Agent skill

App Store Aso

by TimBroddin in TimBroddin/app-store-aso-skill

Generate optimized Apple App Store metadata recommendations with ASO best practices.

MITAuto-check passedMobile

Install App Store Aso

skills CLI
$ npx skills add TimBroddin/app-store-aso-skill --skill app-store-aso -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TimBroddin/app-store-aso-skill app-store-aso --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
app-store-aso
GitHub stars
100
Token cost
~1.5k tokens
SKILL.md length
525 words
Files
6 (incl. scripts, references)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Generate optimized Apple App Store metadata recommendations with ASO best practices.

  • Works in 5 steps: Analyze the App Context → Load ASO Knowledge Base → Generate Optimized Metadata → …
  • Analyzing app listings
  • SKILL.md covers Overview, Core Workflow, Apple App Store Character Limits and Metadata Validation Process, plus 3 more sections
  • Runs Python scripts from its folder; calls python, bun and bunx

What it does

App Store Aso is an agent skill from TimBroddin/app-store-aso-skill. Generate optimized Apple App Store metadata recommendations with ASO best practices. Use this skill when analyzing app listings, optimizing metadata (title, subtitle, description, keywords), performing competitive analysis, or validating App Store listing requirements. Triggers on queries about App Store optimization, metadata review, or screenshot strategy.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `README.md`, `references/aso_learnings.md` and `scripts/validate_metadata.py`).

It sits in Mobile, covering App store release. The repository describes itself as: Claude Code skill for Apple App Store ASO optimization with automated validation. The licence is MIT.

When your agent uses it

  • Analyzing app listings
  • Optimizing metadata (title
  • Performing competitive analysis
  • Validating App Store listing requirements

Example prompts

  • “/app-store-aso”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Analyze the App Context
  2. Load ASO Knowledge Base
  3. Generate Optimized Metadata
  4. Validate Character Counts
  5. Provide Screenshot Strategy

What it can do on your machine

Read from SKILL.md and the folder at commit 3f0b917. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • bun
    • bunx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use bunx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

App Store Aso loads about 1.5k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 94 tokens; SKILL.md has 525 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~94
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~13k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from TimBroddin/app-store-aso-skill at commit 3f0b917, republished under its MIT licence (© TimBroddin). 525 words, ~1,485 tokens.

Download SKILL.mdSave it as .claude/skills/app-store-aso/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
app-store-aso
description
Generate optimized Apple App Store metadata recommendations with ASO best practices. Use this skill when analyzing app listings, optimizing metadata (title, subtitle, description, keywords), performing competitive analysis, or validating App Store listing requirements. Triggers on queries about App Store optimization, metadata review, or screenshot strategy.

Apple App Store ASO Optimization

Overview

This skill enables comprehensive Apple App Store Optimization (ASO) analysis and metadata generation. Analyze existing app listings, generate optimized metadata following Apple's guidelines and character limits, provide competitive insights, and recommend screenshot storyboard strategies.

Core Workflow

When a user requests ASO optimization or metadata review:

  1. Analyze the App Context

    • Understand the app's purpose, features, and target audience
    • Identify unique value propositions and competitive differentiators
    • Note any changes or updates the user mentions
  2. Load ASO Knowledge Base

    • Reference references/aso_learnings.md for comprehensive ASO best practices
    • Apply competitive analysis strategies
    • Use proven optimization patterns
  3. Generate Optimized Metadata

    • Create optimized app name, subtitle, and promotional text
    • Write compelling description with keyword optimization
    • Generate keyword list with strategic placement
    • Ensure all metadata follows Apple's character limits
  4. Validate Character Counts

    • Use scripts/validate_metadata.py to verify all metadata meets Apple's requirements
    • Display validation results with character counts and limit compliance
    • Flag any violations with specific corrections needed
  5. Provide Screenshot Strategy

    • Recommend screenshot storyboard sequence
    • Suggest messaging hierarchy and visual focus areas
    • Align screenshot strategy with metadata messaging

Apple App Store Character Limits

Critical Limits to Validate:

  • App Name: 30 characters maximum
  • Subtitle: 30 characters maximum
  • Promotional Text: 170 characters maximum
  • Description: 4,000 characters maximum
  • Keywords: 100 characters maximum (comma-separated, no spaces)
  • What's New: 4,000 characters maximum

Metadata Validation Process

After generating recommendations, always validate using the validation script:

bash
python scripts/validate_metadata.py

The script will:

  1. Prompt for each metadata field
  2. Calculate character counts
  3. Check against Apple's limits
  4. Display results with ✅ (pass) or ❌ (fail) indicators
  5. Show exact character counts and remaining characters

Integration Pattern:

  • Generate metadata recommendations
  • Run validation script with recommended content
  • Display validation results to user
  • Adjust any failing fields and re-validate

Output Format

Structure recommendations as:

📱 App Metadata Recommendations

App Name (X/30 characters) [optimized name]

Subtitle (X/30 characters) [optimized subtitle]

Promotional Text (X/170 characters) [promotional text]

Keywords (X/100 characters) [keyword,list,no,spaces]

Description (X/4000 characters) [full description]

Show full SKILL.md (204 more words)Show less
🎯 Competitive Analysis

[Key insights and positioning recommendations]

📸 Screenshot Storyboard Strategy

[Ordered list of screenshot recommendations with messaging]

✅ Validation Results

[Output from validation script showing compliance]

Krankie: App Store Ranking Tracker

Krankie is an agent-first CLI tool for tracking App Store keyword rankings. Use it to monitor keyword performance, track ranking changes over time, and inform ASO optimization decisions with real data.

Installation
bash
bun install -g krankie
# or run directly
bunx krankie
Key Commands

App Management:

bash
# Search for apps
krankie app search "<query>" --platform ios

# Add an app to track
krankie app create <app_id> --platform ios

# List tracked apps
krankie app list

Keyword Tracking:

bash
# Add keywords to track for an app
krankie keyword add <app_id> "<keyword>" --store us

# List tracked keywords
krankie keyword list

Ranking Checks:

bash
# Run ranking checks for all tracked keywords
krankie check run

# View current rankings
krankie rankings

# See biggest movers (gains/losses)
krankie rankings movers

# View ranking history for a keyword
krankie rankings history <keyword_id>

# Check status of last run
krankie check status

Automation:

bash
# Install daily cron job (default: 6 AM)
krankie cron install --hour 6

# Check cron status
krankie cron status
Agent Integration

All commands support --json flag for structured output:

bash
krankie rankings --json
krankie app list --json

Get agent-friendly instructions:

bash
krankie instructions --format json
Data Notes
  • Rankings track positions 1-200; null indicates outside this range
  • Data stored locally in ~/.krankie/krankie.db (SQLite)
  • Daily re-checks are rate-limited; use --force to override
  • Logs available at ~/.krankie/check.log
ASO Workflow Integration
  1. Before optimization: Use krankie rankings to establish baseline keyword positions
  2. Competitive analysis: Track competitor apps and their keyword rankings
  3. After metadata changes: Monitor krankie rankings movers to measure impact
  4. Trend analysis: Use krankie rankings history to identify patterns

Resources

scripts/validate_metadata.py

Python script that validates App Store metadata against Apple's character limits. Provides interactive validation with clear pass/fail indicators.

references/aso_learnings.md

Comprehensive ASO knowledge base containing optimization strategies, competitive analysis frameworks, keyword research techniques, and proven best practices. Load this file to inform all ASO recommendations.

© TimBroddin, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references) in the repository root of TimBroddin/app-store-aso-skill.

  • SKILL.md
  • .gitignore
  • LICENSE
  • README.md
  • references/aso_learnings.md
  • scripts/validate_metadata.py

Open the folder on GitHubat commit 3f0b917

Compare with similar skills

App Store Aso next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

App Store Aso compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
App Store Aso this skillTimBroddin/app-store-aso-skill100—~1.5kAutomated safety check: PassMIT
App Preview Videoappeeky/aso-skills2.2k—~1.6kAutomated safety check: PassMIT
Keyword Optimizerrshankras/claude-code-apple-skills787—~2.4kAutomated safety check: PassMIT
Screenshot Plannerrshankras/claude-code-apple-skills787—~2.1kAutomated safety check: PassMIT
Shotshashgraph-online/awesome-codex-plugins1.3k—~2.4kAutomated safety check: PassMIT
Aso Appstore Screenshotsadamlyttleapps/claude-skill-aso-appstore-screenshots1.8k1 repos~9.6kAutomated safety check: PassMIT

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Questions about App Store Aso

What does App Store Aso do?

Generate optimized Apple App Store metadata recommendations with ASO best practices. App Store Aso is an agent skill from TimBroddin/app-store-aso-skill. Generate optimized Apple App Store metadata recommendations with ASO best practices.

When should I use App Store Aso?

App Store Aso fits situations like: analyzing app listings; optimizing metadata (title; performing competitive analysis; validating App Store listing requirements.

How do I install App Store Aso in Claude Code?

Run `npx skills add TimBroddin/app-store-aso-skill --skill app-store-aso -a claude-code`. Or copy the skill folder (the TimBroddin/app-store-aso-skill repository) into .claude/skills/app-store-aso in your project. Claude Code loads it when a task matches its description.

How do I install App Store Aso in Codex?

Run `npx skills add TimBroddin/app-store-aso-skill --skill app-store-aso -a codex`. Or copy the skill folder (the TimBroddin/app-store-aso-skill repository) into .agents/skills/app-store-aso in your project. Codex loads it when a task matches its description.

Can I use App Store Aso in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TimBroddin/app-store-aso-skill --skill app-store-aso -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/app-store-aso, .gemini/skills/app-store-aso, .github/skills/app-store-aso and .opencode/skills/app-store-aso in your project.

What does App Store Aso need to run?

Going by SKILL.md and its folder, App Store Aso needs Python for the scripts in its folder and the command-line tools its instructions call (python, bun and bunx). Our summary lists: Python 3.

Does App Store Aso access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is App Store Aso safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does App Store Aso use?

App Store Aso is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does App Store Aso use?

About 1.5k tokens (SKILL.md is roughly 5.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 12k tokens, read only when the agent opens those files.

What are the alternatives to App Store Aso?

Skills that share tags, products or a category with App Store Aso: App Preview Video (appeeky/aso-skills, 2.2k stars), Keyword Optimizer (rshankras/claude-code-apple-skills, 787 stars), Screenshot Planner (rshankras/claude-code-apple-skills, 787 stars) and Shots (hashgraph-online/awesome-codex-plugins, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains App Store Aso?

TimBroddin (a GitHub user) maintains it in TimBroddin/app-store-aso-skill, which has 100 GitHub stars. The repository was last updated on May 4, 2026.

Source: TimBroddin/app-store-aso-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.