benchmark

Capture and compare browser performance metrics to detect regressions and track trends.

Updated Jun 4, 2026
One-click install
npx skills add https://github.com/Manzueti/cyberdart --skill benchmark-manzueti
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: benchmark
Source: https://github.com/Manzueti/cyberdart/tree/main/benchmark
Command: npx skills add https://github.com/Manzueti/cyberdart --skill benchmark-manzueti

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Read, Write, Glob, AskUserQuestion, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates performance regression detection for web applications by establishing baselines and tracking trends, enabling timely identification and resolution of performance issues.

Core Features & Use Cases

  • Performance Baseline Establishment: Automatically capture performance metrics for a given URL and store them as a baseline.
  • Regression Detection: Compare current performance metrics against the baseline to identify performance regressions.
  • Trend Tracking: Visualize performance trends over time to monitor long-term performance stability.
  • Use Case: Regularly use this Skill on a production web application to ensure that new feature additions or changes do not negatively impact performance.

Quick Start

Use the benchmark skill to perform a performance audit on the website 'https://example.com'.

Frequently Asked Questions about benchmark

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

FAQPage Schema
How do I automate performance regression detection for a web application?

Automate performance regression detection by capturing baseline metrics like TTFB and LCP for a URL, then comparing subsequent browser-based metrics against that baseline to identify regressions.

What web performance metrics can I track for baseline establishment?

You can track web performance metrics including Time to First Byte (TTFB), First Contentful Paint (FCP), Largest Contentful Paint (LCP), and DOM interactions to establish a performance baseline.

How do I monitor long-term performance trends in web development?

Monitor long-term performance trends by repeatedly capturing current metrics against a stored baseline, allowing you to visualize performance stability and detect regressions over time.

Does this performance monitoring approach work with browser-based JavaScript tools?

Yes, this performance monitoring approach utilizes browser-based performance tools and JavaScript to measure, capture, and report web application metrics for regression detection.

When do I need to establish a performance baseline for regression tracking?

You need to establish a performance baseline before deploying new features or changes, enabling timely identification and resolution of performance issues by comparing future metrics.

What is the best way to ensure new code changes do not negatively impact web performance?

The best way to ensure code changes do not impact web performance is by regularly auditing production URLs to compare metrics like FCP and LCP against an established baseline.