The first and most comprehensively benchmarked iOS skill marketplace for Claude Code, Codex, and 40+ AI coding tools.
11 enterprise-grade skills covering architecture, concurrency, testing, security, accessibility, and localization — every skill benchmarked with discriminating assertions and blind A/B quality scoring across multiple LLMs. No other iOS skill collection has this level of rigorous, reproducible evaluation — 850+ assertions across 260+ scenarios, tested on Claude Sonnet 4.6, GPT-5.4, and Gemini 3.1 Pro.
Every skill is benchmarked against multiple LLMs with discriminating assertions and blind A/B quality scoring.
| Skill | Sonnet 4.6 | GPT-5.4 | Gemini 3.1 Pro |
|---|---|---|---|
| swiftui-mvvm | |||
| uikit-mvvm | |||
| gcd-operations | |||
| ios-testing | |||
| swift-concurrency | |||
| ios-security | |||
| tca-swiftui | — | — | |
| viper-uikit | |||
| ios-logging | |||
| ios-accessibility | |||
| ios-localization |
Each cell: assertion delta (with skill vs without) · A/B blind comparison W/T/L with avg scores where available. Colored badge = best result for that skill. "—" = not yet benchmarked.
See BENCHMARKING.md for full methodology.
claude plugin add rusel95/ios-agent-skillsInstall individual skills:
claude plugin add rusel95/ios-agent-skills --skill swiftui-mvvm
claude plugin add rusel95/ios-agent-skills --skill swift-concurrencynpx skills add rusel95/ios-agent-skills --skill swiftui-mvvmClone and copy the skills/ directory into your project.
- Production-first — every pattern comes from real enterprise codebases, not tutorials
- Iterative refactoring — small, reviewable PRs (≤200 lines) instead of "rewrite everything" approaches
- Anti-pattern prevention — AI tools consistently generate broken patterns (retain cycles in VIPER, outdated TCA APIs, unsafe GCD). These skills prevent that
- Architecture coverage — the only collection covering VIPER, TCA, GCD, Security Audit, Accessibility, and Localization. No other iOS skill marketplace covers these domains
- Rigorously benchmarked — the most comprehensively evaluated iOS skill collection available: 850+ discriminating assertions across 260+ scenarios, tested against 3 LLMs with blind A/B quality scoring. Every skill ships with reproducible eval data
Ruslan Popesku — Lead iOS Software Engineer GitHub · LinkedIn
MIT
