技能库智客分类：Agent 工作流 swiftui-performance-audit

Swiftui Performance Audit

审计并改进SwiftUI运行时从代码审查和架构的性能. 用于诊断慢渲染,简洁滚动,高CPU/记忆用法,过度取景更新,或在SwiftUIapps中进行排版,当代码审查不足时为用户运行的仪器剖析提供指引.

9205 安装量

官方网址：skills.sh

技能介绍

先看中文介绍；官方 description 原文单独保留，不改写 SKILL.md。

做什么

何时用

官方 description 未单独写出 Use when。按规范，代理会在用户任务与这段 description 的关键词匹配时激活本技能。

代理如何加载

按 Agent Skills 渐进披露：启动时只加载 name 与 description（约 100 token）；任务匹配后才读入整份 SKILL.md 正文；scripts/、references/、assets/ 仅在需要时再读。本文件正文结构：SwiftUI Performance Audit、Quick start、Workflow、1. Intake、2. Code-First Review、3. Guide the User to Profile。其中含规范建议的小节：分步指令。

文件分析

文件分析：除 SKILL.md 外，正文引用了 references/code-smells.md、references/profiling-intake.md、references/report-template.md、references/optimizing-swiftui-performance-instruments.md，属于带资源的技能包，这些文件按需再读。

官方 description（原文）

Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.

SwiftUI Performance AuditQuick startWorkflow1. Intake2. Code-First Review3. Guide the User to Profile4. Analyze and Diagnose5. Remediate6. VerifyOutputsReferences

来源分类：skills.sh agent-skill

来源与网址

市场来源：skills.sh

GitHub 完整包

开源榜 Skill 分类

SKILL.md 与 Agent 调用

官方规范 ↗

name: swiftui-performance-audit
description: Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.

发现技能客户端向 Agent 提供名称与描述目录。
匹配与调用用户指定或任务匹配后，载入 SKILL.md 指令。
按需加载按步骤读取参考文档、使用脚本与素材。

指令中引用的文件 · 4

references/code-smells.md
references/profiling-intake.md
references/report-template.md
references/optimizing-swiftui-performance-instruments.md

以下路径提取自原文；文件是否齐全请以来源仓库中的完整目录为准。

具体调用语法与可用工具以目标 Agent 客户端为准。查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围，保留技能包的附属文件，安装后检查客户端能否发现该技能。

该技能引用了附属文件，请从来源获取完整目录；仅复制 SKILL.md 可能缺少依赖。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理，确认其中的目标目录与客户端匹配。

把 Agent Skill「swiftui-performance-audit」安装到我的项目：SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-5fb5e3df67e88e1c-Swiftui-Performance-Audit.html
请存为 .cursor/skills/swiftui-performance-audit/SKILL.md 或 .claude/skills/swiftui-performance-audit/SKILL.md，frontmatter 的 name 与 description 保持原样，不要改写。
该技能还带 scripts/、references/、assets/ 等文件，请从 https://github.com/dimillian/skills 取完整目录，不要只建一个 SKILL.md。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表，确认实际名称。

npx skills add 'https://github.com/dimillian/skills' --list

目标客户端安装范围

npx skills add 'https://github.com/dimillian/skills' --skill 'swiftui-performance-audit'

CLI 会交互选择目标 Agent，默认安装到项目；用户级安装使用 -g。先通过查看命令核对仓库内容，再用 npx skills list 检查已安装技能。

SKILL.md 原文可复制，不会改动源文件

---
name: swiftui-performance-audit
description: Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
---

# SwiftUI Performance Audit

## Quick start

Use this skill to diagnose SwiftUI performance issues from code first, then request profiling evidence when code review alone cannot explain the symptoms.

## Workflow

1. Classify the symptom: slow rendering, janky scrolling, high CPU, memory growth, hangs, or excessive view updates.
2. If code is available, start with a code-first review using `references/code-smells.md`.
3. If code is not available, ask for the smallest useful slice: target view, data flow, reproduction steps, and deployment target.
4. If code review is inconclusive or runtime evidence is required, guide the user through profiling with `references/profiling-intake.md`.
5. Summarize likely causes, evidence, remediation, and validation steps using `references/report-template.md`.

## 1. Intake

Collect:
- Target view or feature code.
- Symptoms and exact reproduction steps.
- Data flow: `@State`, `@Binding`, environment dependencies, and observable models.
- Whether the issue shows up on device or simulator, and whether it was observed in Debug or Release.

Ask the user to classify the issue if possible:
- CPU spike or battery drain
- Janky scrolling or dropped frames
- High memory or image pressure
- Hangs or unresponsive interactions
- Excessive or unexpectedly broad view updates

For the full profiling intake checklist, read `references/profiling-intake.md`.

## 2. Code-First Review

Focus on:
- Invalidation storms from broad observation or environment reads.
- Unstable identity in lists and `ForEach`.
- Heavy derived work in `body` or view builders.
- Layout thrash from complex hierarchies, `GeometryReader`, or preference chains.
- Large image decode or resize work on the main thread.
- Animation or transition work applied too broadly.

Use `references/code-smells.md` for the detailed smell catalog and fix guidance.

Provide:
- Likely root causes with code references.
- Suggested fixes and refactors.
- If needed, a minimal repro or instrumentation suggestion.

## 3. Guide the User to Profile

If code review does not explain the issue, ask for runtime evidence:
- A trace export or screenshots of the SwiftUI timeline and Time Profiler call tree.
- Device/OS/build configuration.
- The exact interaction being profiled.
- Before/after metrics if the user is comparing a change.

Use `references/profiling-intake.md` for the exact checklist and collection steps.

## 4. Analyze and Diagnose

- Map the evidence to the most likely category: invalidation, identity churn, layout thrash, main-thread work, image cost, or animation cost.
- Prioritize problems by impact, not by how easy they are to explain.
- Distinguish code-level suspicion from trace-backed evidence.
- Call out when profiling is still insufficient and what additional evidence would reduce uncertainty.

## 5. Remediate

Apply targeted fixes:
- Narrow state scope and reduce broad observation fan-out.
- Stabilize identities for `ForEach` and lists.
- Move heavy work out of `body` into derived state updated from inputs, model-layer precomputation, memoized helpers, or background preprocessing. Use `@State` only for view-owned state, not as an ad hoc cache for arbitrary computation.
- Use `equatable()` only when equality is cheaper than recomputing the subtree and the inputs are truly value-semantic.
- Downsample images before rendering.
- Reduce layout complexity or use fixed sizing where possible.

Use `references/code-smells.md` for examples, Observation-specific fan-out guidance, and remediation patterns.

## 6. Verify

Ask the user to re-run the same capture and compare with baseline metrics.
Summarize the delta (CPU, frame drops, memory peak) if provided.

## Outputs

Provide:
- A short metrics table (before/after if available).
- Top issues (ordered by impact).
- Proposed fixes with estimated effort.

Use `references/report-template.md` when formatting the final audit.

## References

- Profiling intake and collection checklist: `references/profiling-intake.md`
- Common code smells and remediation patterns: `references/code-smells.md`
- Audit output template: `references/report-template.md`
- Add Apple documentation and WWDC resources under `references/` as they are supplied by the user.
- Optimizing SwiftUI performance with Instruments: `references/optimizing-swiftui-performance-instruments.md`
- Understanding and improving SwiftUI performance: `references/understanding-improving-swiftui-performance.md`
- Understanding hangs in your app: `references/understanding-hangs-in-your-app.md`
- Demystify SwiftUI performance (WWDC23): `references/demystify-swiftui-performance-wwdc23.md`

阅读排版

name: swiftui-performance-audit description: Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.

SwiftUI Performance Audit

Quick start

Use this skill to diagnose SwiftUI performance issues from code first, then request profiling evidence when code review alone cannot explain the symptoms.

Workflow

Classify the symptom: slow rendering, janky scrolling, high CPU, memory growth, hangs, or excessive view updates.
If code is available, start with a code-first review using references/code-smells.md.
If code is not available, ask for the smallest useful slice: target view, data flow, reproduction steps, and deployment target.
If code review is inconclusive or runtime evidence is required, guide the user through profiling with references/profiling-intake.md.
Summarize likely causes, evidence, remediation, and validation steps using references/report-template.md.

1. Intake

Collect:

Target view or feature code.
Symptoms and exact reproduction steps.
Data flow: @State, @Binding, environment dependencies, and observable models.
Whether the issue shows up on device or simulator, and whether it was observed in Debug or Release.

Ask the user to classify the issue if possible:

CPU spike or battery drain
Janky scrolling or dropped frames
High memory or image pressure
Hangs or unresponsive interactions
Excessive or unexpectedly broad view updates

For the full profiling intake checklist, read references/profiling-intake.md.

2. Code-First Review

Focus on:

Invalidation storms from broad observation or environment reads.
Unstable identity in lists and ForEach.
Heavy derived work in body or view builders.
Layout thrash from complex hierarchies, GeometryReader, or preference chains.
Large image decode or resize work on the main thread.
Animation or transition work applied too broadly.

Use references/code-smells.md for the detailed smell catalog and fix guidance.

Provide:

Likely root causes with code references.
Suggested fixes and refactors.
If needed, a minimal repro or instrumentation suggestion.

3. Guide the User to Profile

If code review does not explain the issue, ask for runtime evidence:

A trace export or screenshots of the SwiftUI timeline and Time Profiler call tree.
Device/OS/build configuration.
The exact interaction being profiled.
Before/after metrics if the user is comparing a change.

Use references/profiling-intake.md for the exact checklist and collection steps.

4. Analyze and Diagnose

Map the evidence to the most likely category: invalidation, identity churn, layout thrash, main-thread work, image cost, or animation cost.
Prioritize problems by impact, not by how easy they are to explain.
Distinguish code-level suspicion from trace-backed evidence.
Call out when profiling is still insufficient and what additional evidence would reduce uncertainty.

5. Remediate

Apply targeted fixes:

Narrow state scope and reduce broad observation fan-out.
Stabilize identities for ForEach and lists.
Move heavy work out of body into derived state updated from inputs, model-layer precomputation, memoized helpers, or background preprocessing. Use @State only for view-owned state, not as an ad hoc cache for arbitrary computation.
Use equatable() only when equality is cheaper than recomputing the subtree and the inputs are truly value-semantic.
Downsample images before rendering.
Reduce layout complexity or use fixed sizing where possible.

Use references/code-smells.md for examples, Observation-specific fan-out guidance, and remediation patterns.

6. Verify

Ask the user to re-run the same capture and compare with baseline metrics. Summarize the delta (CPU, frame drops, memory peak) if provided.

Outputs