swiftui-performance-audit
$
npx mdskill add TerminalSkills/skills/swiftui-performance-auditDiagnose SwiftUI performance bottlenecks and optimize rendering.
- Identifies slow rendering, janky scrolling, and excessive view updates.
- Integrates with code review and profiling tools for evidence.
- Decides actions by classifying symptoms and requesting runtime data.
- Delivers summaries of causes, evidence, and remediation steps.
SKILL.md
.github/skills/swiftui-performance-auditView on GitHub ↗
---
name: swiftui-performance-audit
description: >-
Audit and optimize SwiftUI runtime performance. Use when: diagnosing slow rendering, janky scrolling, excessive view updates, or high CPU/memory usage in SwiftUI apps.
license: MIT
compatibility: "SwiftUI apps (iOS/macOS)"
metadata:
author: terminal-skills
version: "1.0.0"
category: development
tags: [swiftui, performance, profiling, optimization, ios]
use-cases:
- "Diagnose and fix slow SwiftUI rendering"
- "Audit view hierarchy for unnecessary redraws and layout thrash"
agents: [claude-code, openai-codex, gemini-cli, cursor]
---
# 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`
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