaling, or encountering probe failures, startup delays, dependency checks, timeout configuration errors") with concrete trigger phrases, matching anchor 5.

5 / 5

Trigger Term Quality

"Kubernetes, load balancers, auto-scaling, probe failures, startup delays, dependency checks, timeout configuration errors" are natural phrases users would say, giving good keyword coverage. A few natural terms are missing (healthz, ping endpoint, unhealthy, 503), so it does not reach anchor 5.

4 / 5

Distinctiveness Conflict Risk

The health-check endpoint niche with triggers like "probe failures" and "readiness" is mostly distinct from other skills. Broad terms like "Kubernetes, load balancers, auto-scaling" carry minor overlap risk with general deployment/infrastructure skills, placing it at anchor 4 rather than 5.

4 / 5

Total

17

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
secondsky/claude-skills
Reviewed

Table of Contents

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