benchmark

Detect web performance regressions by comparing baseline metrics with browse daemon.

4|1|Updated Sep 13, 2023
One-click install
npx skills add https://github.com/louisfghbvc/mcp-leetcode-crawler --skill benchmark-louisfghbvc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: benchmark
Source: https://github.com/louisfghbvc/mcp-leetcode-crawler/tree/main/.agent/skills/benchmark
Command: npx skills add https://github.com/louisfghbvc/mcp-leetcode-crawler --skill benchmark-louisfghbvc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Performance regressions creep into builds; teams struggle to detect when PRs degrade user experience. This skill automates detection by running browser-based benchmarks and comparing against baselines.

Core Features & Use Cases

  • Baseline capture and regression detection using browse daemon.
  • Page-level metrics: TTFB, FCP, LCP, DOM timings, and resource sizes.
  • Reporting: markdown and JSON baseline outputs, trend analysis, and PR integration.

Quick Start

Run a baseline benchmark for a URL, then compare current results and view a detailed report

Frequently Asked Questions about benchmark

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

FAQPage Schema
How do I detect web performance regressions in a pull request?

Detect web performance regressions by running browser-based benchmarks against established baseline metrics. The skill compares live measurements from the browse daemon with stored baselines to identify degradations in key web vitals during PR workflows.

What web vitals and page timings are captured for baseline performance reporting?

Baseline performance reporting captures TTFB, FCP, LCP, DOM timings, and resource transfer sizes across pages. These metrics are collected via the browse daemon to provide a comprehensive view of web application loading and rendering performance.

How do I set up a baseline benchmark for my web application?

Set up a baseline benchmark by running the benchmark skill against a target URL to collect initial performance metrics. This baseline is saved and later used to compare live measurements from subsequent deployments to identify performance regressions.

Can I generate JSON and markdown reports for performance trend analysis?

Yes, you can generate JSON and markdown reports for performance trend analysis. After running audits and comparing live metrics against baselines, the skill produces detailed markdown and JSON outputs highlighting regressions and ongoing performance trends.

Does the benchmark skill support ongoing deployment workflows or only single audits?

The benchmark skill supports both ongoing deployment workflows and single audits. It is designed to apply to PR workflows and continuous development by comparing key metrics like TTFB, FCP, and LCP across multiple pages and deployments over time.

Why do I need a browse daemon to measure web vitals for regression detection?

A browse daemon is needed to measure web vitals for regression detection because it automates the collection of live browser-based metrics like DOM timings and resource transfers. This allows accurate comparison against stored baselines to pinpoint performance degradations.