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 skills/hack-dance/hack/swiftui-performance-auditnpx skills add hack-dance/hack --skill swiftui-performance-auditgit clone --depth 1 https://github.com/hack-dance/hackWhat 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 | $0.00066 | $0.01353 |
| Opus 5 | $0.00033 | $0.00677 |
| Sonnet 5 | $0.00013 | $0.00271 |
| Haiku 4.5 | $0.00007 | $0.00135 |
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 yesterday.
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
100% identical to swiftui-performance-audit — 0 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SwiftUI Performance Audit
Overview
Audit SwiftUI view performance end-to-end, from instrumentation and baselining to root-cause analysis and concrete remediation steps.
Workflow Decision Tree
- If the user provides code, start with "Code-First Review."
- If the user only describes symptoms, ask for minimal code/context, then do "Code-First Review."
- If code review is inconclusive, go to "Guide the User to Profile" and ask for a trace or screenshots.
1. Code-First Review
Collect:
- Target view/feature code.
- Data flow: state, environment, observable models.
- Symptoms and reproduction steps.
Focus on:
- View invalidation storms from broad state changes.
- Unstable identity in lists (
idchurn,UUID()per render). - Top-level conditional view swapping (
if/elsereturning different root branches). - Heavy work in
body(formatting, sorting, image decoding). - Layout thrash (deep stacks,
GeometryReader, preference chains). - Large images without downsampling or resizing.
- Over-animated hierarchies (implicit animations on large trees).
Provide:
- Likely root causes with code references.
- Suggested fixes and refactors.
- If needed, a minimal repro or instrumentation suggestion.
2. Guide the User to Profile
Explain how to collect data with Instruments:
- Use the SwiftUI template in Instruments (Release build).
- Reproduce the exact interaction (scroll, navigation, animation).
- Capture SwiftUI timeline and Time Profiler.
- Export or screenshot the relevant lanes and the call tree.
Ask for:
- Trace export or screenshots of SwiftUI lanes + Time Profiler call tree.
- Device/OS/build configuration.
3. Analyze and Diagnose
Prioritize likely SwiftUI culprits:
- View invalidation storms from broad state changes.
- Unstable identity in lists (
idchurn,UUID()per render). - Top-level conditional view swapping (
if/elsereturning different root branches). - Heavy work in
body(formatting, sorting, image decoding). - Layout thrash (deep stacks,
GeometryReader, preference chains). - Large images without downsampling or resizing.
- Over-animated hierarchies (implicit animations on large trees).
What ships with it
4 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.
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.
- yesterday First seen · 204 lines · 66 tokens per session scan A ff2db94adc31
swiftui-performance-audit is a skill published in the GitHub repository hack-dance/hack (8 stars, last pushed 20d ago), licensed MIT. It adds 66 tokens to every session and 1,353 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to swiftui-performance-audit, differing in 0 lines, and is treated as a copy.
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