axiom-concurrency-profiling

charleswiltgen/axiom · updated Apr 8, 2026

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$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-concurrency-profiling
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summary

Profile and optimize Swift async/await code using Instruments.

skill.md

Concurrency Profiling — Instruments Workflows

Profile and optimize Swift async/await code using Instruments.

When to Use

Use when:

  • UI stutters during async operations
  • Suspecting actor contention
  • Tasks queued but not executing
  • Main thread blocked during async work
  • Need to visualize task execution flow

Don't use when:

  • Issue is pure CPU performance (use Time Profiler)
  • Memory issues unrelated to concurrency (use Allocations)
  • Haven't confirmed concurrency is the bottleneck

Swift Concurrency Template

What It Shows

Track Information
Swift Tasks Task lifetimes, parent-child relationships
Swift Actors Actor access, contention visualization
Thread States Blocked vs running vs suspended

Statistics

  • Running Tasks: Tasks currently executing
  • Alive Tasks: Tasks present at a point in time
  • Total Tasks: Cumulative count created

Color Coding

  • Blue: Task executing
  • Red: Task waiting (contention)
  • Gray: Task suspended (awaiting)

Workflow 1: Diagnose Main Thread Blocking

Symptom: UI freezes, main thread timeline full

  1. Profile with Swift Concurrency template
  2. Look at main thread → "Swift Tasks" lane
  3. Find long blue bars (task executing on main)
  4. Check if work could be offloaded

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
    }
}

Workflow 2: Find Actor Contention

Symptom: Tasks serializing unexpectedly, parallel work running sequentially

  1. Enable "Swift Actors" instrument
  2. Look for serialized access patterns
  3. Red = waiting, Blue = executing
  4. High red:blue ratio = contention problem

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:

  • Split actor into multiple (domain separation)
  • Use Mutex for hot paths (faster than actor hop)
  • Reduce actor scope (fewer isolated properties)

Workflow 3: Thread Pool Exhaustion

Symptom: Tasks queued but not executing, gaps in task execution

Cause: Blocking calls exhaust cooperative pool

  1. Look for gaps in task execution across all threads
  2. Check for blocking primitives
  3. Replace with async equivalents

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.

Workflow 4: Priority Inversion

Symptom: High-priority task waits for low-priority

  1. Inspect task priorities in Instruments
  2. Follow wait chains
  3. Ensure critical paths use appropriate priority
// ✅ Explicit priority for critical work
Task(priority: .userInitiated) {
    await criticalUIUpdate()
}

Thread Pool Model

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:

  • Each blocked thread holds memory + kernel structures
  • Limited threads means blocked = no progress
  • Pool exhaustion deadlocks the app

Quick Checks (Before Profiling)

Run these checks first:

  1. Is work actually async?

    • Look for suspension points (await)
    • Sync code in async function still blocks
  2. Holding locks across await?

    // ❌ Deadlock risk
    mutex.withLock {
        await something()  // Never!
    }
    
  3. 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) }
        }
    }
    
  4. DispatchSemaphore in async context?

    • Always unsafe — use withCheckedContinuation instead

Common Issues Summary

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 vs Unsafe Primitives

Safe with cooperative pool:

  • await, actors, task groups
  • os_unfair_lock, NSLock (short critical sections)
  • Mutex (iOS 18+)

Unsafe (violate forward progress):

  • DispatchSemaphore.wait()
  • pthread_cond_wait
  • Sync file/network I/O
  • Thread.sleep() in Task

Resources

WWDC: 2022-110350, 2021-10254

Docs: /xcode/improving-app-responsiveness

Skills: axiom-swift-concurrency, axiom-performance-profiling, axiom-synchronization, axiom-lldb (interactive thread state inspection)

how to use axiom-concurrency-profiling

How to use axiom-concurrency-profiling on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add axiom-concurrency-profiling
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-concurrency-profiling

The skills CLI fetches axiom-concurrency-profiling from GitHub repository charleswiltgen/axiom and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/axiom-concurrency-profiling

Reload or restart Cursor to activate axiom-concurrency-profiling. Access the skill through slash commands (e.g., /axiom-concurrency-profiling) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.662 reviews
  • Kabir Okafor· Dec 28, 2024

    I recommend axiom-concurrency-profiling for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Neel Harris· Dec 20, 2024

    axiom-concurrency-profiling fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Olivia Reddy· Dec 20, 2024

    axiom-concurrency-profiling has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aanya Nasser· Dec 12, 2024

    Useful defaults in axiom-concurrency-profiling — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Daniel Chen· Dec 8, 2024

    We added axiom-concurrency-profiling from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kabir Desai· Nov 19, 2024

    Solid pick for teams standardizing on skills: axiom-concurrency-profiling is focused, and the summary matches what you get after install.

  • Noor Mehta· Nov 11, 2024

    Useful defaults in axiom-concurrency-profiling — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aisha Lopez· Nov 11, 2024

    We added axiom-concurrency-profiling from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Alexander Li· Nov 3, 2024

    axiom-concurrency-profiling has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Alexander Thomas· Oct 22, 2024

    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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