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📱 Mobile Engineering Agents

Turn your AI coding agent into a Senior mobile engineer

A drop-in knowledge system that gives Claude Code, Codex, Cursor, Windsurf, Gemini CLI, and Aider the judgment of an experienced mobile team — architecture, security, testing, and standards — so the code they generate is production-grade, not just plausible.

License: MIT Docs PRs Welcome Platform AI-ready

Docs Site · Quick Start · What's Inside · The Agent Team · How to Use · How It Works · Workflows


Why this exists

AI agents can write a lot of mobile code, fast. The bottleneck isn't typing — it's engineering judgment: picking the right architecture, getting concurrency and error handling right, securing data, and keeping the codebase maintainable as it grows.

Without this toolkit: "Build me a login screen" → a Massive View Controller with the token in UserDefaults and no tests.

With it: the agent acts as a Security Expert + SwiftUI Expert — OAuth2 + PKCE, Keychain storage, MVVM, typed errors, and unit tests — then self-reviews against a checklist.

This repo encodes that judgment as machine-loadable agents, skills, workflows, checklists, templates, prompts, standards, and architecture references. Primary focus: iOS / Swift / SwiftUI; secondary: Android/Kotlin and Flutter.

It is not a tutorial or handbook. It's an operational toolkit you point your AI agent at.


Quick Start

Get running in three steps. The everyday workflow needs zero file paths.

1. Clone the toolkit into your project

cd your-project
git clone https://github.com/sokpichdev/mobile-engineering-agents.git .mobile-agents
echo ".mobile-agents/" >> .gitignore   # optional: keep it out of your repo

The hidden .mobile-agents/ folder keeps the toolkit from cluttering your own files.

2. Wire up the entry file for your tool

echo "@.mobile-agents/CLAUDE.md" > CLAUDE.md             # Claude Code
echo "@.mobile-agents/.cursorrules" > .cursorrules       # Cursor
echo "@.mobile-agents/.windsurfrules" > .windsurfrules   # Windsurf

The @ import pulls in the full toolkit. Codex (AGENTS.md) and Gemini CLI (GEMINI.md) auto-load their entry files straight from the cloned folder — no extra step.

3. Describe what you want

> Build a Profile screen that loads /me and stores the auth token securely.

On its first reply of every session, the agent confirms it loaded:

Mobile Engineering Agents — loaded ✓

See that line and you're wired in — the agent now routes every plain-language request to the right experts and scales its process to the task. Head to How to Use the Agents for the full usage model.

Confirm & keep updated

  • Quick check: start a session — the loaded ✓ line should head the reply.
  • Deterministic check: run ./verify.sh (or !verify in-session, which runs workflows/verify_setup.md) to validate every entry-point file and the agent/skill/workflow/checklist counts.
  • Update: cd .mobile-agents && git pull.

What's Inside

Directory What it gives your agent Count
agents/ Loadable expert roles (architect, security, testing…) 14
skills/ Deep, single-topic know-how (auth, websockets, caching…) 31
workflows/ Step-by-step procedures (build a feature, integrate an API…) 11
checklists/ Objective, automatable review gates 8
standards/ Non-negotiable rules (coding, security, testing, git) 7
architecture/ Reference designs with Mermaid diagrams 6
prompts/ Copy-paste prompts for common tasks 10
templates/ Scaffolding with boilerplate Swift 8
examples/ Reference apps (banking, chat, CoffeeCraft, ecommerce, social) 5

Plus AGENTS.md (orchestration), GLOSSARY.md (shared terms), and a README.md index inside every directory.


The Agent Team

Each agent is a self-contained role: purpose, responsibilities, hard rules, coding standards, review checklist, common mistakes, and example tasks. They're organized into four tiers that hand off to each other (see AGENTS.md).

Strategy

Implementation

Quality & Hardening

Gate & Delivery


How to Use the Agents

There are only two ways to drive the toolkit, and you'll use the first one 95% of the time.

Way 1 — Just describe the task (the default)

Talk to your agent in plain language. The entry file reads the request, routes it to the right experts, and self-reviews — you never name a file:

> Build an Account Summary screen that loads /accounts and stores the token securely.

Way 2 — Name a file to steer it (for precision or to override routing)

Point the agent at a specific role, workflow, or checklist when you want exact control:

> Read agents/security_expert.md and act as that agent, then audit Sources/Auth.

What to type for common goals

Your goal Just say… Or steer with…
Build a feature "Build a profile screen that loads /me" workflows/create_feature.md
Add / change an API "Add the /transactions endpoint" workflows/integrate_rest_api.md
Add auth / login "Add OAuth login with secure token storage" agents/security_expert.md
Review a diff "Review my changes" checklists/code_review.md
Fix something slow "The feed scroll is janky, fix it" agents/performance_expert.md
Write tests "Write tests for AuthRepository" agents/testing_expert.md

You don't need to know which agent owns a task — that's the toolkit's job. Naming a file (Way 2) is just how you override or sharpen the automatic routing.

Per-tool syntax

The mental model above is identical in every tool; only the way you reference a file changes. The examples below show the file-steer form (Way 2).

Claude Code

CLAUDE.md loads automatically. Pull in a specific role or workflow:

> Read agents/security_expert.md and act as that agent.
> Audit Sources/Auth for credential issues using checklists/security_review.md.
> Follow workflows/integrate_rest_api.md to add the /transactions endpoint.
OpenAI Codex

AGENTS.md is read automatically. Reference files in your prompt:

Using agents/swiftui_expert.md and standards/swiftui_standards.md, build the
account summary screen described below.
Cursor

.cursorrules applies automatically. Add a file to context and prompt:

@workflows/integrate_graphql.md implement the feed query with pagination.
Windsurf

.windsurfrules is applied by Cascade. Reference files in chat:

@checklists/code_review.md review the open diff.
Gemini CLI

GEMINI.md loads automatically. Use @path to include files:

@agents/testing_expert.md @standards/testing_standards.md write tests for AuthRepository.
Aider

Add files to the chat session:

aider --read agents/ios_architect.md --read standards/architecture_standards.md

How It Works

You describe a task; the toolkit handles the assignment. Every request goes through the same four moves:

  1. Classify — the entry file reads your request and identifies its primary deliverable (architecture, UI, data, security, a test, a release).
  2. Route — it picks the one entry agent that owns that deliverable. You don't choose the agent; the request does.
  3. Chain — that agent hands off down the tiers (Strategy → Implementation → Hardening → Gate), scaling the chain to the task: a one-line fix gets the specialist plus a review, a new feature runs the full sequence.
  4. Self-review — the chain ends against the matching file in checklists/.

What loads when. Only the entry files (CLAUDE.md, AGENTS.md, GEMINI.md, .cursorrules, .windsurfrules) load at startup. Everything else — agents/, skills/, standards/, workflows/, checklists/ — is pulled in by the agent as the task needs it, so context stays lean. Naming a file yourself just overrides or sharpens this automatic routing.

Multi-platform by design. The agent detects your project's platform (iOS, Android, Flutter, React Native) and loads only that platform's subtree — skills/<topic>/<platform>/ and templates/<platform>/ — plus the shared, platform-neutral layers (standards/, architecture/, checklists/, workflows/). It never pulls another platform's code into context. iOS is the most complete today; see Contributing to help port the rest.

See AGENTS.md for the full routing table and the tier hierarchy, or the Example Workflows diagram below for a real multi-agent handoff.


Example Workflows

Ready-made, end-to-end procedures — each with inputs, steps, validation, and acceptance criteria:

Behind the scenes, a non-trivial task flows through multiple agents:

flowchart LR
    R[Feature Request] --> A[iOS Architect]
    A --> U[SwiftUI Expert]
    U --> N[Networking Expert]
    N --> S[Security Expert]
    S --> T[Testing Expert]
    T --> C[Code Reviewer]
    C --> Done([Merge-ready])
Loading

Best Practices

  1. Load the smallest sufficient context — the specific agent/skill/workflow, not the whole repo.
  2. Chain agents for real work: architect → implementer → reviewer.
  3. Always end with a checklist — have the agent self-review against checklists/.
  4. Treat standards as non-negotiable — reference standards/ for consistent output.
  5. Prefer workflows over ad-hoc prompts for anything you'll do more than once.

Design Principles

Every agent defaults to the same engineering values, so output looks like one team wrote it:

  • Clean Architecture + MVVM and SOLID by default.
  • Security is a requirement, not an afterthought (OWASP MASVS).
  • Testable, modular, observable code with explicit, typed error handling.
  • Consistent standards across sessions, tools, and contributors.

Contributing — everyone is welcome

This is a community toolkit, and it gets sharper with every perspective. You do not need to be an iOS engineer to help. Here's where people of every background fit in:

If you're a… You can help by…
iOS / Swift dev Sharpening agents, skills, and standards; adding patterns you ship in production
Android / Kotlin dev Porting iOS skills to Kotlin/Compose — Android parity is a top roadmap goal
Flutter / cross-platform dev Adding Flutter, React Native, or KMP equivalents of existing skills and agents
Backend / API dev Improving the networking, API-contract, and integration workflows
Tester / QA Strengthening the testing agent, the checklists, and test-strategy skills
Security reviewer Auditing the security standards and Keychain / crypto / pinning guidance
Critic / reviewer Running the agents on real tasks and filing where the output falls short
Writer / typo hunter Fixing typos, tightening wording, and improving clarity and examples
Web dev Building a docs site or landing page for the toolkit (open an issue to claim it)
Designer Improving the diagrams, the logo / banner, and visual explanations
Anyone Filing ideas and bug reports, starring, and sharing the repo

Three ways in, smallest effort first — pick whichever fits:

  1. Spot something off? Open an issue — a typo, a wrong recommendation, a missing topic, or just an idea.
  2. Have feedback on agent output? Tell us what you asked, what you got, and what a senior engineer would have done instead — that's some of the most valuable input we receive.
  3. Want to write code or docs? See CONTRIBUTING.md for setup, section templates, and style, then send a PR.

Good First Issues

New to the project? These are scoped, beginner-friendly, and have clear acceptance criteria — the perfect place to start:

Browse good first issues

Your first contribution in four steps:

  1. Pick an issue from the list above and comment that you're taking it.
  2. Fork & branchgit checkout -b feat/<short-name>.
  3. Make the change following the section templates, then run npm install && npm run lint.
  4. Open a PR with a Conventional Commit title (e.g. feat(skills): add SwiftData storage skill).

That's it — a maintainer will review and help you land it.


Roadmap

  • Kotlin/Compose and Flutter parity for the iOS-first skills.
  • Machine-readable agent manifests (YAML front-matter) for automated routing.
  • Expanded example apps with full test suites.
  • Evaluations that score agent output against the checklists.
  • Optional MCP server exposing skills as callable tools.

License

MIT © Sok Pich — free to use, fork, and adapt.

If this makes your AI a better mobile engineer, give it a ⭐ and share it.

About

AI-first engineering toolkit that turns coding agents (Claude Code, Codex, Cursor, Windsurf, Gemini CLI, Aider) into Senior mobile engineers — agents, skills, workflows, checklists & standards for iOS/Android/Cross-Platform.

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