MCPInstall

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
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads swiftui-performance automatically when relevant.

  3. 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.

Gen Agent Trust Hub PassSAFE ·The skill provides guidelines and reference documentation for diagnosing and optimizing SwiftUI performance. It contains no executable code or external tool calls, and no security risks were found.
Socket PassNo alerts
Snyk PassLOW ·Risk: LOW · No issues
Runlayer PassLOW ·1/5 files flagged
ZeroLeaks PassNONE ·Score: 93/100 · 2 sections analyzed

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

  • 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/@Observable closer to leaf views).
  • Stabilize identities for ForEach and lists.
  • Move heavy work out of body into model-layer precomputation, an explicit derived value updated when its inputs change, a memoized helper, or background processing. Use @State only 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)

SmellEvidence to seekTargeted fix
Formatter, sort, filter, or decode in bodyLong/frequent body updates with matching call-tree costRecompute when inputs change; downsample/decode off the main actor
UUID() or unstable id: \.selfRecreated rows, lost state, excess updatesUse stable model identity
Root if/else swapsState reset or update spikes when toggledLocalize conditional content/modifiers when semantics allow
Broad model readsMany unrelated views update togetherPass narrow values or move reads into focused child views
Geometry writes during layoutRepeating layout/update cycleThreshold 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 onAppear because of prefetching. Do not make onAppear the only setup point for data a row needs to render.
  • Treat onAppear and onDisappear as visibility signals, not lifetime guarantees.
  • Filter data before ForEach; avoid if branches that make each element produce zero or one row.
  • Keep each ForEach element to a constant number of top-level subviews. Wrap row contents in a stable container if needed. Use -LogForEachSlowPath YES while 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 Layout before 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

  1. Profiling Debug builds. Debug builds include extra runtime checks and disable optimizations, producing misleading perf data. Profile Release builds on a real device.
  2. Observing an entire model when only one property is needed. Break large @Observable models into focused ones, or use computed properties/closures to narrow observation scope.
  3. 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.
  4. Calling DateFormatter() or NumberFormatter() inside body. These are expensive to create. Make them static or move them outside the view.
  5. 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.
  6. Large flat List without identifiers. Use id: or make items Identifiable so SwiftUI can diff efficiently instead of rebuilding the entire list.
  7. Unnecessary @State wrapper objects. Wrapping a simple value type in a class for @State defeats value semantics. Use plain @State with structs.
  8. Blocking MainActor with 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; reserve Task.detached for cases where you intentionally break actor inheritance and handle cancellation yourself.

Review Checklist

  • No DateFormatter/NumberFormatter allocations inside body
  • Large lists use Identifiable items or explicit id:
  • @Observable models 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 onAppear as 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
  • @State is 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
  • @Observable view models are @MainActor-isolated; types crossing concurrency boundaries are Sendable

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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