Profile and optimize Swift async/await code using Instruments.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionaxiom-concurrency-profilingExecute the skills CLI command in your project's root directory to begin installation:
Fetches axiom-concurrency-profiling from charleswiltgen/axiom and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate axiom-concurrency-profiling. Access via /axiom-concurrency-profiling in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Profile and optimize Swift async/await code using Instruments.
✅ Use when:
❌ Don't use when:
| Track | Information |
|---|---|
| Swift Tasks | Task lifetimes, parent-child relationships |
| Swift Actors | Actor access, contention visualization |
| Thread States | Blocked vs running vs suspended |
Symptom: UI freezes, main thread timeline full
Solution patterns:
// ❌ Heavy work on MainActor
@MainActor
class ViewModel: ObservableObject {
func process() {
let result = heavyComputation() // Blocks UI
self.data = result
}
}
// ✅ Offload heavy work
@MainActor
class ViewModel: ObservableObject {
func process() async {
let result = await Task.detached {
heavyComputation()
}.value
self.data = result
}
}
Symptom: Tasks serializing unexpectedly, parallel work running sequentially
Solution patterns:
// ❌ All work serialized through actor
actor DataProcessor {
func process(_ data: Data) -> Result {
heavyProcessing(data) // All callers wait
}
}
// ✅ Mark heavy work as nonisolated
actor DataProcessor {
nonisolated func process(_ data: Data) -> Result {
heavyProcessing(data) // Runs in parallel
}
func storeResult(_ result: Result) {
// Only actor state access serialized
}
}
More fixes:
Symptom: Tasks queued but not executing, gaps in task execution
Cause: Blocking calls exhaust cooperative pool
Common culprits:
// ❌ Blocks cooperative thread
Task {
semaphore.wait() // NEVER do this
// ...
semaphore.signal()
}
// ❌ Synchronous file I/O in async context
Task {
let data = Data(contentsOf: fileURL) // Blocks
}
// ✅ Use async APIs
Task {
let (data, _) = try await URLSession.shared.data(from: fileURL)
}
Debug flag:
SWIFT_CONCURRENCY_COOPERATIVE_THREAD_BOUNDS=1
Detects unsafe blocking in async context.
Symptom: High-priority task waits for low-priority
// ✅ Explicit priority for critical work
Task(priority: .userInitiated) {
await criticalUIUpdate()
}
Swift uses a cooperative thread pool matching CPU core count:
| Aspect | GCD | Swift Concurrency |
|---|---|---|
| Threads | Grows unbounded | Fixed to core count |
| Blocking | Creates new threads | Suspends, frees thread |
| Dependencies | Hidden | Runtime-tracked |
| Context switch | Full kernel switch | Lightweight continuation |
Why blocking is catastrophic:
Run these checks first:
Is work actually async?
await)Holding locks across await?
// ❌ Deadlock risk
mutex.withLock {
await something() // Never!
}
Tasks in tight loops?
// ❌ Overhead may exceed benefit
for item in items {
Task { process(item) }
}
// ✅ Structured concurrency
await withTaskGroup(of: Void.self) { group in
for item in items {
group.addTask { process(item) }
}
}
DispatchSemaphore in async context?
withCheckedContinuation instead| Issue | Symptom in Instruments | Fix |
|---|---|---|
| MainActor overload | Long blue bars on main | Task.detached, nonisolated |
| Actor contention | High red:blue ratio | Split actors, use nonisolated |
| Thread exhaustion | Gaps in all threads | Remove blocking calls |
| Priority inversion | High-pri waits for low-pri | Check task priorities |
| Too many tasks | Task creation overhead | Use task groups |
Safe with cooperative pool:
await, actors, task groupsos_unfair_lock, NSLock (short critical sections)Mutex (iOS 18+)Unsafe (violate forward progress):
DispatchSemaphore.wait()pthread_cond_waitThread.sleep() in TaskWWDC: 2022-110350, 2021-10254
Docs: /xcode/improving-app-responsiveness
Skills: axiom-swift-concurrency, axiom-performance-profiling, axiom-synchronization, axiom-lldb (interactive thread state inspection)
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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I recommend axiom-concurrency-profiling for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
axiom-concurrency-profiling fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
axiom-concurrency-profiling has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in axiom-concurrency-profiling — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added axiom-concurrency-profiling from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: axiom-concurrency-profiling is focused, and the summary matches what you get after install.
Useful defaults in axiom-concurrency-profiling — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added axiom-concurrency-profiling from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
axiom-concurrency-profiling has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: axiom-concurrency-profiling is focused, and the summary matches what you get after install.
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