
swiftui-performance
Profile, diagnose, and remediate SwiftUI runtime performance using code review, Instruments, and repeatable measurements. Use when a SwiftUI screen renders slowly, scrolling or animations hitch, view bodies update excessively, list identity churns, layout work spikes, or broad Observation dependencies raise CPU cost. Covers evidence-based triage, SwiftUI Instruments lanes, lazy-container guardrails, state lifetime, and before/after verification.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/dpearson2699/swift-ios-skills --skill swiftui-performance- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads swiftui-performance automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
SwiftUI Performance
Audit SwiftUI view performance from a reproducible symptom to measured
remediation. Route animation design to swiftui-animation, production telemetry
to metrickit, ownership/leak analysis to ios-memgraph-analysis, navigation
behavior to swiftui-navigation, state architecture to swiftui-patterns, and
layout construction to swiftui-layout-components.
Contents
- Workflow Decision Tree
- 1. Code-First Review
- 2. Guide the User to Profile
- 3. Analyze and Diagnose
- 4. Remediate
- Common Code Smells (and Fixes)
- 5. Verify
- Outputs
- Instruments Profiling
- Identity and Lifetime
- Lazy Loading Patterns
- State and Observation Optimization
- Common Mistakes
- Review Checklist
- References
Workflow Decision Tree
- Code supplied: review it first and label findings as hypotheses.
- Symptoms only: collect the smallest relevant view, data flow, reproduction, device, OS, and build configuration.
- Inconclusive review: collect a trace or lane screenshots before prescribing a broad refactor.
Use this triage list for both code and trace analysis:
- Broad state dependencies or invalidation storms
- Unstable list identity or root conditional swapping
- Formatting, sorting, decoding, or synchronous I/O in
body - Layout/geometry feedback loops and oversized images
- Implicit animation applied to a large hierarchy
1. Code-First Review
Map each suspect from the triage list to exact code. Report likely causes with code references, but label them code-backed hypotheses until a trace confirms cost. Propose a minimal repro or measurement when evidence is missing.
2. Guide the User to Profile
Use the SwiftUI Instruments template on a Release build and real device when possible. Reproduce the exact interaction, capturing SwiftUI lanes, Time Profiler, and Hangs/Hitches as relevant. Ask for the trace or screenshots of the lanes and call tree.
3. Analyze and Diagnose
Apply the same triage list to trace evidence. Correlate long or frequent SwiftUI updates with the Time Profiler call tree and the reproduced interaction. Separate trace-backed findings from code-backed hypotheses and name the next measurement that would resolve remaining uncertainty.
4. Remediate
Apply targeted fixes:
- Narrow state scope (
@State/@Observablecloser to leaf views). - Stabilize identities for
ForEachand lists. - Move heavy work out of
bodyinto model-layer precomputation, an explicit derived value updated when its inputs change, a memoized helper, or background processing. Use@Stateonly when the view owns both the value and its update lifecycle; it is not a generic cache for arbitrary computation. - Use
equatable()only when equality is cheaper than recomputing the subtree and the compared inputs have stable value semantics. - Downsample images before rendering.
- Reduce layout complexity or use fixed sizing where possible.
Common Code Smells (and Fixes)
| Smell | Evidence to seek | Targeted fix |
|---|---|---|
Formatter, sort, filter, or decode in body | Long/frequent body updates with matching call-tree cost | Recompute when inputs change; downsample/decode off the main actor |
UUID() or unstable id: \.self | Recreated rows, lost state, excess updates | Use stable model identity |
Root if/else swaps | State reset or update spikes when toggled | Localize conditional content/modifiers when semantics allow |
| Broad model reads | Many unrelated views update together | Pass narrow values or move reads into focused child views |
| Geometry writes during layout | Repeating layout/update cycle | Threshold changes or replace the feedback path with stable layout |
5. 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.
Instruments Profiling
Use the SwiftUI template in Instruments (Cmd+I to profile). Current SwiftUI lanes include Update Groups, Long View Body Updates, Long Representable Updates / Representable Updates, Other Long Updates / Other Updates, and the Cause & Effect Graph. Correlate those with Time Profiler and Hangs/Hitches.
Add Self._printChanges() in debug builds to log which property triggered a view update:
var body: some View {
#if DEBUG
let _ = Self._printChanges() // "MyView: @self, _count changed."
#endif
Text("Count: \(count)")
}
See references/optimizing-swiftui-performance-instruments.md for the full profiling workflow.
Identity and Lifetime
Identity controls view lifetime and state. Use stable model IDs in repeated
content and reserve .id(_:) changes for intentional resets. Prefer
@ViewBuilder or generic composition over AnyView in profiled hot rows. Treat
root conditional branches as suspects—not automatic defects—when evidence shows
state churn or expensive recreation.
Text(title)
.foregroundStyle(isHighlighted ? .yellow : .primary)
ForEach(items) { item in
Row(item: item).id(item.stableID)
}
Lazy Loading Patterns
Use lazy containers when profiling shows eager construction, layout, or update
work is material; there is no universal item-count threshold. Route grid/list
construction choices to swiftui-layout-components.
Guardrails:
- Off-screen views are removed from the lazy stack. SwiftUI may keep them briefly, then delete the views and their view-local state.
- Persist important row state outside the row view if it must survive scrolling away.
- Body and layout work can happen before
onAppearbecause of prefetching. Do not makeonAppearthe only setup point for data a row needs to render. - Treat
onAppearandonDisappearas visibility signals, not lifetime guarantees. - Filter data before
ForEach; avoidifbranches that make each element produce zero or one row. - Keep each
ForEachelement to a constant number of top-level subviews. Wrap row contents in a stable container if needed. Use-LogForEachSlowPath YESwhile debugging list/table slow paths. - Avoid absolute content-size or content-offset assumptions; lazy stacks estimate off-screen sizes.
- Avoid geometry feedback loops in lazy rows. Prefer stable sizing, layout primitives, or a custom
Layoutbefore feeding geometry changes back into row state.
State and Observation Optimization
Observation tracks properties read during view evaluation. Reduce fan-out by passing narrow derived values or moving reads into focused child views.
// Split reads into child views so each tracks only what it renders.
struct ProfileView: View {
let model: ProfileModel
var body: some View {
VStack {
NameRow(model: model) // only tracks name
EmailRow(model: model) // only tracks email
AvatarView(model: model) // only tracks avatar
SettingsForm(model: model) // only tracks settings
}
}
}
Cheap computed values can remain derived; expensive transformations need an
explicit owner, input set, and refresh trigger. Do not add view models as a
performance ritual—measure first and route general state design to
swiftui-patterns.
Common Mistakes
- Profiling Debug builds. Debug builds include extra runtime checks and disable optimizations, producing misleading perf data. Profile Release builds on a real device.
- Observing an entire model when only one property is needed. Break large
@Observablemodels into focused ones, or use computed properties/closures to narrow observation scope. - Using geometry feedback inside ScrollView items. GeometryReader or noisy geometry state can force repeated layout. Prefer stable sizing, custom layout, or narrowly scoped
.onGeometryChange(iOS 16+) with thresholds. - Calling
DateFormatter()orNumberFormatter()insidebody. These are expensive to create. Make them static or move them outside the view. - Animating non-equatable state. If SwiftUI cannot determine equality, it redraws every frame. Conform state to
Equatable, then use.animation(_:value:)for simple value-bound changes or.animation(_:body:)for narrower modifier-scoped implicit animation. - Large flat
Listwithout identifiers. Useid:or make itemsIdentifiableso SwiftUI can diff efficiently instead of rebuilding the entire list. - Unnecessary
@Statewrapper objects. Wrapping a simple value type in a class for@Statedefeats value semantics. Use plain@Statewith structs. - Blocking
MainActorwith synchronous I/O. File reads, JSON parsing of large payloads, and image decoding should happen off the main actor. Prefer nonisolated async helpers or dedicated actors; reserveTask.detachedfor cases where you intentionally break actor inheritance and handle cancellation yourself.
Review Checklist
- No
DateFormatter/NumberFormatterallocations insidebody - Large lists use
Identifiableitems or explicitid: -
@Observablemodels expose only the properties views actually read - Heavy computation is off
MainActor(image processing, parsing) - Lazy rows have stable identity, constant top-level row shape, and prefiltered data
- Geometry changes in scroll rows are thresholded and do not feed broad state
- Row rendering does not depend on
onAppearas the only setup point - Implicit animations use
.animation(_:value:)for value-bound changes or.animation(_:body:)for narrower modifier scope - No synchronous network/file I/O on the main thread
- Profiling done on Release build, real device
-
@Stateis not used as an unspecified cache; every derived value has an explicit owner and refresh trigger -
equatable()is used only when comparison is cheaper than recomputation and inputs have stable value semantics - Findings distinguish code-backed hypotheses from trace-backed evidence
-
@Observableview models are@MainActor-isolated; types crossing concurrency boundaries areSendable
References
- Demystify SwiftUI performance (WWDC23): references/demystify-swiftui-performance-wwdc23.md
- Optimizing SwiftUI performance with Instruments: references/optimizing-swiftui-performance-instruments.md
- Understanding hangs in your app: references/understanding-hangs-in-your-app.md
- Understanding and improving SwiftUI performance: references/understanding-improving-swiftui-performance.md
- WWDC transcript sources: references/wwdc-session-sources.md
FAQ
What does the swiftui-performance skill do?
Profile, diagnose, and remediate SwiftUI runtime performance using code review, Instruments, and repeatable measurements. Use when a SwiftUI screen renders slowly, scrolling or animations hitch, view bodies update excessively, list identity churns, layout work spikes, or broad Observation dependencies raise CPU cost. Covers evidence-based triage, SwiftUI Instruments lanes, lazy-container guardrails, state lifetime, and before/after verification.
How do I install swiftui-performance?
Run npx skills add https://github.com/dpearson2699/swift-ios-skills --skill swiftui-performance in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/swiftui-performance/ (personal) or .claude/skills/swiftui-performance/ (project).
Which AI agents can use swiftui-performance?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is swiftui-performance safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed; Runlayer passed; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains swiftui-performance?
It is published by dpearson2699 in dpearson2699/swift-ios-skills. It has 4,644 recorded installs.
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