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performance-tuning

Measure, analyze, optimize, and evaluate build size and execution speed.

3|2|Updated Jun 13, 2025
Search Tags:#performance#optimization#benchmark#measurement#code-tuning#build-size
One-click install
npx skills add https://github.com/poteto-go/go-alchemy-sdk --skill performance-tuning-poteto-go
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance-tuning
Source: https://github.com/poteto-go/go-alchemy-sdk/tree/main/.gemini/skills/performance-tuning
Command: npx skills add https://github.com/poteto-go/go-alchemy-sdk --skill performance-tuning-poteto-go

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This section explains the challenge of improving build size and execution speed and emphasizes measuring before making changes to ensure verifiable improvements.

Core Features & Use Cases

  • Build size minimization: reduce binary or bundle sizes across Go, TS, and Rust projects.
  • Execution speed improvement: shorten test times and runtime latency through bottleneck analysis and benchmarking.
  • Use Case: When optimizing a large Go service, apply the workflow to identify bottlenecks, implement targeted changes, and re-measure to validate improvements.

Quick Start

Run the documented measurement and optimization workflow on your project to establish baselines, identify bottlenecks, implement optimizations, and re-measure for validation.

Frequently Asked Questions about performance-tuning

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

FAQPage Schema
How do I reduce binary or bundle size across Go, TypeScript, and Rust projects?▼

Reduce build size by applying a measurement-driven workflow that establishes baselines, identifies bottlenecks, implements optimizations, and re-measures to validate reductions in Go, TypeScript, and Rust codebases.

What is the best way to improve execution speed and shorten test times?▼

Improving execution speed requires measuring baseline runtime, analyzing bottlenecks, benchmarking targeted changes, and re-measuring post-optimization to verify latency reductions and faster test execution.

How do I measure performance before and after code tuning?▼

Measure performance before and after code tuning using a structured workflow that captures baseline metrics, guides bottleneck analysis, and evaluates post-optimization results to ensure verifiable improvements.

Does this performance optimization workflow work with multi-language codebases?▼

Yes, the performance optimization workflow applies to multi-language codebases, specifically supporting Go, TypeScript, and Rust projects for both build size minimization and execution speed improvement.

Why should I measure baselines before optimizing build size?▼

Measuring baselines before optimizing build size ensures verifiable improvements by providing a reference point to compare against post-optimization results, preventing blind changes and confirming the effectiveness of code tuning.

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