axiom-background-processing-ref▌
charleswiltgen/axiom · updated Apr 8, 2026
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Complete API reference for iOS background execution, with code examples from WWDC sessions.
Background Processing Reference
Complete API reference for iOS background execution, with code examples from WWDC sessions.
Related skills: axiom-background-processing (decision trees, patterns), axiom-background-processing-diag (troubleshooting)
Part 1: BGTaskScheduler Registration
Info.plist Configuration
<!-- Required: List all task identifiers -->
<key>BGTaskSchedulerPermittedIdentifiers</key>
<array>
<string>com.yourapp.refresh</string>
<string>com.yourapp.maintenance</string>
<!-- Wildcard for dynamic identifiers (iOS 26+) -->
<string>com.yourapp.export.*</string>
</array>
<!-- Required: Enable background modes -->
<key>UIBackgroundModes</key>
<array>
<!-- For BGAppRefreshTask -->
<string>fetch</string>
<!-- For BGProcessingTask -->
<string>processing</string>
</array>
Register Handler
import BackgroundTasks
func application(
_ application: UIApplication,
didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey: Any]?
) -> Bool {
// Register BEFORE returning from didFinishLaunching
BGTaskScheduler.shared.register(
forTaskWithIdentifier: "com.yourapp.refresh",
using: nil // nil = system creates serial background queue
) { task in
self.handleAppRefresh(task: task as! BGAppRefreshTask)
}
BGTaskScheduler.shared.register(
forTaskWithIdentifier: "com.yourapp.maintenance",
using: nil
) { task in
self.handleMaintenance(task: task as! BGProcessingTask)
}
return true
}
Parameters:
forTaskWithIdentifier: Must match Info.plist exactly (case-sensitive)using: DispatchQueue for handler callback; nil = system creates onelaunchHandler: Called when task is launched; receives BGTask subclass
Registration Timing
From WWDC 2019-707:
"You do this by registering a launch handler before your application finishes launching"
Register in:
- ✅
application(_:didFinishLaunchingWithOptions:)beforereturn true - ❌ Not in viewDidLoad, button handlers, or async callbacks
Part 2: BGAppRefreshTask
Purpose
Keep app content fresh throughout the day. System launches app based on user usage patterns.
Runtime
~30 seconds (same as legacy background fetch)
Scheduling
func scheduleAppRefresh() {
let request = BGAppRefreshTaskRequest(identifier: "com.yourapp.refresh")
// earliestBeginDate = MINIMUM delay (not exact time)
// System decides actual time based on usage patterns
request.earliestBeginDate = Date(timeIntervalSinceNow: 15 * 60)
do {
try BGTaskScheduler.shared.submit(request)
} catch BGTaskScheduler.Error.notPermitted {
// Background App Refresh disabled in Settings
} catch BGTaskScheduler.Error.tooManyPendingTaskRequests {
// Too many pending requests for this identifier
} catch BGTaskScheduler.Error.unavailable {
// Background tasks not available (Simulator, etc.)
} catch {
print("Schedule failed: \(error)")
}
}
// Schedule when app enters background
func applicationDidEnterBackground(_ application: UIApplication) {
scheduleAppRefresh()
}
Handler
func handleAppRefresh(task: BGAppRefreshTask) {
// 1. Set expiration handler FIRST
task.expirationHandler = { [weak self] in
self?.currentOperation?.cancel()
}
// 2. Schedule NEXT refresh (continuous pattern)
scheduleAppRefresh()
// 3. Perform work
let operation = fetchLatestContentOperation()
currentOperation = operation
operation.completionBlock = {
// 4. Signal completion (REQUIRED)
task.setTaskCompleted(success: !operation.isCancelled)
}
operationQueue.addOperation(operation)
}
BGAppRefreshTaskRequest Properties
| Property | Type | Description |
|---|---|---|
identifier |
String | Must match Info.plist |
earliestBeginDate |
Date? | Minimum delay before execution |
Part 3: BGProcessingTask
Purpose
Deferrable maintenance work (database cleanup, ML training, backups). Runs at system-friendly times, typically overnight when charging.
Runtime
Several minutes (significantly longer than refresh tasks)
Scheduling with Constraints
func scheduleMaintenanceIfNeeded() {
// Only schedule if work is needed
guard Date().timeIntervalSince(lastMaintenanceDate) > 7 * 24 * 3600 else {
return
}
let request = BGProcessingTaskRequest(identifier: "com.yourapp.maintenance")
// CRITICAL for CPU-intensive work
request.requiresExternalPower = true
// Optional: Need network for cloud sync
request.requiresNetworkConnectivity = true
// Keep within 1 week — longer may be skipped
// request.earliestBeginDate = ...
do {
try BGTaskScheduler.shared.submit(request)
} catch {
print("Schedule failed: \(error)")
}
}
Handler with Progress Checkpointing
func handleMaintenance(task: BGProcessingTask) {
var shouldContinue = true
task.expirationHandler = {
shouldContinue = false
}
Task {
for item in workItems {
How to use axiom-background-processing-ref on Cursor
AI-first code editor with Composer
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-background-processing-ref
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches axiom-background-processing-ref from GitHub repository charleswiltgen/axiom and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate axiom-background-processing-ref. Access the skill through slash commands (e.g., /axiom-background-processing-ref) 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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★64 reviews- ★★★★★Ganesh Mohane· Dec 28, 2024
I recommend axiom-background-processing-ref for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ren Park· Dec 28, 2024
Solid pick for teams standardizing on skills: axiom-background-processing-ref is focused, and the summary matches what you get after install.
- ★★★★★Mei Bansal· Dec 16, 2024
Registry listing for axiom-background-processing-ref matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kofi Khan· Dec 16, 2024
axiom-background-processing-ref has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Benjamin Mehta· Dec 12, 2024
axiom-background-processing-ref is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Xiao Dixit· Dec 12, 2024
axiom-background-processing-ref fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Diya Sethi· Dec 12, 2024
Useful defaults in axiom-background-processing-ref — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yash Thakker· Nov 27, 2024
Useful defaults in axiom-background-processing-ref — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakshi Patil· Nov 19, 2024
Solid pick for teams standardizing on skills: axiom-background-processing-ref is focused, and the summary matches what you get after install.
- ★★★★★Diya Kapoor· Nov 19, 2024
I recommend axiom-background-processing-ref for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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