load-test-scenario-builder
SkillDev toolsDesigns realistic load and performance testing scenarios with k6, Locust, or JMeter for traffic simulations.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the load-test-scenario-builder skill
What this skill tells your AI
The instructions your AI receives, as published by codebygarv/ai-skills in skills/testing/load-test-scenario-builder/SKILL.md and read by ahel’s review.
Purpose
Create realistic, multi-phase performance and stress testing scripts modeling authentic user traffic patterns (browsing, authentication, cart checkout, search) with proper ramp-up and threshold gates.
When to Use
- Benchmarking system throughput and maximum capacity limits.
- Validating autoscaling triggers and database connection limits under load.
- Setting up CI performance regression testing gates.
What to Analyze
- Traffic Profile: Ramp-up, sustained peak load, stress spikes, and ramp-down phases.
- User Journey Distribution: Weighted action ratios (e.g., 70% browse/search, 20% add to cart, 10% checkout).
- Think Time & Jitter: Realistic pauses between user clicks (e.g.,
sleep(random(1, 4))). - Performance Thresholds (SLOs): Target response time percentiles (p95 < 200ms, error rate < 0.1%).
- Data Parameterization: Dynamic test data pools to avoid un-realistic cache warming on a single ID.
Output Format
- Load Scenario Script: Complete k6 (JavaScript) or Locust (Python) script.
- Execution Stages: Configuration of virtual users (VUs) and durations.
- Threshold Definitions: Explicit pass/fail assertion rules.
Avoid
- Hammering a single URL with 1,000 requests/sec with zero think-time (unrealistic traffic).
- Omitting assertions on HTTP status and response payload validation.
Signals
- GitHub stars
- 25
- Forks
- 1
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
load-test-scenario-builder- Source
- github.com/codebygarv/ai-skills