Feature Flags logo

Feature Flags

Community
rshankras
feature-flags

Generate feature flag infrastructure with local defaults, remote configuration, SwiftUI integration, and debug menu. Use when adding feature flags or A/B testing to iOS/macOS apps.

Overview

Publisherrshankras
Repositoryclaude-code-apple-skills
Skill namefeature-flags
Stars
744
Forks
70
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Feature Flags 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.
  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/rshankras/claude-code-apple-skills.git /tmp/claude-code-apple-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-apple-skills/skills/generators/feature-flags .claude/skills/feature-flags
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feature Flags 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 Feature Flags 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 Feature Flags 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.

Feature Flags Generator

Generate a complete feature flag infrastructure with typed flag definitions, protocol-based providers (local, remote, composite), SwiftUI environment integration, an @Observable manager, and a debug menu for toggling flags at runtime.

When This Skill Activates

Use this skill when the user:

  • Asks to "add feature flags" or "add feature toggles"
  • Mentions A/B testing or gradual rollouts
  • Asks about Firebase Remote Config or similar remote configuration
  • Wants to disable features without shipping an app update
  • Mentions "kill switches" or "feature gates"
  • Wants to control features remotely for a subset of users
  • Asks for a debug menu to toggle features during development

Pre-Generation Checks

1. Project Context Detection

  • Check for existing feature flag implementations
  • Check for Firebase Remote Config or third-party flag SDKs
  • Identify source file locations (Sources/, App/, or root)
  • Verify minimum deployment target (iOS 17+ / macOS 14+ for @Observable)

2. Conflict Detection

Search for existing feature flag code:

Glob: **/*FeatureFlag*.swift, **/*FeatureToggle*.swift, **/*RemoteConfig*.swift
Grep: "FeatureFlag" or "FeatureToggle" or "RemoteConfig" or "isFeatureEnabled"

If existing feature flag code is found:

  • Ask whether to replace or extend the existing implementation
  • Check for flag names or enum cases that could conflict

If a third-party SDK (Firebase, LaunchDarkly, etc.) is detected:

  • Ask if the user wants a standalone implementation or a wrapper around the SDK

3. Required Capabilities

Feature flags require:

  • iOS 17+ / macOS 14+ deployment target (for @Observable manager)
  • Network access entitlement if using remote flags
  • No special Info.plist entries needed

Configuration Questions

Ask user via AskUserQuestion:

  1. What features do you want to flag? (freeform)

    • Examples: new onboarding, premium paywall, experimental UI, dark mode v2
    • This determines the flag enum cases and their default values
  2. What flag value types do you need?

    • Boolean only (feature on/off)
    • Boolean + String (on/off plus string configuration)
    • Boolean + String + Integer (full typed support)
    • Boolean + String + Integer + JSON (for complex configurations)
  3. What provider architecture?

    • Local only -- UserDefaults-based with compile-time defaults
    • Remote only -- JSON endpoint with local caching
    • Composite (recommended) -- Local defaults with remote override; remote wins when available
  4. Include debug menu?

    • Yes -- SwiftUI view for toggling flags at runtime (DEBUG builds only)
    • No -- Skip the debug view
  5. Include SwiftUI environment integration?

    • Yes (recommended) -- Inject the flag manager via SwiftUI Environment
    • No -- Use the manager directly

Generation Process

Step 1: Determine File Locations

Check project structure:

  • If Sources/ exists --> Sources/FeatureFlags/
  • If App/ exists --> App/FeatureFlags/
  • Otherwise --> FeatureFlags/

Step 2: Create Core Files

Generate these files based on configuration answers:

  1. FeatureFlag.swift -- Flag enum with typed default values
  2. FeatureFlagService.swift -- Protocol defining provider interface
  3. LocalFeatureFlagProvider.swift -- UserDefaults-based provider with debug overrides
  4. RemoteFeatureFlagProvider.swift -- URL-based provider with disk caching (if remote or composite)
  5. CompositeFeatureFlagProvider.swift -- Combines local + remote; remote overrides local (if composite)
  6. FeatureFlagManager.swift -- @Observable manager for SwiftUI
  7. FeatureFlagEnvironmentKey.swift -- SwiftUI Environment integration (if requested)
  8. FeatureFlagDebugView.swift -- Debug toggle view (if requested)

Step 3: Generate Code from Templates

Use the templates in templates.md and customize based on user answers:

  • Replace placeholder flag cases with real feature names
  • Set appropriate default values per flag
  • Include or exclude remote/composite providers based on architecture choice
  • Include or exclude typed value methods (string, int, JSON) based on type selection
  • Include or exclude environment key and debug view

Output Format

After generation, provide:

Files Created

Sources/FeatureFlags/
├── FeatureFlag.swift                    # Flag enum with typed defaults
├── FeatureFlagService.swift             # Provider protocol
├── LocalFeatureFlagProvider.swift       # UserDefaults-based provider
├── RemoteFeatureFlagProvider.swift      # URL-based provider (if remote/composite)
├── CompositeFeatureFlagProvider.swift   # Local + remote combiner (if composite)
├── FeatureFlagManager.swift             # @Observable manager for SwiftUI
├── FeatureFlagEnvironmentKey.swift      # SwiftUI Environment key (if requested)
└── FeatureFlagDebugView.swift           # Debug toggle menu (if requested)

Integration Steps

1. Initialize the manager in your App struct or entry point:

swift
import SwiftUI

@main
struct MyApp: App {
    @State private var featureFlagManager: FeatureFlagManager

    init() {
        // Local only
        let provider = LocalFeatureFlagProvider()

        // Or composite (remote overrides local)
        // let provider = CompositeFeatureFlagProvider(
        //     local: LocalFeatureFlagProvider(),
        //     remote: RemoteFeatureFlagProvider(
        //         endpoint: URL(string: "https://api.example.com/flags")!
        //     )
        // )

        _featureFlagManager = State(initialValue: FeatureFlagManager(provider: provider))
    }

    var body: some Scene {
        WindowGroup {
            ContentView()
                .environment(featureFlagManager)
        }
    }
}

2. Use flags in your views:

swift
struct ContentView: View {
    @Environment(FeatureFlagManager.self) private var flags

    var body: some View {
        VStack {
            if flags.isEnabled(.newOnboarding) {
                NewOnboardingView()
            } else {
                LegacyOnboardingView()
            }
        }
    }
}

3. Refresh remote flags (if using remote or composite):

swift
// Refresh on app launch or periodically
Task {
    try await featureFlagManager.refresh()
}

4. Add debug menu (if generated, DEBUG builds only):

swift
#if DEBUG
NavigationLink("Feature Flags") {
    FeatureFlagDebugView()
        .environment(featureFlagManager)
}
#endif

Testing Instructions

  1. Unit test providers independently: Each provider conforms to FeatureFlagService and can be tested in isolation.
  2. Mock provider for previews and tests:
    swift
    final class MockFeatureFlagProvider: FeatureFlagService {
        var overrides: [FeatureFlag: Bool] = [:]
    
        func isEnabled(_ flag: FeatureFlag) -> Bool {
            overrides[flag] ?? flag.defaultValue
        }
        // ... implement remaining protocol methods
    }
  3. Debug menu: Run in DEBUG builds, navigate to the debug menu, and toggle flags to verify behavior.
  4. Remote provider: Use a local JSON file served via a test server or mock URLProtocol to test remote fetching.

Common Patterns

Boolean Flags (Kill Switches)

The most common pattern. Enable or disable a feature entirely.

swift
if flags.isEnabled(.premiumPaywall) {
    PremiumPaywallView()
}

String Flags (Copy Variants / A/B Testing)

Use string values to serve different text or configuration strings remotely.

swift
let welcomeMessage = flags.stringValue(.welcomeMessage) ?? "Welcome!"
Text(welcomeMessage)

Integer Flags (Thresholds / Limits)

Control numeric parameters like retry counts, page sizes, or rate limits.

swift
let maxRetries = flags.intValue(.maxRetries) ?? 3

JSON Flags (Complex Configuration)

For structured configuration that changes server-side.

swift
struct PaywallConfig: Codable {
    let title: String
    let trialDays: Int
    let showTestimonials: Bool
}

if let config: PaywallConfig = flags.jsonValue(.paywallConfig) {
    PaywallView(config: config)
}

Gradual Rollout

Combine feature flags with user segmentation.

swift
// Server returns different flag values per user segment
// The flag is simply on/off from the client perspective
if flags.isEnabled(.newCheckoutFlow) {
    NewCheckoutView()
} else {
    LegacyCheckoutView()
}

Gotchas

  • Stale flags: Always provide sensible local defaults. If the remote fetch fails, the app must still function correctly with local values.
  • Flag cleanup: After a feature is fully rolled out, remove the flag enum case, delete related conditional code, and clean up remote configuration. Stale flags accumulate technical debt.
  • Thread safety: The generated FeatureFlagManager is @MainActor-isolated. Access it on the main thread or via @Environment in SwiftUI views. The providers use Sendable-conforming storage.
  • Testing both paths: When a flag controls a UI branch, write tests (or at least manual test plans) for both the enabled and disabled paths. It is easy to forget the disabled path once a flag has been on for weeks.
  • Debug overrides in production: The debug override mechanism uses #if DEBUG guards. Double-check that debug toggles never leak into release builds.
  • Cache invalidation: The remote provider caches to disk. Set an appropriate cacheDuration (default 5 minutes). For time-sensitive flags, call refresh() explicitly.
  • UserDefaults key collisions: All flag keys are prefixed with ff_ to avoid collisions with other UserDefaults entries in the app.

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 Feature Flags AI skill do?

Generate feature flag infrastructure with local defaults, remote configuration, SwiftUI integration, and debug menu. Use when adding feature flags or A/B testing to iOS/macOS apps.

Why use Feature Flags on TypingMind?

Because you install it once and use it with any model. Feature Flags 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 Feature Flags in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rshankras/claude-code-apple-skills/tree/main/skills/generators/feature-flags. 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 Feature Flags?

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 Feature Flags?

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

Is the Feature Flags AI skill free?

Yes. It is published on GitHub by rshankras under the MIT license. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇