performance-benchmark

Measure and compare performance baselines before and after code changes.

Updated Dec 24, 2025

Search Tags:#performance #web vitals #bundle size #profiling #lighthouse #regression #benchmark

Ready to run

npx skills add https://github.com/JoyJoin-Tech-Limited/JoyJoin_app_v0.1 --skill performance-benchmark-joyjoin-tech-limited

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Please help me install this Agent Skill.
Skill: performance-benchmark
Source: https://github.com/JoyJoin-Tech-Limited/JoyJoin_app_v0.1/tree/main/.github/skills/performance-benchmark
Command: npx skills add https://github.com/JoyJoin-Tech-Limited/JoyJoin_app_v0.1 --skill performance-benchmark-joyjoin-tech-limited

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Performance claims without numbers are guesses. This Skill provides a repeatable method for measuring route transitions, web vitals, bundle behavior, and script throughput before and after a change, so regressions and improvements are proven with data instead of asserted. ## Core Features & Use Cases - Before-and-After Benchmarking: Record baseline metrics and compare them against post-change results using the same environment and inputs. - Metric Selection Guidance: Match the right metric to the question, whether that is LCP, route transition time, bundle size, or script throughput. - Mini-Program Package Analysis: Compare main-package size, first-open latency, and preload behavior when evaluating ordinary versus independent subpackages. - Use Case: A developer claims a refactor made page loads faster. Use this Skill to capture Lighthouse or route-transition timings on both revisions under identical conditions and report a concrete numeric comparison. ## Quick Start Ask the AI to benchmark the route transition time before and after your change using the same environment and input conditions.

Frequently Asked Questions about performance-benchmark

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

FAQPage Schema

How do I benchmark a performance change before and after implementation?▼

Record a baseline metric on the original code, apply the change, then re-run the identical measurement under the same environment, input size, and sample conditions. Compare the two numeric results rather than relying on subjective impressions of speed.

What metrics should I use to measure frontend performance?▼

Match the metric to the user-visible problem: LCP and Lighthouse for load experience, route transition timing for navigation, bundle size for delivery weight, and long-list scroll behavior for rendering. Avoid collapsing different problems into one generic score.

How do I compare script throughput between two revisions?▼

Run the same script with the same input size and environment assumptions on both revisions, then compare runtime numerically. Repo scripts like simulate-1000-users.ts can act as repeatable baseline harnesses for non-UI work.

When should I use ordinary versus independent subpackages in a mini-program?▼

Measure first. Compare main-package size reduction and target-page first-open latency with an ordinary subpackage plus preload, and only test an independent subpackage if bootstrap cost still dominates. Include duplication and bootstrap overhead in the comparison.

Why is a benchmark result without numbers not valid?▼

A claim of faster with no metric and no comparison point is not a benchmark. Every result needs at least one concrete metric, a baseline for comparison, and stated environment assumptions so another engineer can reproduce it.