Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add patrickserrano/lacquer --skill ios-performance-battery-patternsgit clone --depth 1 https://github.com/patrickserrano/lacquerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/patrickserrano/lacquer/ios-performance-battery-patterns)<a href="https://agentmods.dev/skills/patrickserrano/lacquer/ios-performance-battery-patterns"><img src="https://agentmods.dev/badge/skills/patrickserrano/lacquer/ios-performance-battery-patterns.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.00508 |
| Opus 5 | $0.00028 | $0.00254 |
| Sonnet 5 | $0.00011 | $0.00102 |
| Haiku 4.5 | $0.00006 | $0.00051 |
Grade A, and why
ios-performance-battery-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Battery & Performance Patterns
Apply these whenever touching widgets, animations, networking, or background work.
Widgets
- Limit
Timelineentries to ≤ 2 (current + one next-day refresh). More entries run the provider repeatedly and drain battery. - Use
.atEndreload policy — let WidgetKit decide when to refresh.
Animations
- Always stop animations in
.onDisappear. Animations left running off-screen still consume CPU/GPU. - Bind repeating animations to a
@State var isAnimating = false: settruein.onAppear,falsein.onDisappear, and passvalue: isAnimatingtowithAnimation. - Use
.repeatCount(N)instead of.repeatForeverfor attention animations.
Low Power Mode
Guard expensive operations before they start:
guard !ProcessInfo.processInfo.isLowPowerModeEnabled else { return }
Apply to: image preloading, background downloads, video prefetch, heavy sync.
Network
let config = URLSessionConfiguration.default
config.allowsConstrainedNetworkAccess = false // respect Low Data Mode
config.allowsExpensiveNetworkAccess = false // avoid cellular when Wi-Fi preferred
config.waitsForConnectivity = true // queue rather than fail when offline
Observer & Task Cleanup
@Observable macro-generated storage prevents nonisolated deinit from removing NotificationCenter observers. Use reference-type boxes instead:
final class NotificationObserverBox {
private var tokens: [NSObjectProtocol] = []
func add(_ token: NSObjectProtocol) { tokens.append(token) }
deinit { tokens.forEach { NotificationCenter.default.removeObserver($0) } }
}
final class TaskBox {
private var cancel: (() -> Void)?
func store<Success, Failure>(_ task: Task<Success, Failure>) { cancel = { task.cancel() } }
deinit { cancel?() }
}
For MPRemoteCommandCenter: store addTarget return values; call removeTarget(nil) on each in deinit.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 61 lines · 56 tokens per session scan A cdd18bf37cdf
ios-performance-battery-patterns is a skill published in the GitHub repository patrickserrano/lacquer (3 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 508 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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