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Swift Architecture

CommunityPopular
dpearson2699
swift-architecture

Selects, reviews, and migrates Apple-platform app architectures across MV with Observation, MVVM, MVI, TCA, Clean Architecture, Coordinator, and legacy VIPER. Use when choosing module and dependency boundaries, escalating a feature beyond simple SwiftUI MV, planning incremental architecture migration, or auditing state ownership and test seams.

Overview

Publisherdpearson2699
Repositoryswift-ios-skills
Skill nameswift-architecture
Stars
1.2K
Forks
61
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by dpearson2699 on GitHub. Read the source before you install it.

Installation

Install the Swift Architecture AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dpearson2699/swift-ios-skills/tree/main/skills/swift-architecture
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dpearson2699/swift-ios-skills.git /tmp/swift-ios-skills
mkdir -p .claude/skills
cp -r /tmp/swift-ios-skills/skills/swift-architecture .claude/skills/swift-architecture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Swift Architecture in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Swift Architecture on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Swift Architecture is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Swift Architecture

Choose the smallest architecture that makes state ownership, dependencies, side effects, and tests explicit. Default new SwiftUI features to MV; escalate only for observed complexity.

Contents

Scope Boundary

This skill owns pattern selection, module boundaries, dependency direction, migration strategy, and architecture-level test seams. Route SwiftUI property-wrapper wiring and view composition to swiftui-patterns, navigation APIs and route models to swiftui-navigation, isolation diagnostics to swift-concurrency, and test syntax/fixtures to swift-testing.

Decision Workflow

  1. Record the feature's state owner, inputs, outputs, dependencies, side effects, navigation handoffs, and current tests.
  2. Identify the concrete pressure: complex state machine, shared derived state, dependency control, feature composition, team ownership, or UIKit navigation.
  3. Select the smallest pattern that addresses that pressure; write down what it adds and what remains unchanged.
  4. Implement one vertical slice with injected dependencies and observable state transitions.
  5. Run existing behavior tests plus state-transition and dependency-failure tests. If behavior changes, restore the fixture, fix the smallest boundary, and rerun before migrating another slice.

Pattern Selection

PatternChoose whenMain cost
MVSwiftUI feature has straightforward state and orchestrationLogic can drift into large views without decomposition
MVVMPresentation logic needs an independently testable adapterExtra layer can become a forwarding shell
MVIA feature is best modeled as explicit state + intents + reducer/effectsBoilerplate and centralized transition design
TCAMany composable features need deterministic effects, dependencies, and testingFramework learning and architectural commitment
Clean ArchitectureLarge product needs strict dependency direction across domain/data/UIProtocol and mapping overhead
CoordinatorUIKit or hybrid navigation needs a separate flow ownerAnother lifecycle and routing owner
VIPERMaintaining an existing UIKit module with established VIPER boundariesVery high ceremony; poor default for new SwiftUI work

Use Coordinator alongside another state pattern when navigation complexity is the pressure; it is not a replacement for domain/state architecture.

MV Default

Keep views as state expressions and put business operations in observable models and injected services:

swift
@MainActor
@Observable
final class TripStore {
    private let client: TripClient
    var trips: [Trip] = []
    var error: Error?

    init(client: TripClient) { self.client = client }

    func load() async {
        do { trips = try await client.fetchTrips() }
        catch { self.error = error }
    }
}

struct TripList: View {
    @State private var store: TripStore

    init(client: TripClient) {
        _store = State(initialValue: TripStore(client: client))
    }

    var body: some View {
        List(store.trips) { Text($0.name) }
            .task { await store.load() }
    }
}

Load Architecture Pattern Recipes for MVVM, MVI, TCA, Clean Architecture, Coordinator, and VIPER structure.

Escalation Signals

  • Choose MVVM when substantial presentation transformation must be tested without rendering and the adapter has real behavior.
  • Choose MVI when transitions, invalid states, and effects need one auditable reducer-like path.
  • Choose TCA when feature composition, dependency overrides, cancellation, and deterministic effect tests recur across modules.
  • Choose Clean Architecture when independent domain rules and dependency direction matter across multiple delivery/data layers.
  • Add Coordinator for UIKit/hybrid route ownership, deep flow composition, or conditional navigation outside view controllers.
  • Keep VIPER for compatible legacy modules or deliberate migrations; do not start a new SwiftUI feature with it by habit.

Do not escalate merely because a view is long. First extract subviews, services, and focused observable models.

Migration

Migrate one feature boundary at a time:

  1. Freeze behavior with tests and a dependency/state inventory.
  2. Introduce the target boundary around existing operations.
  3. Move one state transition or dependency at a time without rewriting UI and persistence simultaneously.
  4. Compare behavior, navigation, cancellation, error, and persistence results after each slice.
  5. Remove the old path only after no callers or tests depend on it.

For ObservableObject to Observation, preserve the same owner and mutation isolation before replacing wrappers. For MVVM to MV, delete forwarding view-model members only after views bind to the same model/service behavior. For TCA adoption, wrap one feature's state/actions/effects and migrate dependencies incrementally.

Common Mistakes

MistakeFix
Pattern chosen by popularityTie it to an observed feature pressure.
View model only forwards propertiesRemove it and use MV.
One object owns navigation, networking, formatting, persistence, and UI stateSplit by responsibility and dependency direction.
TCA or Clean Architecture applied to trivial screensStart with MV and preserve an escalation seam.
Coordinator used as a state architectureKeep it focused on route/lifecycle ownership.
Multiple patterns mixed inside one featureDefine one local state/effect model and migrate at feature boundaries.
Big-bang migrationMove one tested vertical slice and rerun the same proof matrix.

Review Checklist

  • Choice is justified by concrete feature/team pressures
  • State owner, mutation path, dependencies, effects, and navigation owner are explicit
  • Dependencies are injected and replaceable in tests
  • Pattern cost is proportional to feature complexity
  • UI mechanics, navigation APIs, isolation, and test syntax route to sibling skills
  • Migration preserves behavior one vertical slice at a time
  • Failure, cancellation, navigation, and persistence behavior are verified after each slice
  • No forwarding-only layers or god objects remain

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Swift Architecture AI skill do?

Selects, reviews, and migrates Apple-platform app architectures across MV with Observation, MVVM, MVI, TCA, Clean Architecture, Coordinator, and legacy VIPER. Use when choosing module and dependency boundaries, escalating a feature beyond simple SwiftUI MV, planning incremental architecture migration, or auditing state ownership and test seams.

Why use Swift Architecture on TypingMind?

Because you install it once and use it with any model. Swift Architecture is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Swift Architecture in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dpearson2699/swift-ios-skills/tree/main/skills/swift-architecture. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Swift Architecture?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Swift Architecture?

As many as you like. As long as a model supports skills, you can use Swift Architecture with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Swift Architecture AI skill free?

It is published on GitHub by dpearson2699. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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