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 flaqai/ios-application-development-skills --skill swiftui-performance-auditgit clone --depth 1 https://github.com/flaqai/ios-application-development-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/flaqai/ios-application-development-skills/swiftui-performance-audit)<a href="https://agentmods.dev/skills/flaqai/ios-application-development-skills/swiftui-performance-audit"><img src="https://agentmods.dev/badge/skills/flaqai/ios-application-development-skills/swiftui-performance-audit/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/flaqai/ios-application-development-skills/swiftui-performance-audit"><img src="https://agentmods.dev/badge/skills/flaqai/ios-application-development-skills/swiftui-performance-audit.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 | $0.00032 | $0.01055 |
| Opus 5 | $0.00016 | $0.00528 |
| Sonnet 5 | $0.00006 | $0.00211 |
| Haiku 4.5 | $0.00003 | $0.00105 |
Grade A, and why
swiftui-performance-audit 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 10d 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.
This is a copy
94% identical to swiftui-performance-audit — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SwiftUI Performance Audit
Quick start
Use this skill to diagnose SwiftUI performance issues from code first, then request profiling evidence when code review alone cannot explain the symptoms.
Workflow
- Classify the symptom: slow rendering, janky scrolling, high CPU, memory growth, hangs, or excessive view updates.
- If code is available, start with a code-first review using
references/code-smells.md. - If code is not available, ask for the smallest useful slice: target view, data flow, reproduction steps, and deployment target.
- If code review is inconclusive or runtime evidence is required, guide the user through profiling with
references/profiling-intake.md. - Summarize likely causes, evidence, remediation, and validation steps using
references/report-template.md.
1. Intake
Collect:
- Target view or feature code.
- Symptoms and exact reproduction steps.
- Data flow:
@State,@Binding, environment dependencies, and observable models. - Whether the issue shows up on device or simulator, and whether it was observed in Debug or Release.
Ask the user to classify the issue if possible:
- CPU spike or battery drain
- Janky scrolling or dropped frames
- High memory or image pressure
- Hangs or unresponsive interactions
- Excessive or unexpectedly broad view updates
For the full profiling intake checklist, read references/profiling-intake.md.
2. Code-First Review
Focus on:
- Invalidation storms from broad observation or environment reads.
- Unstable identity in lists and
ForEach. - Heavy derived work in
bodyor view builders. - Layout thrash from complex hierarchies,
GeometryReader, or preference chains. - Large image decode or resize work on the main thread.
- Animation or transition work applied too broadly.
Use references/code-smells.md for the detailed smell catalog and fix guidance.
Provide:
- Likely root causes with code references.
- Suggested fixes and refactors.
- If needed, a minimal repro or instrumentation suggestion.
What ships with it
8 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.
- agents/openai.yaml 242 B
- references/code-smells.md 3.7 KB
- references/demystify-swiftui-performance-wwdc23.md 1.8 KB
- references/optimizing-swiftui-performance-instruments.md 1.8 KB
- references/profiling-intake.md 1.9 KB
- references/report-template.md 1.2 KB
- references/understanding-hangs-in-your-app.md 1.2 KB
- references/understanding-improving-swiftui-performance.md 2.2 KB
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.
- 10d ago First seen · 108 lines · 32 tokens per session scan A 6fc6bd4d49b4
swiftui-performance-audit is a skill published in the GitHub repository flaqai/ios-application-development-skills (4 stars, last pushed 26d ago), licensed MIT. It adds 32 tokens to every session and 1,055 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to swiftui-performance-audit, differing in 3 lines, and is treated as a copy.
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