What is ios-performance?

An iOS performance guide for finding and fixing slow startup, rendering delays, memory growth, CPU-heavy work, and excess energy use. It uses profiling tools to compare a representative workload on a real device or suitable test setup.

Use it to investigate launch latency, scrolling or rendering hitches, memory leaks, CPU usage, image handling, and battery impact.

It replaces guesswork with measurements and helps distinguish problems such as repeated fetching, expensive image decoding, excessive view updates, and tasks with the wrong lifetime.

ios-performance — Skill for Claude Code and Codex by CarolaneLFBV

Install

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.

Any agent

npx skills add CarolaneLFBV/ios-development-agents --skill ios-performance

Clone the repo

git clone --depth 1 https://github.com/CarolaneLFBV/ios-development-agents

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/carolanelfbv/ios-development-agents/ios-performance/github.svg)](https://agentmods.dev/skills/carolanelfbv/ios-development-agents/ios-performance)

Your own site

<a href="https://agentmods.dev/skills/carolanelfbv/ios-development-agents/ios-performance"><img src="https://agentmods.dev/badge/skills/carolanelfbv/ios-development-agents/ios-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/carolanelfbv/ios-development-agents/ios-performance"><img src="https://agentmods.dev/badge/skills/carolanelfbv/ios-development-agents/ios-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 352 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00026	$0.00352
Opus 5.5	$0.00010	$0.00141
Sonnet 5.5	$0.00005	$0.00070
Haiku 4.5	$0.00003	$0.00035

Measured today against content hash 78adaef35b67, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ios-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 today.

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.

skills/ios-performance/SKILL.md · 31 lines

What it actually says

Performance

Identify the symptom and representative workload. Inspect existing performance tests, device targets and budgets. Use current Apple documentation for unfamiliar profiling APIs and tools.

Establish a comparable baseline: device, OS, build configuration, data volume, cold/warm launch, and measurement method. Simulator timings alone do not prove device performance. Do not impose generic memory or launch-time thresholds.
Match tools to the symptom: Time Profiler for CPU, Allocations/Leaks and memory graphs for lifetime issues, SwiftUI instruments for updates, signposts/MetricKit for app-specific timing and field evidence. Discover installed templates.
Optimize demonstrated hot paths. Check main-actor CPU work, repeated fetching, unstable view IDs, image decoding, allocation growth and task lifetime. async does not guarantee background execution; verify isolation settings.
Choose lazy containers from collection size and interaction requirements. View extraction is a composition technique, not a guarantee of fewer evaluations.
Downsample images before decoding full resolution; bound caches and respond to memory pressure. An actor around NSCache does not by itself make UIKit values safe to transfer between actors. Check actual SDK sendability and consumers.
Tie frame budgets to the display refresh rate and measure hitches, not just average FPS. Avoid trading away correctness, accessibility or battery for a score.

Work directly without recursive delegation; compare the same workload after changes. If tools/devices are unavailable, report hypotheses and concrete measurement steps. Report before/after figures only when measured.

Changes

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.

today First seen · 31 lines · 26 tokens per session scan A 78adaef35b67

Subscribe to this mod's changes

ios-performance is a skill published in the GitHub repository CarolaneLFBV/ios-development-agents (7 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 352 once invoked, about $0.0001 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 2026-10-17.

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