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-perceived-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-perceived-performance)<a href="https://agentmods.dev/skills/livsy90/ios-performance-agent-skills/ios-perceived-performance"><img src="https://agentmods.dev/badge/skills/livsy90/ios-performance-agent-skills/ios-perceived-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-perceived-performance"><img src="https://agentmods.dev/badge/skills/livsy90/ios-performance-agent-skills/ios-perceived-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 121 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00089 | $0.02025 |
| Opus 5 | $0.00044 | $0.01012 |
| Sonnet 5 | $0.00018 | $0.00405 |
| Haiku 4.5 | $0.00009 | $0.00202 |
Grade A, and why
ios-perceived-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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS Perceived Performance
Purpose
Use this skill to review whether an iOS screen or flow feels responsive to users, even when raw execution time does not change.
This skill focuses on user-visible feedback, loading behavior, staged content, continuity, optimistic UI, high-stakes actions, and validation of perceived responsiveness.
When to use this skill
Use this skill when the task involves:
- a screen that feels slow, stuck, blank, jumpy, or unresponsive;
- no visible feedback after a tap or gesture;
- delayed first meaningful content;
- loading states, placeholders, skeletons, empty states, retry states, or refresh states;
- progressive rendering, partial content, section-level loading, or stale-while-refreshing UI;
- optimistic updates, pending state, rollback, retries, or local/server reconciliation;
- high-stakes, irreversible, destructive, financial, legal, medical, identity, or security-sensitive actions;
- duplicate submissions or repeated taps during async work;
- perceived latency trade-offs where the product behavior matters as much as the raw duration;
- validation using recordings, UI tests, Instruments, MetricKit, production logs, or user-visible signals.
When not to use this skill
Do not use this skill for:
- low-level CPU, allocation, ARC, memory, runtime, or compiler-performance investigations;
- SwiftUI invalidation, identity, layout, or scrolling problems unless the question is about perceived responsiveness;
- Swift Concurrency internals unless task behavior affects visible UI feedback or staged loading;
- app launch performance unless the question is about first useful screen or first interaction from the user's point of view;
- visual redesign requests with no responsiveness, loading, or feedback concern;
- claims that require running the app when no runtime evidence is available.
Use ios-performance-profiling, swiftui-performance, swift-concurrency-performance, swift-runtime-performance, or ios-launch-performance when those domains are the primary problem.
What ships with it
6 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.
- 11d ago First seen · 194 lines · 89 tokens per session scan A f9428a6b99c1
ios-perceived-performance is a skill published in the GitHub repository Livsy90/iOS-Performance-Agent-Skills (113 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 2,025 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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