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 Livsy90/iOS-Performance-Agent-Skills --skill ios-launch-performancegit clone --depth 1 https://github.com/Livsy90/iOS-Performance-Agent-SkillsWrote 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/livsy90/ios-performance-agent-skills/ios-launch-performance)<a href="https://agentmods.dev/skills/livsy90/ios-performance-agent-skills/ios-launch-performance"><img src="https://agentmods.dev/badge/skills/livsy90/ios-performance-agent-skills/ios-launch-performance/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/livsy90/ios-performance-agent-skills/ios-launch-performance"><img src="https://agentmods.dev/badge/skills/livsy90/ios-performance-agent-skills/ios-launch-performance.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00072 | $0.03137 |
| Opus 5 | $0.00036 | $0.01569 |
| Sonnet 5 | $0.00014 | $0.00627 |
| Haiku 4.5 | $0.00007 | $0.00314 |
Grade A, and why
ios-launch-performance 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS Launch Performance
Use this skill to review the path from an app launch request to first visible UI and early responsiveness.
Focus on work that happens:
- before
main - during UIKit or SwiftUI startup
- inside
UIApplicationDelegate,UISceneDelegate, or SwiftUIApp - during root UI creation
- before the first visible frame
- before the first meaningful interaction
- during early post-launch work that still affects user-perceived readiness
This is not a general iOS performance skill. Use it only when the issue is launch-specific or when the code runs on the launch path.
Core Model
Treat launch as a pipeline with separate phases:
- Process creation and system preparation
- dyld loading, binding, fixups, runtime registration, and static initialization
- UIKit or SwiftUI runtime startup
- App-level initialization in
UIApplicationDelegate,UISceneDelegate, or SwiftUIApp - Launch orchestration and dependency setup
- Root UI construction, layout, drawing, and first frame commit
- Early post-launch work that affects responsiveness
- Later feature-specific or maintenance work
Do not optimize blindly. First identify which phase is expensive, then recommend changes that move, remove, lazy-load, parallelize, serialize, or measure that specific work.
When to Use This Skill
Use this skill when the task involves:
- slow app launch
- startup regressions
- cold, warm, or prewarmed launch
- resume-vs-launch confusion
- first-frame readiness
- early responsiveness after launch
- pre-main or dyld work
- Objective-C
+load,+initialize, constructor functions, or static initialization - AppDelegate or SceneDelegate startup work
- SwiftUI
@main App,WindowGroup, root view setup, or environment injection - dependency container setup during launch
- launch orchestrators or ordered startup steps
- third-party SDK initialization during launch
- framework linking strategy when launch cost is suspected
- launch metrics from Instruments, XCTest, MetricKit, or Xcode Organizer
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 306 B
- references/appdelegate-scenedelegate-and-first-frame.md 28 KB
- references/launch-orchestration-and-dependency-graph.md 27 KB
- references/launch-taxonomy-and-targets.md 22 KB
- references/linking-strategy.md 25 KB
- references/metrics-instruments-xctest-metrickit.md 26 KB
- references/pre-main-dyld-and-static-initializers.md 23 KB
- references/swiftui-app-launch.md 27 KB
- references/third-party-sdks-at-launch.md 35 KB
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.
- 11d ago First seen · 345 lines · 72 tokens per session scan A 8aa2c296af80
ios-launch-performance is a skill published in the GitHub repository Livsy90/iOS-Performance-Agent-Skills (113 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 3,137 once invoked, about $0.0004 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 2026-08-30.
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