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 nimadorostkar/Claude-Skills-collection --skill iosgit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/ios)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/ios"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/ios/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/nimadorostkar/claude-skills-collection/ios"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/ios.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 57 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Rogue Agent · line 57 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00033 | $0.01102 |
| Opus 5 | $0.00016 | $0.00551 |
| Sonnet 5 | $0.00007 | $0.00220 |
| Haiku 4.5 | $0.00003 | $0.00110 |
Grade A, and why
ios 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 9d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS
Purpose
Build iOS applications with a single source of truth for state, correct lifecycle handling, and an architecture that survives the App Review process without surprises.
When to Use
- Building or reviewing a SwiftUI application.
- Structuring navigation, state, and dependencies.
- Handling background execution, notifications, or deep links.
- Preparing an App Store submission.
Capabilities
- SwiftUI architecture with
@Observableand unidirectional data flow. - Navigation with
NavigationStackand type-safe routes. - Networking with async/await, retries, and offline behavior.
- Persistence: SwiftData, Core Data, Keychain.
- Background tasks, push notifications, and app lifecycle.
- App Store requirements: privacy manifest, permissions, review guidelines.
Inputs
- The feature set and the minimum supported iOS version.
- Data requirements: offline, sync, sensitive.
- Distribution target: App Store, TestFlight, enterprise.
Outputs
- Views that read state and emit intent; models that own the state.
- A navigation model that supports deep links by construction.
- A submission checklist covering permissions, privacy, and metadata.
Workflow
- Model the state — One
@Observablemodel per screen or feature. The view derives everything it displays from it; it holds no duplicate copies. - Make navigation data-driven —
NavigationStack(path:)with an enumerated route type. Deep linking then becomes "append to the path", not a second navigation system. - Handle the lifecycle — Work started in the foreground is suspended when the app is backgrounded. Anything that must complete needs a background task assertion or a background URL session.
- Design for offline — Assume the network fails. Cache, queue writes, and reconcile. On mobile this is the normal case, not the edge case.
- Prepare for review — Every permission needs a purpose string that says what the app does with it. A privacy manifest is mandatory. Rejections are almost always about permissions, purchases, or metadata.
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.
- 9d ago First seen · 115 lines · 33 tokens per session scan A f0fee3918f11
ios is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 25d ago), licensed MIT. It adds 33 tokens to every session and 1,102 once invoked, about $0.0002 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 2026-09-03.
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