swiftui-expert-skill
Use when writing, reviewing, or refactoring SwiftUI code for iOS or macOS, including state management, view composition, performance, Liquid Glass adoption, or Instruments `.trace` capture/analysis for hangs, hitches, CPU hotspots, or excessive view updates.
What this skill does
# SwiftUI Expert Skill
## Operating Rules
- Consult `references/latest-apis.md` at the start of every task to avoid deprecated APIs
- Prefer native SwiftUI APIs over UIKit/AppKit bridging unless bridging is necessary
- Focus on correctness and performance; do not enforce specific architectures (MVVM, VIPER, etc.)
- Encourage separating business logic from views for testability without mandating how
- Follow Apple's Human Interface Guidelines and API design patterns
- Only adopt Liquid Glass when explicitly requested by the user (see `references/liquid-glass.md`)
- Present performance optimizations as suggestions, not requirements
- Use `#available` gating with sensible fallbacks for version-specific APIs
## Task Workflow
### Review existing SwiftUI code
- Read the code under review and identify which topics apply
- Flag deprecated APIs (compare against `references/latest-apis.md`)
- Run the Topic Router below for each relevant topic
- Validate `#available` gating and fallback paths for iOS 26+ features
### Improve existing SwiftUI code
- Audit current implementation against the Topic Router topics
- Replace deprecated APIs with modern equivalents from `references/latest-apis.md`
- Refactor hot paths to reduce unnecessary state updates
- Extract complex view bodies into separate subviews
- Suggest image downsampling when `UIImage(data:)` is encountered (optional optimization, see `references/image-optimization.md`)
### Implement new SwiftUI feature
- Design data flow first: identify owned vs injected state
- Structure views for optimal diffing (extract subviews early)
- Apply correct animation patterns (implicit vs explicit, transitions)
- Use `Button` for all tappable elements; add accessibility grouping and labels
- Gate version-specific APIs with `#available` and provide fallbacks
### Record a new Instruments trace
Trigger when the user asks to "record a trace", "profile the app", "capture a session", etc. Full reference: `references/trace-recording.md`.
1. **Confirm target** — attach to a running app, launch an app, or record all processes? If the user didn't say, ask. List connected devices when useful:
```bash
python3 "${SKILL_DIR}/scripts/record_trace.py" --list-devices
```
2. **Pick a template based on target kind** — the `SwiftUI` template populates the SwiftUI lane on any **real device**: a physical iOS/iPadOS device **or the host Mac**. The only exception is the **iOS Simulator**, where the SwiftUI lane comes back empty — switch to `--template "Time Profiler"` in that case (still gives Time Profiler + Hangs + Animation Hitches). Always check `--list-devices`: `simulators` kind → `Time Profiler`; `devices` kind (real devices and the host Mac) → default `SwiftUI`. Full decision table in `references/trace-recording.md`.
3. **Start the recording**. For agent-driven sessions where the user says "I'll tell you when I'm done", start in the background and use a stop-file:
```bash
python3 "${SKILL_DIR}/scripts/record_trace.py" \
--device "<name|udid>" --attach "<AppName>" \
--stop-file /tmp/stop-trace --output ~/Desktop/session.trace
```
For interactive sessions, just tell the user to press Ctrl+C when done.
4. **Signal stop** — when the user says they've finished exercising the app, `touch /tmp/stop-trace`. The script cleanly SIGINTs xctrace and waits up to 60s for finalisation.
5. **Analyse** the resulting trace (flow into the "Trace-driven improvement" workflow below).
### Trace-driven improvement (Instruments `.trace` provided)
Trigger whenever the user's request references a `.trace` file. A target SwiftUI source file is **optional** — if given, cite specific lines; if not, recommend where to look based on view names and symbols the trace already reveals.
Full reference: `references/trace-analysis.md`. Summary of the composition pattern:
1. **Scope the analysis.** Ask yourself: does the user want the whole trace, or a slice?
- "focus on X / after X / between X and Y / during X" → **resolve to a window first** (see step 2).
- No scoping cue → analyse the whole trace.
2. **Resolve a window (only if the user scoped).** The parser exposes two discovery modes:
```bash
# Find a log that marks the start/end of the region of interest:
python3 "${SKILL_DIR}/scripts/analyze_trace.py" --trace <path> \
--list-logs --log-message-contains "loaded feed" --log-limit 5
# Or list os_signpost intervals (paired begin/end), filterable by name:
python3 "${SKILL_DIR}/scripts/analyze_trace.py" --trace <path> \
--list-signposts --signpost-name-contains "ImageDecode"
```
Both modes accept `--window START_MS:END_MS` to scope discovery. Pick the `time_ms` (for logs) or `start_ms`/`end_ms` (for signposts) that match the user's description. Build a window like `--window 10400:11700`.
3. **Run the main analysis** (with or without `--window`):
```bash
python3 "${SKILL_DIR}/scripts/analyze_trace.py" --trace <path> \
--json-only --top 10 [--window START_MS:END_MS]
```
4. **Interpret with `references/trace-analysis.md`** — key diagnostics:
- `main_running_coverage_pct` inside each correlation (<25% = blocked; ≥75% = CPU-bound).
- `swiftui-causes.top_sources` reveals *why* updates keep happening — high-edge-count sources like `UserDefaultObserver.send()` or wide `EnvironmentWriter` entries are structural invalidation bugs. Fixing one often collapses many downstream hot views.
5. **When a specific view shows as expensive, ask who's invalidating it.** Use `--fanin-for "<view name>"` to get the ranked list of source nodes driving the updates.
6. **Optionally ground in source.** If the user pointed at a file, read it and match view names / user-code symbols against identifiers there. If not, recommend which files to open based on the view names SwiftUI reported.
7. **Return a prioritised plan.** Cite evidence (coverage %, hot symbol, overlapping view, log timestamp, cause-graph edges) and route each recommendation to a Topic Router reference.
8. Only edit code if the user asked for edits.
### Topic Router
Consult the reference file for each topic relevant to the current task:
| Topic | Reference |
|-------|-----------|
| State management | `references/state-management.md` |
| View composition | `references/view-structure.md` |
| Performance | `references/performance-patterns.md` |
| Lists and ForEach | `references/list-patterns.md` |
| Layout | `references/layout-best-practices.md` |
| Sheets and navigation | `references/sheet-navigation-patterns.md` |
| ScrollView | `references/scroll-patterns.md` |
| Focus management | `references/focus-patterns.md` |
| Animations (basics) | `references/animation-basics.md` |
| Animations (transitions) | `references/animation-transitions.md` |
| Animations (advanced) | `references/animation-advanced.md` |
| Accessibility | `references/accessibility-patterns.md` |
| Swift Charts | `references/charts.md` |
| Charts accessibility | `references/charts-accessibility.md` |
| Image optimization | `references/image-optimization.md` |
| Liquid Glass (iOS 26+) | `references/liquid-glass.md` |
| macOS scenes | `references/macos-scenes.md` |
| macOS window styling | `references/macos-window-styling.md` |
| macOS views | `references/macos-views.md` |
| Text patterns | `references/text-patterns.md` |
| Deprecated API lookup | `references/latest-apis.md` |
| Previews | `references/previews.md` |
| Instruments trace analysis | `references/trace-analysis.md` |
| Instruments trace recording | `references/trace-recording.md` |
## Correctness Checklist
These are hard rules -- violations are always bugs:
- [ ] `@State` properties are `private`
- [ ] `@Binding` only where a child modifies parent state
- [ ] Passed values never declared as `@State` or `@StateObject` (they ignore updates)
- [ ] `@StateObject` for view-owned objects; `@ObservedObject` for injected
- [ ] iOS 17+: `@State` with `@Observable`; `@Bindable` for injected observables needing bindiRelated in Writing & Docs
jax-development
IncludedUse this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.
nature-article-writer
IncludedDrafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.
deckrd
IncludedDocument-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.
clinical-decision-support
IncludedGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
handling-sf-data
IncludedSalesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).
accelint-ac-to-playwright
IncludedConvert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.