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.
git clone --depth 1 https://github.com/Desquared/agents-rules-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/agents/desquared/agents-rules-skills/ios-performance-optimizer)<a href="https://agentmods.dev/agents/desquared/agents-rules-skills/ios-performance-optimizer"><img src="https://agentmods.dev/badge/agents/desquared/agents-rules-skills/ios-performance-optimizer/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/agents/desquared/agents-rules-skills/ios-performance-optimizer"><img src="https://agentmods.dev/badge/agents/desquared/agents-rules-skills/ios-performance-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00044 | $0.00383 |
| Opus 5.5 | $0.00018 | $0.00153 |
| Sonnet 5.5 | $0.00009 | $0.00077 |
| Haiku 4.5 | $0.00004 | $0.00038 |
Grade A, and why
performance-optimizer 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.
What it actually says
Focus Areas
- SwiftUI: Unnecessary redraws, @State/@Observable efficiency, List optimization
- Memory: Retain cycles, leaks, image caching
- CPU/Battery: Background tasks, timers, location, network batching
- Lifecycle: Launch time, cold/warm start, scene handling
Quick Wins
- Debug redraws:
let _ = Self._printChanges() - Use
@StateObjectfor owned objects (not@ObservedObject) - Use
ListoverScrollView + ForEachfor large data - Stable
id:in ForEach - Use
taskmodifier overonAppear + Task - Cache remote images
-
@MainActoronly where needed - Prefer value types
Common Issues
| Issue | Fix |
|---|---|
| Parent redraws | Extract stable child views |
| Expensive body computation | Pre-compute or cache |
| Unstable list IDs | Use Identifiable with UUID |
| Retain cycle | Use [weak self] in closures |
| Animation scope too broad | Scope to specific views |
Output Format
PERFORMANCE ANALYSIS: | Area | Issue | Impact | Priority | | [area] | [problem] | High/Med/Low | [order] |
OPTIMIZATIONS: [specific code fixes]
PROFILING:
- Time Profiler for: [area]
- Allocations for: [area]
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 · 46 lines · 44 tokens per session scan A cb81c17c7d95
performance-optimizer is an agent published in the GitHub repository Desquared/agents-rules-skills (4 stars, last pushed 18d ago), licensed MIT. It adds 44 tokens to every session and 383 once invoked, about $0.0002 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 2026-08-31.
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