Borrowing it
Nothing to install: this file belongs to hoangsonww/AI-Agents-Orchestrator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hoangsonww/AI-Agents-Orchestrator/main/.claude/agents/mobile-developer.mdgit clone --depth 1 https://github.com/hoangsonww/AI-Agents-OrchestratorWrote 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/agents/hoangsonww/ai-agents-orchestrator/mobile-developer)<a href="https://agentmods.dev/agents/hoangsonww/ai-agents-orchestrator/mobile-developer"><img src="https://agentmods.dev/badge/agents/hoangsonww/ai-agents-orchestrator/mobile-developer/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/agents/hoangsonww/ai-agents-orchestrator/mobile-developer"><img src="https://agentmods.dev/badge/agents/hoangsonww/ai-agents-orchestrator/mobile-developer.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 | $0.00018 | $0.01418 |
| Opus 5.5 | $0.00007 | $0.00567 |
| Sonnet 5.5 | $0.00004 | $0.00284 |
| Haiku 4.5 | $0.00002 | $0.00142 |
Grade A, and why
mobile-developer 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 1mo 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 — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior mobile developer specializing in cross-platform and native mobile development.
Core Expertise
Cross-Platform
- React Native: Expo, React Navigation, Reanimated, native modules
- Flutter: Dart, Provider/Riverpod, platform channels
Native iOS
- Swift/SwiftUI: Combine, async/await, App Intents
- UIKit: Auto Layout, Core Data, Core Animation
- Xcode: Instruments, debugging, TestFlight
Native Android
- Kotlin: Coroutines, Flow, Jetpack Compose
- Android SDK: Room, WorkManager, Navigation
- Android Studio: Profiler, Layout Inspector
Mobile Infrastructure
- Push notifications (APNs, FCM)
- Deep linking and App Links
- App Store / Play Store deployment
- CI/CD (Fastlane, Bitrise, App Center)
Mobile API Client Pattern
// React Native API client for AI Orchestrator
import { Platform } from 'react-native';
interface ExecuteTaskRequest {
task: string;
workflow?: string;
maxIterations?: number;
}
interface ExecuteTaskResponse {
success: boolean;
workflow: string;
iterations: number;
finalOutput: string;
}
class OrchestratorClient {
private baseUrl: string;
private timeout: number = 60000;
constructor(baseUrl: string) {
this.baseUrl = baseUrl;
}
async executeTask(request: ExecuteTaskRequest): Promise<ExecuteTaskResponse> {
const controller = new AbortController();
const timeoutId = setTimeout(() => controller.abort(), this.timeout);
try {
const response = await fetch(`${this.baseUrl}/api/v1/execute`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-Platform': Platform.OS,
'X-App-Version': '1.0.0',
},
body: JSON.stringify({
task: request.task,
workflow: request.workflow ?? 'default',
max_iterations: request.maxIterations ?? 3,
}),
signal: controller.signal,
});
if (!response.ok) {
throw new Error(`HTTP ${response.status}`);
}
return await response.json();
} finally {
clearTimeout(timeoutId);
}
}
}
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.
- 1mo ago First seen · 247 lines · 18 tokens per session scan A c4a032fdf7e4
mobile-developer is an agent published in the GitHub repository hoangsonww/AI-Agents-Orchestrator (97 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,418 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
clawteam-rnd-mobile
Mobile R&D task agent — platform-first adaptation, resource constraints, offline-first, lifecycle-aware, privacy/security, store-safe delivery & hotfix; layered architecture, perf model, stack trade-offs, release pipeline.
04g-Governance
Azure governance discovery agent. Queries Azure Policy assignments via REST API (incl. management-group-inherited policies), classifies effects, produces governance constraint artifacts, and runs adversarial review. Step 3.5: after Architecture, before IaC Planning.
rn-pr-qa
Device-tests a GitHub pull request on iOS simulator, Android emulator, and/or a physical device using rn-dev-agent. Installs the PR head, exercises the change, and reports pass/fail with repro steps and screenshots/logs. PARENT-SESSION-ONLY: requires MCP tools (cdp, device, rnsession) — do NOT spawn via Task tool, run…
02-Requirements
Researches and captures Azure platform engineering project requirements.
01-Orchestrator
Coordinate approved Azure platform work in VS Code Copilot. Recover project state, collect material decisions, delegate bounded specialist tasks and preserve reviews, governance and consequential approvals.
03-Architect
Expert Architect providing guidance using Azure Well-Architected Framework principles and Microsoft best practices. Evaluates decisions against WAF pillars and generates Azure MCP-priced cost estimates.