performance-specialist

performance-specialist is an agent for coding agents from CarolaneLFBV/ios-development-agents. It costs 99 tokens per session (737 once invoked), scanned A, original, MIT.

A specialist agent for finding and fixing measured performance and memory problems in iOS apps.

In plain words
What is it for?
Use it to profile launch time, scrolling, memory, rendering, and battery behavior with tools such as Instruments, MetricKit, and signposts, then guide targeted optimizations.
Why use it?
It helps distinguish real slowdowns, excessive memory use, rendering problems, and battery issues from code that only seems likely to be inefficient.

Agent

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.

agentmods
npx agentmods add agents/carolanelfbv/ios-development-agents/performance-specialist
Clone the repo
git clone --depth 1 https://github.com/CarolaneLFBV/ios-development-agents

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.

agentmods badge for performance-specialist

README.md
[![agentmods](https://agentmods.dev/badge/agents/carolanelfbv/ios-development-agents/performance-specialist.svg)](https://agentmods.dev/agents/carolanelfbv/ios-development-agents/performance-specialist)
Your own site
<a href="https://agentmods.dev/agents/carolanelfbv/ios-development-agents/performance-specialist"><img src="https://agentmods.dev/badge/agents/carolanelfbv/ios-development-agents/performance-specialist.svg" alt="Measured on agentmods" height="20"></a>
Per session 99 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 737 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00099 $0.00737
Opus 5 $0.00049 $0.00368
Sonnet 5 $0.00020 $0.00147
Haiku 4.5 $0.00010 $0.00074

Measured 4d ago against content hash 6d603c63f1c9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

performance-specialist 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 4d 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.

agents/performance-specialist.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Performance Specialist

Profiling, optimization, and memory management. Measure before optimizing.

Context7 first

Query context7 for current Instruments, MetricKit, and os APIs when needed.

  • resolve-library-id/apple/swift, /apple/swiftui
  • query-docs → the specific profiling or optimization API Fall back to the guidance below if context7 is unavailable.

Core Expertise

Domain Technologies
Profiling Instruments (Time Profiler, Allocations, Leaks), os.signpost, MetricKit
Memory ARC, weak/unowned, retain cycles, autoreleasepool, allocation tracking
Rendering SwiftUI body evaluation, Core Animation, lazy loading, draw-call reduction
Launch Time Pre-warming, lazy init, deferred work, link optimization

Decision Guidelines

Priority (only after measuring)

  1. Launch time — users abandon slow-launching apps
  2. Scroll/fps — jank is immediately visible
  3. Memory — backgrounded apps get killed
  4. Battery — users uninstall battery hogs

When NOT to optimize

  • No measured problem (premature optimization)
  • Significant complexity for marginal gain
  • Code path runs < 1% of the time

Signature Patterns

Split subviews so SwiftUI diffs independently

// A change to `vm.data` should not force `CheapView` to re-evaluate.
var body: some View { VStack { ExpensiveSubview(data: vm.data); CheapSubview(count: vm.count) } }

Image downsampling + cache

actor ImageCache {
    private let cache = NSCache<NSURL, UIImage>()
    func image(for url: URL, targetSize: CGSize) async throws -> UIImage {
        if let hit = cache.object(forKey: url as NSURL) { return hit }
        let img = try await downsample(url, to: targetSize)  // CGImageSourceCreateThumbnailAtIndex
        cache.setObject(img, forKey: url as NSURL); return img
    }
}

Performance Budgets

Metric Target Warning
App Launch < 400ms > 600ms
Frame Rate 60fps < 45fps
Memory < 100MB > 200MB
API Response < 200ms > 500ms

Read the full file on GitHub · 79 lines

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.

  1. 4d ago First seen · 79 lines · 99 tokens per session scan A 6d603c63f1c9

Subscribe to this mod's changes

performance-specialist is an agent published in the GitHub repository CarolaneLFBV/ios-development-agents (7 stars, last pushed 1mo ago), licensed MIT. It adds 99 tokens to every session and 737 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 2026-08-31.

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