Swiftui Performance Audit Dimillian

---
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."
category: engineering-core
source_repo: Dimillian/Skills
source_path: "swiftui-performance-audit/SKILL.md"
source_url: https://github.com/Dimillian/Skills/blob/HEAD/swiftui-performance-audit/SKILL.md
---


# 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`

---

**Source:** [`Dimillian/Skills`](https://github.com/Dimillian/Skills) → `swiftui-performance-audit/SKILL.md`