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benchmark-design

Design, run, and analyze E2E performance benchmarks with per-round statistics.

Updated Aug 23, 2026
Search Tags:#workflow#testing#performance#e2e#analysis#metrics#benchmark
One-click install
npx skills add https://github.com/MajorLift/metamask-extension-skills --skill benchmark-design-majorlift
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: benchmark-design
Source: https://github.com/MajorLift/metamask-extension-skills/tree/main/domains/testing/skills/benchmark-design
Command: npx skills add https://github.com/MajorLift/metamask-extension-skills --skill benchmark-design-majorlift

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Design, run, and analyze end-to-end performance benchmarks for E2E testing workflows, enabling reliable performance assessments and faster optimization cycles.

Core Features & Use Cases

  • Guidance on designing one-vector-per-benchmark workflows to maximize signal
  • Support for per-round statistics, artifact grouping by timestamp, and clear result interpretation
  • Pathways for adding metrics and ensuring session hygiene across benchmark runs

Quick Start

Create a new E2E benchmark design, run reference benchmarks, and analyze results using per-round statistics and artifact grouping.

Frequently Asked Questions about benchmark-design

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

FAQPage Schema
How do I design E2E performance benchmarks for testing workflows?▼

Designing E2E performance benchmarks involves creating one-vector-per-benchmark workflows to maximize signal, ensuring reliable performance assessments for your testing harness. This approach isolates variables for clear result interpretation.

What is the best way to analyze end-to-end performance metrics?▼

Analyzing end-to-end performance metrics is best handled using per-round statistics and artifact grouping by timestamp. This method organizes benchmark runs by generation time to deliver clear result interpretation.

Why should I use one-vector-per-benchmark workflows for performance testing?▼

One-vector-per-benchmark workflows maximize signal in performance testing by isolating variables in your end-to-end testing harness. This design guideline ensures reliable performance assessments and faster optimization cycles.

Can I add custom metrics to my E2E testing harness for benchmark runs?▼

Yes, you can add custom metrics to your E2E testing harness. The benchmark design provides pathways for adding metrics and ensuring session hygiene across multiple benchmark runs to capture accurate performance data.

How do I maintain session hygiene across multiple benchmark runs?▼

Maintaining session hygiene across benchmark runs requires grouping artifacts by timestamp and applying per-round statistics. This ensures clean state isolation and prevents data contamination between E2E testing workflows.

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