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 swift-runtime-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/swift-runtime-performance)<a href="https://agentmods.dev/skills/livsy90/ios-performance-agent-skills/swift-runtime-performance"><img src="https://agentmods.dev/badge/skills/livsy90/ios-performance-agent-skills/swift-runtime-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/swift-runtime-performance"><img src="https://agentmods.dev/badge/skills/livsy90/ios-performance-agent-skills/swift-runtime-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 | $0.00098 | $0.03417 |
| Opus 5 | $0.00049 | $0.01708 |
| Sonnet 5 | $0.00020 | $0.00683 |
| Haiku 4.5 | $0.00010 | $0.00342 |
Grade A, and why
swift-runtime-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 10d 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Swift Runtime Performance
Purpose
Use this skill to review Swift code for runtime-level performance costs without turning every abstraction into a problem. Focus on concrete costs such as allocation, ARC traffic, dispatch, specialization, copying, optimizer visibility, and unsafe memory boundaries.
This skill should help the agent distinguish real hot-path runtime costs from theoretical micro-optimizations.
When to use this skill
Use this skill when the task involves Swift runtime behavior such as:
- heap allocation, stack vs heap storage, object layout, boxed values, or closure contexts;
- ARC retain/release traffic, ownership, lifetime, weak/unowned references, or closure captures;
- direct dispatch, class dispatch, Objective-C dispatch, witness dispatch, or dynamic dispatch in hot paths;
any Protocol,some Protocol, generics, type erasure, specialization, or unspecialized hot code;- copy-on-write collections, large values, custom COW storage, or repeated copies;
- optimized SIL inspection, compiler optimization, inlining, devirtualization, or specialization evidence;
- unsafe Swift, pointer lifetime, memory binding, aliasing, buffer mutation, or safe wrappers around unsafe regions;
- module boundaries that affect optimizer visibility,
@inlinable,@usableFromInline,@frozen, or public API resilience trade-offs.
When not to use this skill
Do not use this skill for:
- general Swift syntax or API usage questions with no runtime performance concern;
- app launch investigations where the main issue is pre-main, dyld, static initializers, SDK startup, first frame, or first interaction;
- SwiftUI performance issues where the main issue is identity, invalidation, state scope, layout, drawing, animation, or scrolling;
- Swift Concurrency issues where the main issue is task lifetime, actor isolation, MainActor responsiveness, cancellation, AsyncSequence cleanup, reentrancy, or executor behavior;
- profiling workflow questions where the main task is choosing tools, interpreting traces, designing signposts, XCTest metrics, MetricKit, or production signals;
- broad architecture questions unless there is a specific runtime cost in a hot path.
What ships with it
10 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 318 B
- references/allocation-and-layout.md 21 KB
- references/arc-and-ownership.md 21 KB
- references/concurrency-runtime.md 23 KB
- references/cow-and-large-values.md 18 KB
- references/dispatch-and-specialization.md 21 KB
- references/existentials-generics-opaque-types.md 25 KB
- references/modularization-and-linking.md 25 KB
- references/sil-inspection.md 20 KB
- references/unsafe-swift.md 24 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.
- 10d ago First seen · 266 lines · 98 tokens per session scan A f9250d11468a
swift-runtime-performance is a skill published in the GitHub repository Livsy90/iOS-Performance-Agent-Skills (112 stars, last pushed 1mo ago), licensed MIT. It adds 98 tokens to every session and 3,417 once invoked, about $0.0005 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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