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agnaldo4j
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load-testing

Automate k6 load testing scenarios for REST APIs with Docker and k6 CLI.

1|Updated Mar 14, 2026
Search Tags:#performance#api#benchmarking#regression#load-testing#k6
One-click install
npx skills add https://github.com/agnaldo4j/kanban-vision-api-kt --skill load-testing-agnaldo4j
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: load-testing
Source: https://github.com/agnaldo4j/kanban-vision-api-kt/tree/main/.claude/skills/load-testing
Command: npx skills add https://github.com/agnaldo4j/kanban-vision-api-kt --skill load-testing-agnaldo4j

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires k6, and includes scripts (resource) components.

What problem does it solve?

This skill addresses the challenge of maintaining system performance by providing a structured, repeatable way to run load tests, identify latency regressions, and validate throughput against established baselines.

Core Features & Use Cases

  • Performance Benchmarking: Run standardized k6 profiles (smoke, baseline, stress, soak, spike) to measure system behavior under various conditions.
  • Regression Analysis: Compare current performance summaries against historical references to detect latency or throughput degradation.
  • Use Case: After implementing a new feature, use this skill to run a baseline load test and compare the results against the official performance documentation to ensure no regressions were introduced.

Quick Start

Execute the load testing skill to run the baseline performance profile against the current local environment.

Frequently Asked Questions about load-testing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate k6 load testing for REST APIs?▼

Automate k6 load testing for REST APIs by executing standardized performance profiles to measure system behavior under various conditions. This skill handles script execution and analysis automatically, requiring a configured Docker environment and the k6 CLI.

What is the best way to detect API latency regressions after deploying new code?▼

Detect API latency regressions by comparing current k6 performance summaries against historical references. This skill automates regression analysis to identify throughput degradation or latency issues introduced by new features.

Can I validate throughput thresholds against established baselines using k6?▼

Validate throughput against established baselines by running k6 performance benchmarking scenarios. This skill supports threshold validation across multiple load profiles to ensure current performance meets your historical reference metrics.

When do I need to run a soak test versus a spike test for API performance?▼

Run a soak test to measure system behavior under sustained load, and a spike test for sudden traffic surges. This skill supports executing both k6 profiles to validate system stability across various load conditions.

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