Energy issues manifest as battery drain, hot devices, and poor App Store reviews. Core principle: Measure before optimizing. Use Power Profiler to identify the dominant subsystem (CPU/GPU/Network/Location/Display), then apply targeted fixes.
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.cursor/skills/axiom-energy
Restart Cursor to activate axiom-energy. Access via /axiom-energy in your agent's command palette.
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Security Notice
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Energy issues manifest as battery drain, hot devices, and poor App Store reviews. Core principle: Measure before optimizing. Use Power Profiler to identify the dominant subsystem (CPU/GPU/Network/Location/Display), then apply targeted fixes.
Key insight: Developers often don't know where to START auditing. This skill provides systematic diagnosis, not guesswork.
Requirements: iOS 26+, Xcode 26+, Power Profiler in Instruments
Example Prompts
Real questions developers ask that this skill answers:
1. "My app is always at the top of Battery Settings. How do I find what's draining power?"
β The skill covers Power Profiler workflow to identify dominant subsystem and targeted fixes
2. "Users report my app makes their phone hot. Where do I start debugging?"
β The skill provides decision tree: CPU vs GPU vs Network diagnosis with specific patterns
3. "I have timers and location updates. Are they causing battery drain?"
β The skill covers timer tolerance, location accuracy trade-offs, and audit checklists
4. "My app drains battery in the background even when users aren't using it."
β The skill covers background execution patterns, BGTasks, and EMRCA principles
5. "How do I measure if my optimization actually improved battery life?"
β The skill demonstrates before/after Power Profiler comparison workflow
Red Flags β High Energy Likely
If you see ANY of these, suspect energy inefficiency:
Battery Settings: Your app consistently at top of battery consumers
Device temperature: Phone gets warm during normal app use
User reviews: Mentions of "battery drain", "hot phone", "kills my battery"
Xcode Energy Gauge: Shows sustained high or very high impact
Background runtime: App runs longer than expected when not visible
Network activity: Frequent small requests instead of batched operations
Location icon: Appears in status bar when app shouldn't need location
Difference from normal energy use
Normal: App uses energy during active use, minimal when backgrounded
Problem: App uses significant energy even when user isn't interacting
Mandatory First Steps
ALWAYS run Power Profiler FIRST before optimizing code:
Step 1: Record a Power Trace (5 minutes)
1. Connect iPhone wirelessly to Xcode (wireless debugging)
2. Xcode β Product β Profile (Cmd+I)
3. Select Blank template
4. Click "+" β Add "Power Profiler" instrument
5. Optional: Add "CPU Profiler" for correlation
6. Click Record
7. Use your app normally for 2-3 minutes
8. Click Stop
Why wireless: When device is charging via cable, power metrics show 0. Use wireless debugging for accurate readings.
Step 2: Identify Dominant Subsystem
Expand the Power Profiler track and examine per-app metrics:
Lane
Meaning
High Value Indicates
CPU Power Impact
Processor activity
Computation, timers, parsing
GPU Power Impact
Graphics rendering
Animations, blur, Metal
Display Power Impact
Screen usage
Brightness, always-on content
Network Power Impact
Radio activity
Requests, downloads, polling
Look for: Which subsystem shows highest sustained values during your app's usage.
Step 3: Branch to Subsystem-Specific Fixes
Once you identify the dominant subsystem, use the decision trees below.
What this tells you
CPU dominant β Check timers, polling, JSON parsing, eager loading
Network dominant β Check request frequency, polling vs push
Display dominant β Check Dark Mode, brightness, screen-on time
Location (shown in CPU) β Check accuracy, update frequency
Why diagnostics first
Finding root cause with Power Profiler: 15-20 minutes
Guessing and testing random optimizations: 4+ hours, often wrong subsystem
Energy Decision Tree
User reports energy issue?
β
ββ CPU Power Impact dominant?
β ββ Continuous high impact?
β β ββ Timers running? β Pattern 1: Timer Efficiency
β β ββ Polling data? β Pattern 2: Push vs Poll
β β ββ Processing in loop? β Pattern 3: Lazy Loading
β ββ Spikes during specific actions?
β β ββ JSON parsing? β Cache parsed results
β β ββ Image processing? β Move to background, cache
β β ββ Database queries? β Index, batch, prefetch
β ββ High background CPU?
β ββ Location updates? β Pattern 4: Location Efficiency
β ββ BGTasks running too long? β Pattern 5: Background Execution
β ββ Audio session active? β Stop when not playing
β
ββ Network Power Impact dominant?
β ββ Many small requests?
β β ββ Batch into fewer large requests
β ββ Polling pattern detected?
β β ββ Convert to push notifications β Pattern 2
β ββ Downloads in foreground?
β β ββ Use discretionary background URLSession
β ββ High cellular usage?
β ββ Defer to WiFi when possible
β
ββ GPU Power Impact dominant?
β ββ Continuous animations?
β β ββ Stop when view not visible
β ββ Blur effects (UIVisualEffectView)?
β β ββ Reduce or remove, use solid colors
β ββ High frame rate animations?
β β ββ Audit secondary frame rates β Pattern 6
β ββ Metal rendering?
β ββ Implement frame limiting
β
ββ Display Power Impact dominant?
β ββ Light backgrounds on OLED?
β β ββ Implement Dark Mode (up to 70% savings)
β ββ High brightness content?
β β ββ Use darker UI elements
β ββ Screen always on?
β ββ Allow screen to sleep when appropriate
β
ββ Location causing drain? (check CPU lane + location icon)
ββ Continuous updates?
β ββ Switch to significant-change monitoring
ββ High accuracy (kCLLocationAccuracyBest)?
β ββ Reduce to kCLLocationAccuracyHundredMeters
ββ Background location?
ββ Evaluate if truly needed β Pattern 4
Common Energy Patterns (With Fixes)
Pattern 1: Timer Efficiency
Problem: Timers wake the CPU from idle states, consuming significant energy.
β Anti-Pattern β Timer without tolerance
// BAD: Timer fires exactly every 1.0 seconds// Prevents system from batching with other timersTimer.scheduledTimer(withTimeInterval:1.0, repeats:true){_inself.updateUI()}
β Fix β Set tolerance for timer batching
// GOOD: 10% tolerance allows system to batch timerslet timer =Timer.scheduledTimer(withTimeInterval:1.0, repeats:true){_inself.updateUI()}timer.tolerance =0.1// 10% tolerance minimum// BETTER: Use Combine Timer with toleranceTimer.publish(every:1.0, tolerance:0.1, on:.main,in:.default).autoconnect().sink {[weakself]_inself?.updateUI()}.store(in:&cancellables)
β Best β Use event-driven instead of polling
// BEST: Don't use timer at all β react to eventsNotificationCenter.default.publisher(for:.dataDidUpdate).sink {[weakself]_inself?.updateUI()}.store(in:&cancellables)
Key points:
Set tolerance to at least 10% of interval
Timer tolerance allows system to batch multiple timers into single wake
Prefer event-driven patterns over polling timers
Always invalidate timers when no longer needed
Pattern 2: Push vs Poll
Problem: Polling (checking server every N seconds) keeps radios active and drains battery.
β Anti-Pattern β Polling every 5 seconds
// BAD: Polls server every 5 seconds// Radio stays active, massive battery drainTimer.scheduledTimer(withTimeInterval:5.0, repeats:true){[weakself]_inself?.fetchLatestData()// Network request every 5 seconds}
β Fix β Use background push notifications
// GOOD: Server pushes when data changes// Radio only active when there's actual new data// 1. Register for remote notificationsUIApplication.shared.registerForRemoteNotifications()// 2. Handle background notificationfuncapplication(_ application:UIApplication, didReceiveRemoteNotification userInfo:[AnyHashable:Any], fetchCompletionHandler completionHandler:@escaping(UIBackgroundFetchResult)->Void){guardlet_= userInfo["content-available"]else{completionHandler(.noData)return}Task{do{let hasNewData =tryawaitfetchLatestData()completionHandler(hasNewData ?.newData :.noData)}catch{completionHandler(.failed)}}}
βΊAccess to product documentation and roadmap tools (Jira, Notion, etc.)
βΊUnderstanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
βΊStakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share effective prompts with product team
Common Pitfalls
β Not validating competitive researchβverify facts before sharing
β Accepting user stories without involving engineering team
β Over-relying on frameworks without qualitative judgment
β Not customizing outputs to company culture and communication style
β Skipping stakeholder validation of generated requirements
Best Practices
β 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
β Don't
βDon't publish competitive analysis without fact-checking
βDon't finalize user stories without engineering review
βDon't make prioritization decisions solely on AI scoring
βDon't skip customer validation of generated requirements
βDon't ignore company-specific context and culture
π‘ Pro Tips
β Provide context: company goals, constraints, customer feedback
β Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
β Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
β Use skill for 70% generation + 30% customization to company needs
When to Use This
β Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
β 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