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Appstore Launch

npx machina-cli add skill fredzannarbor/agentic-social-feed/appstore-launch --openclaw
Files (1)
SKILL.md
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Generate App Store launch assets (text, images, screenshots, video scripts) for a macOS, iOS, or iPadOS app.

Usage

/appstore-launch [app_path_or_config] [--images-only] [--text-only]

Arguments

  • app_path_or_config (optional): Path to either:
    • An Xcode project directory (will analyze and generate config)
    • A JSON config file (will use directly)
    • If omitted, will prompt interactively for app details
  • --images-only: Only generate images (icons, screenshots, banners)
  • --text-only: Only generate text assets (descriptions, keywords, etc.)

Examples

/appstore-launch ~/xcode_projects/MyApp
/appstore-launch ./my_app_config.json
/appstore-launch

What This Skill Does

  1. Analyzes your app (if given an Xcode project path):

    • Reads Swift source files to understand features
    • Extracts version info from project settings
    • Identifies key views and functionality
  2. Generates App Store text assets (appstore_assets/):

    • appstore_content.md - Full description, subtitle, promotional text
    • appstore_content.json - Machine-readable version
    • screenshot_guide.md - Screenshot scenes with captions
    • video_storyboard.md - 30-second app preview script
    • promotional_variants.json - Social media posts (Twitter, LinkedIn, Product Hunt)
    • keywords_analysis.md - Optimized keywords with suggestions
    • localization_template.json - Ready for translation
    • asset_checklist.md - Complete launch checklist
  3. Generates App Store images (appstore_images/):

    • icons/ - App icons at all required sizes (16x16 to 1024x1024)
    • screenshots/ - Marketing screenshots with text overlays for each device size
    • banners/ - Social media banners (Twitter, Facebook, LinkedIn, Instagram)
  4. Outputs to: {project_dir}/appstore_assets/ and {project_dir}/appstore_images/

Steps

If given an Xcode project path:

  1. First, explore the project to understand its structure:

    • Find Swift files and read key ones (ContentView, App file, feature views)
    • Look for existing AboutView, version info, feature documentation
    • Identify the app's main features and functionality
  2. Create a JSON config file from the analysis:

    • App name, version, bundle ID from project settings
    • Features extracted from code and documentation
    • Target audiences inferred from functionality
  3. Generate text assets using LLM capabilities:

    • App Store description optimized for ASO
    • Compelling subtitle and promotional text
    • Screenshot captions and video storyboard
  4. Generate image assets:

    • App icons at all required resolutions
    • Marketing screenshots with device frames
    • Social media banners

If given a config file:

Use the provided configuration directly to generate all assets.

If no arguments:

  1. Ask the user for key information:

    • App name and version
    • Platform (macOS, iOS, iPadOS)
    • Key features (3-5)
    • Target audiences (2-3)
    • Pricing model
  2. Generate a config and produce all assets

Config File Schema

If you want to create a config file manually, use this structure:

{
  "name": "App Name",
  "version": "1.0.0",
  "codename": "Optional Release Name",
  "bundle_id": "com.example.appname",
  "developer": "Developer Name",
  "platform": "macOS",

  "primary_category": "Productivity",
  "secondary_category": "Business",
  "age_rating": "4+",
  "price_tier": "Free with In-App Purchases",

  "tagline": "Short marketing tagline",
  "subtitle": "30 character subtitle",
  "description_intro": "Opening paragraph for description",
  "whats_new_intro": "What's new in this version",

  "features": [
    {
      "title": "Feature Name",
      "description": "What this feature does",
      "icon": "sf.symbol.name",
      "marketing_hook": "Why users care",
      "is_premium": false
    }
  ],

  "premium_features": [
    "Premium feature 1",
    "Premium feature 2"
  ],

  "target_audiences": [
    {
      "role": "Audience Name",
      "use_case": "How they use the app",
      "pain_point": "Problem it solves"
    }
  ],

  "min_os_version": "14.0",
  "technologies": ["SwiftUI", "PDFKit", "SwiftData"],
  "keywords": ["keyword1", "keyword2"],

  "support_url": "https://example.com/support",
  "privacy_policy_url": "https://example.com/privacy"
}

Platform Support

  • macOS: MacBook Pro 16", 14", iMac resolutions
  • iOS: iPhone 6.7", 6.5", 5.5" resolutions
  • iPadOS: iPad Pro 12.9", 11" resolutions

Output

After running, you'll have a complete set of App Store assets:

Text Assets (appstore_assets/)

FilePurpose
appstore_content.mdHuman-readable text content
appstore_content.jsonMachine-readable content
screenshot_guide.mdScreenshot capture guide
screenshot_specs.jsonResolution requirements
video_storyboard.mdApp preview video script
promotional_variants.jsonSocial media posts
keywords_analysis.mdKeyword optimization
localization_template.jsonTranslation template
asset_checklist.mdLaunch checklist

Image Assets (appstore_images/)

DirectoryContents
icons/App icons: 16x16, 32x32, 64x64, 128x128, 256x256, 512x512, 1024x1024 PNG
screenshots/Marketing screenshots at each device resolution with feature overlays
banners/Social media banners: Twitter (1200x675), Facebook (1200x630), LinkedIn (1200x627), Instagram (1080x1080)

Tips

  • Review and customize the generated content before submission
  • Use the screenshot guide to capture consistent screenshots
  • The video storyboard helps plan your 15-30 second app preview
  • Social media posts are ready to copy and customize

Source

git clone https://github.com/fredzannarbor/agentic-social-feed/blob/main/plugins/appstore-launch/skills/appstore-launch/SKILL.mdView on GitHub

Overview

Generates a complete set of App Store launch assets for macOS, iOS, and iPadOS apps. Outputs text, images, and video scripts organized under appstore_assets and appstore_images to streamline ASO and marketing.

How This Skill Works

The skill analyzes the provided Xcode project or JSON config to extract app features, version, and key views. It then uses AI to produce ASO-optimized text assets, screenshot captions, a 30-second video storyboard, keywords, localization templates, and all required images, writing them to appstore_assets and appstore_images. Users can opt to generate only text or only images with flags.

When to Use It

  • Preparing a fresh app launch and need a full ASO pack (text + images + video)
  • Updating assets after a feature release or version bump
  • Revising keywords and descriptions to improve App Store ranking
  • Producing marketing assets for social campaigns tied to the app
  • Creating localization-ready templates for translation

Quick Start

  1. Step 1: Provide an app path or config, e.g. /appstore-launch /path/to/MyApp or ./config.json
  2. Step 2: Optional flags: --images-only or --text-only to limit output
  3. Step 3: Run the command and retrieve assets from appstore_assets/ and appstore_images/

Best Practices

  • Provide accurate app name, version, and platform to tailor descriptions and icon sizes
  • List 3–5 core features to guide asset generation and avoid feature gaps
  • Review ASO guidelines and adjust keywords, subtitles, and descriptions accordingly
  • Validate assets across device sizes with device frames in screenshots
  • Use localization_template.json to prepare translations and maintain consistency

Example Use Cases

  • HabitFlow iOS app: ASO-optimized description, feature-driven screenshots, and 30s video storyboard
  • NoteForge macOS app: marketing banners and desktop-optimized screenshots with captions
  • WeatherNow iPadOS app: device-appropriate screenshots and banners for multi-device campaigns
  • BudgetBuddy macOS: keyword-rich description and localization-ready assets
  • TaskFlow Pro iOS: social-ready promotional variants and cross-platform asset alignment

Frequently Asked Questions

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