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 termio-sh/termio --skill swift-performance-optimization-skillgit clone --depth 1 https://github.com/termio-sh/termioWrote 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/termio-sh/termio/swift-performance-optimization-skill)<a href="https://agentmods.dev/skills/termio-sh/termio/swift-performance-optimization-skill"><img src="https://agentmods.dev/badge/skills/termio-sh/termio/swift-performance-optimization-skill/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/termio-sh/termio/swift-performance-optimization-skill"><img src="https://agentmods.dev/badge/skills/termio-sh/termio/swift-performance-optimization-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00068 | $0.01439 |
| Opus 5.5 | $0.00027 | $0.00576 |
| Sonnet 5.5 | $0.00014 | $0.00288 |
| Haiku 4.5 | $0.00007 | $0.00144 |
Grade A, and why
Swift Performance Optimization Skill 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 1mo 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Swift Performance Optimization Skill
Optimize from evidence. Preserve behavior, accessibility, data correctness, and lifecycle safety while changing performance characteristics.
Baseline
The copy-ready examples use Xcode 16, Swift 6 language mode with strict concurrency, and iOS 17. Most principles apply to older targets; verify each API against the app's actual minimum. Material from the OS 27 development cycle is beta relative to stable Xcode 26.6 and requires an explicit request, beta labeling, stable fallback, and availability gate.
Measurement workflow
- Define a user-visible symptom and a reproducible scenario.
- Record device, OS, build configuration, dataset, thermal state, and network conditions.
- Measure an optimized Release build on representative hardware. Simulator-only timing is not release evidence.
- Select the instrument that answers the hypothesis.
- Save a baseline trace or metric, change one variable, then repeat the same scenario.
- Confirm that the bottleneck moved and no memory, energy, correctness, or accessibility regression appeared.
- Add a regression threshold where the workload is stable enough to automate.
Useful tools include:
| Symptom | First evidence source |
|---|---|
| CPU-bound work | Time Profiler; inspect heavy stacks and self time |
| SwiftUI update cost | SwiftUI instrument plus Time Profiler |
| Scroll or animation stalls | Animation Hitches, Core Animation, signposts |
| Growth or leaks | Allocations, Leaks, Memory Graph, memgraphs |
| Slow launch | App Launch template and launch signposts |
| Battery or thermal issues | Energy Log and device testing |
| Field regressions | MetricKit payloads and app-specific telemetry |
Use os_signpost or signposter intervals around important operations so traces answer product questions rather than only showing raw symbols.
Lifetime and memory safety
- A capture is a cycle only when the closure is retained along a path back to its owner. Do not add
[weak self]mechanically to every closure. - Use
weakwhen the owner may legitimately disappear before the callback. Useunownedonly when the lifetime invariant is proven and documented; a wrong assumption traps. - Prefer structured
asyncfunctions over storing completion closures. - Cancel owned tasks and invalidate repeating timers when the owner stops needing them and during teardown.
- Never use
[unowned self]in a repeating timer merely to silence a cycle.
What ships with it
4 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.
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.
- 1mo ago First seen · 137 lines · 68 tokens per session scan A f6e43a81a161
Swift Performance Optimization Skill is a skill published in the GitHub repository termio-sh/termio (548 stars, last pushed today), licensed MIT. It adds 68 tokens to every session and 1,439 once invoked, about $0.0003 per session on Opus 5.5. 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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