Verified:GitHub

benchmark

Establish reproducible performance baselines and detect regressions across web pages, APIs, bundles, and database queries.

2|1|Updated Jul 25, 2026

Search Tags:#bundle size #lighthouse #load testing #regression testing #core web vitals #performance benchmarking #api latency

Ready to run

npx skills add https://github.com/CODE-SAURABH/OpenSkills --skill benchmark-code-saurabh

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: benchmark
Source: https://github.com/CODE-SAURABH/OpenSkills/tree/main/benchmark
Command: npx skills add https://github.com/CODE-SAURABH/OpenSkills --skill benchmark-code-saurabh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill replaces unreliable performance impressions with reproducible measurements, baselines, comparisons, and clear ship-or-hold decisions.

Core Features & Use Cases

Frontend Performance: Measure Core Web Vitals, Lighthouse scores, network requests, and bundle sizes.
API and Database Benchmarking: Evaluate response-time percentiles, error rates, load behavior, and query execution plans.
Regression Detection: Compare before-and-after metrics, apply warning and blocking thresholds, and integrate performance checks into CI.
Use Case: Before merging a frontend change, establish a three-run baseline, measure the candidate build, compare LCP, INP, CLS, bundle size, and API latency, then document whether the change is safe to ship.

Quick Start

Use the benchmark skill to establish a baseline for the specified page or endpoint, measure it three times, compare the results with the candidate version, and produce a ship-or-hold report.

Frequently Asked Questions about benchmark

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

FAQPage Schema

How do I catch performance regressions before merging a frontend change?▼

To catch performance regressions, establish a three-run baseline, measure the candidate build's Core Web Vitals and bundle size, then compare before-and-after metrics to produce a ship-or-hold report.

What is the best way to establish reproducible API latency benchmarks?▼

Reproducible API latency benchmarks require consistent environments to measure response-time percentiles and error rates, then apply explicit regression thresholds for automated comparison and load behavior analysis.

How do I automate Core Web Vitals monitoring in CI pipelines?▼

Automate Core Web Vitals monitoring in CI pipelines by integrating performance checks that compare candidate metrics against established baselines, applying warning and blocking thresholds to enforce ship-or-hold decisions.

Can I measure database query performance and execution plans for load testing?▼

Yes, you can measure database query performance and execution plans during load testing by evaluating response-time percentiles and error rates under load, establishing baselines to detect query regressions.

Does performance benchmarking work without setting up consistent environments?▼

No, performance benchmarking requires consistent environments to establish reproducible measurements and baselines, ensuring that before-and-after comparisons and regression detection remain accurate and reliable.

Why do my Lighthouse scores fluctuate between benchmark runs?▼

Lighthouse scores fluctuate without reproducible baselines from consistent environments; establishing a three-run baseline and comparing compatible numeric metric files ensures accurate regression detection.