Swiftui Performance Audit

作者 dimillian05ba982bfeb0無授權條款3.9K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫6 個月前更新

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 產生的概覽

透過程式碼審查與架構分析稽核 SwiftUI 執行效能,並引導使用者以 Instruments 進行效能剖析。

功能
診斷 SwiftUI 效能問題症狀,例如渲染緩慢、捲動卡頓、CPU 或記憶體用量過高、卡住,以及檢視更新過於頻繁。它先依程式碼異味清單進行程式碼優先審查,當程式碼審查無法得出結論時,再引導使用者以 Instruments 進行效能剖析。最終產出稽核報告,包含可能原因、依影響排序的問題、修正步驟與驗證指引。
適用情境
當 SwiftUI 應用程式出現渲染緩慢、掉幀、CPU 或記憶體壓力過高、卡住,或檢視更新範圍異常擴大時使用。也適合在效能剖析之前或同時,對 SwiftUI 的狀態、識別、版面配置、影像與動畫成本進行結構化程式碼審查。
執行需求
不需要指令碼,僅包含說明與參考文件。代理需要能存取目標 SwiftUI 程式碼或其最小片段。效能剖析證據由使用者在 Xcode Instruments 中蒐集,因此可能需要使用者提供 trace 匯出檔或截圖,以及裝置、作業系統與建置設定資訊。

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

來源與署名

來源:dimillian/skills位於swiftui-performance-audit提交05ba982

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