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 vignesh2027/AI-AGENT-SKILLS --skill mobile-developmentgit clone --depth 1 https://github.com/vignesh2027/AI-AGENT-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/vignesh2027/ai-agent-skills/mobile-development)<a href="https://agentmods.dev/skills/vignesh2027/ai-agent-skills/mobile-development"><img src="https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/mobile-development/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/vignesh2027/ai-agent-skills/mobile-development"><img src="https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/mobile-development.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 | $0.00022 | $0.00520 |
| Opus 5 | $0.00011 | $0.00260 |
| Sonnet 5 | $0.00004 | $0.00104 |
| Haiku 4.5 | $0.00002 | $0.00052 |
Grade A, and why
mobile-development 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 8d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Mobile apps have unique constraints: unreliable networks, limited battery, strict platform guidelines, and app store review. This skill applies mobile-specific engineering discipline.
When to Use
- Before implementing a new mobile feature
- When an app is slow, crashes, or drains battery
- Before submitting to the app store
Process
Step 1: Design for offline-first
Assume the network is unavailable. Design data flows that work offline and sync when connectivity returns. Use optimistic UI updates.
Step 2: Main thread discipline
- No I/O on the main thread
- No heavy computation on the main thread
- Profile with Instruments (iOS) or Android Profiler for frame drops
Target: 60fps during all user interactions.
Step 3: Memory management
- No strong reference cycles (iOS: use weak/unowned)
- Instrument for memory leaks before release
- Release large resources when the app backgrounds
Step 4: Battery efficiency
- Minimize background work
- Batch network requests
- Use push over polling
- Reduce GPS/sensor usage frequency when precision isn't needed
Step 5: App size
- Analyze app size before each release
- Use on-demand resources for large assets
- Target: < 30MB download for initial install
Step 6: Crash rate
- Integrate crash reporting from day one (Crashlytics, Sentry)
- Fix crashes before shipping new features
- Target: < 0.1% crash-free sessions
Step 7: Accessibility
- Dynamic Type support (iOS) / font scaling (Android)
- VoiceOver (iOS) / TalkBack (Android) tested
- Touch targets ≥ 44pt × 44pt
- Color contrast meets WCAG AA
Step 8: App store compliance
- Review App Store / Play Store guidelines for relevant categories before implementing
- Test on oldest supported OS version
- Implement required privacy labels/permissions honestly
Verification Requirements
- Offline state handled gracefully
- No I/O or heavy computation on main thread
- Profiled: 60fps during interactions
- Crash reporting integrated
- Accessibility tested with platform screen reader
- App size within budget
- Tested on oldest supported OS version
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.
- 8d ago First seen · 71 lines · 22 tokens per session scan A d3ced4cda65f
mobile-development is a skill published in the GitHub repository vignesh2027/AI-AGENT-SKILLS (2 stars, last pushed 10d ago), licensed MIT. It adds 22 tokens to every session and 520 once invoked, about $0.0001 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 2026-08-31.
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