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 agentmods add commands/carolanelfbv/ios-development-agents/optimizegit clone --depth 1 https://github.com/CarolaneLFBV/ios-development-agentsWhat 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 | $0.00005 | $0.00563 |
| Opus 5 | $0.00003 | $0.00282 |
| Sonnet 5 | $0.00001 | $0.00113 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
optimize 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 2d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ios:optimize - Performance Optimization
Optimize $ARGUMENTS using Instruments profiling and best practices.
Delegation
Executed by the performance-specialist. Spawn it via the Task tool with the --metric and --goal; it profiles, applies optimizations, and reports before/after measurements.
Arguments
| Flag | Values | Default | Description |
|---|---|---|---|
--metric |
launch|render|memory|battery | render | Optimization metric |
--goal |
<value> |
- | Performance goal (e.g., "launch<2s") |
--instruments |
- | - | Use Xcode Instruments |
Optimization Areas
| Metric | Focus | Target |
|---|---|---|
launch |
App startup time | <2s cold, <1s warm |
render |
SwiftUI rendering | 60fps, no hitches |
memory |
Memory usage | <100MB baseline |
battery |
Energy efficiency | Low CPU usage |
Optimization Patterns
// List Performance
// Before:
VStack { ForEach(items) { ExpensiveView(item: $0) } }
// After:
LazyVStack(spacing: 8) {
ForEach(items, id: \.id) { ItemView(item: $0).id($0.id) }
}
// Image Loading
// Before:
Image(uiImage: loadImage())
// After:
AsyncImage(url: imageURL) { phase in
switch phase {
case .success(let image): image.resizable()
default: ProgressView()
}
}
Instruments Templates
| Template | Use Case |
|---|---|
| Time Profiler | CPU usage, hot paths |
| Allocations | Memory usage, leaks |
| SwiftUI | View body evaluation |
| Core Animation | Rendering performance |
| Energy Log | Battery consumption |
Examples
/ios:optimize App --metric launch --goal "launch<1s"
/ios:optimize ProductList --metric render
/ios:optimize . --metric memory --instruments
/ios:optimize ImageLoader --metric battery
Output
# Optimization: [Target]
## Metric: launch | render | memory | battery
## Before: Current measurements
## After: Improved measurements
## Changes: Applied optimizations
## Instruments: Profile recommendations
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.
- 2d ago First seen · 86 lines · 5 tokens per session scan A 1f9671eb658d
optimize is a command published in the GitHub repository CarolaneLFBV/ios-development-agents (7 stars, last pushed 1mo ago), licensed MIT. It adds 5 tokens to every session and 563 once invoked, about $0.0000 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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