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Agent Skill · 研究检索

swift-performance-optimization-skill(Swift 性能 optimization 技能)

swift-performance-optimization-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

swift-performance-optimization-skill 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 14,225。

总安装 8,729周安装 383GitHub Stars 公开资料未说明下载 4,431核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:swift-performance-optimization-skill(Swift 性能 optimization 技能)
来源仓库:https://github.com/pstuart/pstuart
仓库路径:skills/swift-performance-optimization-skill
安装命令:
npx skills add pstuart/pstuart --skill "swift-performance-optimization-skill"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add pstuart/pstuart --skill "swift-performance-optimization-skill"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持基于关键词快速定位候选结果。适用于 Codex、Claude、Cursor 和 Gemini CLI 中的研究检索场景。可结合来源仓库 README 核验具体用法和功能边界。安装前需确认权限范围和维护状态,避免触发不必要的联网操作。建议评估是否会执行命令或读写文件后再部署使用。

来源仓库内路径:skills/swift-performance-optimization-skill

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add pstuart/pstuart --skill "swift-performance-optimization-skill";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

swift-performance-optimization-skill 怎么安装?

在终端执行 npx skills add pstuart/pstuart --skill "swift-performance-optimization-skill"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

swift-performance-optimization-skill 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

swift-performance-optimization-skill 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

swift-performance-optimization-skill 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

swift-performance-optimization-skill 用的人多吗?

公开数据是累计安装 8,729 次,近一周安装 383 次,下载 4,431 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

swift-performance-optimization-skill 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
swift-performance-optimization-skill

Swift 性能 optimization 技能 · 本页

8,729—需要联网MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
Swift Performance Optimization Skill
description
Techniques for optimizing Swift code performance, memory usage, rendering efficiency, and using Instruments for profiling.
version
1.0
activation
Activate for queries on Swift performance optimization, memory management, rendering improvements, Instruments usage, or profiling Swift/iOS apps.

Swift Performance Optimization Skill

This skill provides expertise in optimizing Swift code for better performance, memory efficiency, and smooth rendering. It covers profiling with Instruments, memory management best practices, and performance patterns specific to iOS development.

Best Practices

  1. Profile First: Always use Instruments to identify bottlenecks before optimizing.
  1. Memory Management: Understand ARC, avoid retain cycles, and manage memory efficiently.
  1. Lazy Loading: Defer expensive operations and use lazy properties when appropriate.
  1. Efficient Collections: Choose the right data structures and operations for performance.
  1. UI Performance: Optimize rendering with techniques like cell reuse and background processing.
  1. Concurrency: Use GCD or Swift Concurrency for background tasks without blocking the main thread.

Performance Guidelines

  • Minimize work on the main thread, especially UI updates.
  • Use Instruments Time Profiler to find CPU hotspots.
  • Monitor memory usage with Allocations and Leaks instruments.
  • Optimize images and assets for size and loading.
  • Cache expensive computations when possible.
  • Avoid unnecessary view updates in SwiftUI with proper state management.

Examples

Example 1: Optimizing SwiftUI List Performance

User Prompt: "How can I optimize a SwiftUI List with many items that's scrolling slowly?"

Expected Output:

import SwiftUI

struct OptimizedListView: View {
    let items = Array(1...10000) // Large dataset
    
    var body: some View {
        List(items, id: \.self) { item in
            OptimizedRowView(item: item)
        }
        .listStyle(.plain)
    }
}

struct OptimizedRowView: View {
    let item: Int
    
    var body: some View {
        HStack {
            Text("Item \(item)")
            Spacer()
            Image(systemName: "star")
                .foregroundColor(.yellow)
        }
        .padding(.vertical, 8)
        // Avoid complex computations in body
        // Use @StateObject for view models if needed
    }
}

// For even better performance with large datasets:
struct LazyOptimizedListView: View {
    let items = Array(1...10000)
    
    var body: some View {
        ScrollView {
            LazyVStack {
                ForEach(items, id: \.self) { item in
                    OptimizedRowView(item: item)
                }
            }
        }
    }
}

Example 2: Memory Management with Weak References

User Prompt: "Fix a potential memory leak in a closure capturing self."

Expected Output:

class NetworkManager {
    var completionHandler: (() -> Void)?
    
    func fetchData() {
        // BAD: Strong reference cycle
        // self.completionHandler = {
        //     self.processData()
        // }
        
        // GOOD: Weak self to avoid retain cycle
        self.completionHandler = { [weak self] in
            self?.processData()
        }
        
        // Simulate network call
        DispatchQueue.global().asyncAfter(deadline: .now() + 1) {
            self.completionHandler?()
        }
    }
    
    func processData() {
        print("Data processed")
    }
}

// Alternative with unowned for non-optional self
class ViewController {
    var timer: Timer?
    
    func startTimer() {
        timer = Timer.scheduledTimer(withTimeInterval: 1.0, repeats: true) { [unowned self] timer in
            self.updateUI()
        }
    }
    
    func updateUI() {
        // Update UI
    }
}

Example 3: Instruments Time Profiler Usage

User Prompt: "How do I use Instruments to profile CPU performance in my Swift app?"

Expected Output: To profile CPU performance:

  1. Open Xcode and select Product > Profile (⌘I)
  2. Choose "Time Profiler" from the Instruments template
  3. Click the record button to start profiling
  4. Perform the actions you want to profile in your app
  5. Stop recording and examine the call tree
  6. Look for methods with high "Self" time (time spent in that method itself)
  7. Expand the heaviest stack trace to identify bottlenecks

Key Time Profiler tips:

  • Focus on "Self" column for time spent in each method
  • Use "Invert Call Tree" to see bottom-up view
  • Separate by thread to identify main thread blocking
  • Look for recursive calls or unexpected frequent calls

Example findings:

  • If viewDidLoad() takes 500ms, check for expensive operations
  • Heavy tableView(_:cellForRowAt:) calls indicate list optimization needed
  • Frequent layoutSubviews() suggests layout inefficiencies

Example 4: Efficient Image Loading

User Prompt: "Optimize image loading and display in a collection view."

Expected Output:

import UIKit

class ImageCollectionViewCell: UICollectionViewCell {
    let imageView = UIImageView()
    private var imageLoadTask: URLSessionDataTask?
    
    override init(frame: CGRect) {
        super.init(frame: frame)
        setupViews()
    }
    
    required init?(coder: NSCoder) {
        fatalError("init(coder:) has not been implemented")
    }
    
    private func setupViews() {
        imageView.contentMode = .scaleAspectFill
        imageView.clipsToBounds = true
        contentView.addSubview(imageView)
        imageView.frame = contentView.bounds
    }
    
    func configure(with imageURL: URL) {
        // Cancel previous task
        imageLoadTask?.cancel()
        
        // Placeholder
        imageView.image = UIImage(named: "placeholder")
        
        // Load image asynchronously
        imageLoadTask = URLSession.shared.dataTask(with: imageURL) { [weak self] data, _, _ in
            guard let data = data, let image = UIImage(data: data) else { return }
            
            DispatchQueue.main.async {
                self?.imageView.image = image
            }
        }
        imageLoadTask?.resume()
    }
    
    override func prepareForReuse() {
        super.prepareForReuse()
        imageLoadTask?.cancel()
        imageView.image = nil
    }
}

// Usage in ViewController
class ImageGalleryViewController: UIViewController, UICollectionViewDataSource {
    let collectionView = UICollectionView(frame: .zero, collectionViewLayout: UICollectionViewFlowLayout())
    let imageURLs: [URL] = [] // Your image URLs
    
    func collectionView(_ collectionView: UICollectionView, cellForItemAt indexPath: IndexPath) -> UICollectionViewCell {
        let cell = collectionView.dequeueReusableCell(withReuseIdentifier: "ImageCell", for: indexPath) as! ImageCollectionViewCell
        cell.configure(with: imageURLs[indexPath.item])
        return cell
    }
}

Example 5: SwiftUI Rendering Optimization

User Prompt: "Optimize SwiftUI view updates to prevent unnecessary re-renders."

Expected Output:

import SwiftUI

// BAD: Causes re-render on every change
struct BadCounterView: View {
    @State private var count = 0
    @State private var name = "Counter"
    
    var body: some View {
        VStack {
            Text(name) // Re-renders when count changes
            Text("\(count)")
            Button("Increment") { count += 1 }
        }
    }
}

// GOOD: Separate concerns
struct OptimizedCounterView: View {
    @State private var count = 0
    
    var body: some View {
        VStack {
            CounterTitleView() // Only re-renders when needed
            CounterDisplayView(count: count)
            CounterButtonView(count: $count)
        }
    }
}

struct CounterTitleView: View {
    var body: some View {
        Text("Counter")
    }
}

struct CounterDisplayView: View {
    let count: Int
    
    var body: some View {
        Text("\(count)")
    }
}

struct CounterButtonView: View {
    @Binding var count: Int
    
    var body: some View {
        Button("Increment") { count += 1 }
    }
}

// Alternative: Use Equatable for custom comparisons
struct EquatableView: View, Equatable {
    let title: String
    let count: Int
    
    var body: some View {
        VStack {
            Text(title)
            Text("\(count)")
        }
    }
    
    static func == (lhs: EquatableView, rhs: EquatableView) -> Bool {
        lhs.title == rhs.title && lhs.count == rhs.count
    }
}

平台分布

windsurf

26.97%
按下载量换算1,195

Codex

22.1%
按下载量换算979

Claude Code

20.15%
按下载量换算893

Antigravity

14.02%
按下载量换算621

Gemini CLI

8.5%
按下载量换算377

trae

3.63%
按下载量换算161

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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