adamlyttleapps/claude-skill-aso-appstore-screenshots

Python

1,777

6 commits

updated Mar 30, 2026

See the code

README

ASO App Store Screenshots

A Claude Code skill that generates high-converting App Store screenshots for your iOS app. It analyzes your codebase, identifies core benefits, and creates professional screenshot images using AI.

What It Does

  1. Benefit Discovery — Analyzes your app's codebase to identify the 3-5 core benefits that drive downloads
  2. Screenshot Pairing — Reviews your simulator screenshots, rates them, and pairs each with the best benefit
  3. Generation — Creates polished App Store screenshots using a two-stage process: deterministic scaffolding (compose.py) + AI enhancement (Nano Banana Pro via Gemini MCP)
  4. Showcase — Generates a preview image with all screenshots side-by-side

Installation

1. Add the skill to Claude Code

claude install-skill github.com/adamlyttleapps/claude-skill-aso-appstore-screenshots

2. Install Python dependencies

pip install Pillow

3. Font requirement

The skill uses SF Pro Display Black for headline text. On macOS, install it from Apple's developer fonts. The expected path is:

/Library/Fonts/SF-Pro-Display-Black.otf

4. Set up Gemini MCP (for AI enhancement)

The generation phase requires @houtini/gemini-mcp to be configured as an MCP server in Claude Code:

npm install -g @houtini/gemini-mcp

Then add it to your Claude Code MCP config (~/.claude/settings.json or project .mcp.json).

Usage

From within your app's project directory, run:

/aso-appstore-screenshots

The skill will guide you through each phase interactively. Progress is saved to Claude Code's memory system, so you can resume across conversations.

How It Works

Scaffold → Enhance Pipeline

Rather than generating screenshots from scratch (which produces inconsistent results), the skill uses a two-stage approach:

  1. compose.py creates a deterministic scaffold with exact text positioning, device frame, and your simulator screenshot composited inside
  2. Nano Banana Pro (via Gemini MCP) enhances the scaffold — adding a photorealistic device frame, breakout elements, and visual polish

This ensures consistent layout across all screenshots while letting AI handle the creative enhancement.

Output

Screenshots are saved to a screenshots/ directory in your project:

screenshots/
  01-benefit-slug/          ← working versions
    scaffold.png            ← deterministic compose.py output
    v1.png, v2.png, v3.png  ← AI-enhanced versions
    v1-resized.png, ...     ← cropped to App Store dimensions
  final/                    ← approved screenshots, ready to upload
    01-benefit-slug.png
    02-benefit-slug.png
  showcase.png              ← preview image with all screenshots

The final/ folder contains App Store-ready screenshots at exact Apple dimensions (default: 1290×2796px for iPhone 6.7").

Files

FilePurpose
SKILL.mdThe skill prompt — defines the multi-phase workflow
compose.pyDeterministic scaffold generator (Pillow-based)
generate_frame.pyGenerates the device frame template
showcase.pyGenerates the side-by-side showcase image
assets/device_frame.pngPre-rendered iPhone device frame template

License

MIT

adamlyttleapps/claude-skill-aso-appstore-screenshots

Python

1,777

6 commits

updated Mar 30, 2026

See the code

README

ASO App Store Screenshots

A Claude Code skill that generates high-converting App Store screenshots for your iOS app. It analyzes your codebase, identifies core benefits, and creates professional screenshot images using AI.

What It Does

  1. Benefit Discovery — Analyzes your app's codebase to identify the 3-5 core benefits that drive downloads
  2. Screenshot Pairing — Reviews your simulator screenshots, rates them, and pairs each with the best benefit
  3. Generation — Creates polished App Store screenshots using a two-stage process: deterministic scaffolding (compose.py) + AI enhancement (Nano Banana Pro via Gemini MCP)
  4. Showcase — Generates a preview image with all screenshots side-by-side

Installation

1. Add the skill to Claude Code

claude install-skill github.com/adamlyttleapps/claude-skill-aso-appstore-screenshots

2. Install Python dependencies

pip install Pillow

3. Font requirement

The skill uses SF Pro Display Black for headline text. On macOS, install it from Apple's developer fonts. The expected path is:

/Library/Fonts/SF-Pro-Display-Black.otf

4. Set up Gemini MCP (for AI enhancement)

The generation phase requires @houtini/gemini-mcp to be configured as an MCP server in Claude Code:

npm install -g @houtini/gemini-mcp

Then add it to your Claude Code MCP config (~/.claude/settings.json or project .mcp.json).

Usage

From within your app's project directory, run:

/aso-appstore-screenshots

The skill will guide you through each phase interactively. Progress is saved to Claude Code's memory system, so you can resume across conversations.

How It Works

Scaffold → Enhance Pipeline

Rather than generating screenshots from scratch (which produces inconsistent results), the skill uses a two-stage approach:

  1. compose.py creates a deterministic scaffold with exact text positioning, device frame, and your simulator screenshot composited inside
  2. Nano Banana Pro (via Gemini MCP) enhances the scaffold — adding a photorealistic device frame, breakout elements, and visual polish

This ensures consistent layout across all screenshots while letting AI handle the creative enhancement.

Output

Screenshots are saved to a screenshots/ directory in your project:

screenshots/
  01-benefit-slug/          ← working versions
    scaffold.png            ← deterministic compose.py output
    v1.png, v2.png, v3.png  ← AI-enhanced versions
    v1-resized.png, ...     ← cropped to App Store dimensions
  final/                    ← approved screenshots, ready to upload
    01-benefit-slug.png
    02-benefit-slug.png
  showcase.png              ← preview image with all screenshots

The final/ folder contains App Store-ready screenshots at exact Apple dimensions (default: 1290×2796px for iPhone 6.7").

Files

FilePurpose
SKILL.mdThe skill prompt — defines the multi-phase workflow
compose.pyDeterministic scaffold generator (Pillow-based)
generate_frame.pyGenerates the device frame template
showcase.pyGenerates the side-by-side showcase image
assets/device_frame.pngPre-rendered iPhone device frame template

License

MIT

Significant stargazers

Vincent

7 followers · starred Mar 2026

Steven Nguyen

345 followers · starred Mar 2026

Junbum Lee

953 followers · starred Jun 2026

Mark Phelps

187 followers · starred Mar 2026