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testland/gatling-load-testing

Authors Gatling simulations in Java / Kotlin / Scala (or JS / TS) using the Simulation class plus http() / scenario() / exec() DSL builders, ramps virtual users via injectOpen (arrival rate) or injectClosed (concurrent count), runs via Maven / Gradle / sbt with the Gatling plugin, and gates CI on assertions defined in setUp(). Use when the project is on the JVM and the team prefers code-first load tests over JMeter's XML or k6's JavaScript-only authoring.

75

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Passed

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Overview
Quality
Evals
Security
Files

Quality

Content

100%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An exemplary content body: concise, fully actionable with executable Java and build commands, logically sequenced, and correctly splitting detail into one-level references. No meaningful weaknesses across the four dimensions.

DimensionReasoningScore

Conciseness

Lean and dense — tables, focused code, and terse prose with no padding explaining what load testing is or how libraries work; every section earns its place and assumes Claude's competence.

3 / 3

Actionability

Provides a complete executable Java Simulation class (imports, setUp, assertions) plus concrete mvn/gradlew/sbt commands and real DSL snippets, all copy-paste ready.

3 / 3

Workflow Clarity

Sections are sequenced logically from When-to-use through Limitations, and the authoring flow is unambiguous; as a single-task authoring skill, clear single-action guidance satisfies the workflow-clarity bar per the simple-skills note.

3 / 3

Progressive Disclosure

The body is an overview that splits detailed CI and anti-pattern content into real, clearly signaled one-level-deep references (references/ci-integration.md and references/anti-patterns.md), with easy navigation.

3 / 3

Total

12

/

12

Passed

Description

85%

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, specific description that names concrete capabilities and gives an explicit use-when trigger, with clear differentiation from JMeter and k6. The only gap is trigger-term breadth: it leans on tool-comparison phrasing rather than the fuller vocabulary a user might naturally say.

Suggestions

Broaden trigger terms to natural user phrasings such as 'stress test', 'performance test', 'soak test', and 'endurance test' rather than relying mainly on JMeter/k6 comparisons.

Consider naming the supported non-HTTP protocols (WebSocket, JMS, gRPC, MQTT) in the description, since that is a key differentiator from k6/locust.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Authors Gatling simulations', 'ramps virtual users via injectOpen...or injectClosed', 'runs via Maven/Gradle/sbt', 'gates CI on assertions defined in setUp()' — plus named DSL builders, matching the 'multiple specific concrete actions' anchor.

3 / 3

Completeness

Clearly answers what (authors simulations, ramps VUs, runs via build plugins, gates CI) and when via an explicit 'Use when the project is on the JVM...' clause, matching the both-what-and-when anchor.

3 / 3

Trigger Term Quality

Includes relevant terms (load tests, JMeter, k6, JVM, Gatling) but the trigger leans on tool-comparison jargon rather than a broad spread of natural user phrasings like 'stress test', 'performance test', or 'soak test', so coverage is partial.

2 / 3

Distinctiveness Conflict Risk

Clear niche (Gatling/JVM load testing) explicitly contrasted with JMeter's XML and k6's JS, with body cross-references to k6/locust, making it unlikely to trigger for the wrong skill.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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