Guide Swiftui Performance Audit

Prisma-Labs-Dev/apple-skills/skills/guide-swiftui-performance-audit

作者 Prisma-Labs-Dev498626005e65783ebe8570a103b2335cf397768cMIT收录于 2026年10月9日更新于 2026年10月9日

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.

AI 生成的概览

通过代码审查审计 SwiftUI 运行时性能,并指导用户自行使用 Instruments 进行性能分析。

功能
该指南技能诊断 SwiftUI 性能问题,例如渲染缓慢、滚动卡顿、CPU 或内存占用过高、卡死以及视图更新过于频繁。它先基于代码审查,使用代码坏味道清单进行分析,当代码审查无法得出结论时再索取性能分析证据。最终产出按影响排序的审计结果,包含可能的根本原因、修复建议以及前后对比指标表。
适用场景
当 SwiftUI 应用出现渲染缓慢、掉帧、CPU 或内存压力过高、卡死或视图更新范围异常广泛时使用。也适用于需要结构化指导来采集 Instruments 跟踪数据,或需要一份书面审计报告的场景。
运行要求
无需脚本,仅包含说明与参考文档。需要目标视图或功能代码、症状与复现细节,以及可选的用户提供的 Instruments 跟踪数据或截图。性能分析由用户在 Xcode Instruments 中自行完成。

Guide Skill — This is an expert workflow/pattern guide, not API reference documentation. Originally from Dimillian/Skills by Thomas Ricouard. MIT License.

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

来源与署名

来源:Prisma-Labs-Dev/apple-skills位于skills/guide-swiftui-performance-audit提交4986260

许可证: MIT

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

举报或申请下架