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App Store Optimization

Checked
borghei·vlatest·marketing

Optimize app store listings with data-driven keyword research, A/B testing, and competitor analysis for increased visibility.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add borghei/claude-skills --skill app-store-optimization -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

borghei

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned borghei/claude-skills at 4a698e8d07.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
20 files, 7,743 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill helps optimize your mobile application's presence in app stores. It analyzes keywords, competitor strategies, and app store listing elements to suggest improvements for increased visibility and downloads. The skill aims to improve App Store Optimization (ASO) through data-driven recommendations.

When to use it

  • You want to increase the number of organic downloads for your mobile application.
  • Your app is struggling to rank well in relevant search results within app stores.
  • You need help identifying high-impact keywords for your app store listing.
  • You're looking for a competitive analysis of similar apps on the market.

Key capabilities

  • Keyword research and suggestion
  • Competitor analysis
  • App store listing optimization recommendations

Example prompts

  • "Analyze my app 'MyFitnessTracker' and suggest keywords to improve its ranking in the Apple App Store."
  • "Compare my app 'PhotoEditorPro' with competitor apps like 'PicsArt' and provide ASO insights."
  • "Give me suggestions for improving the description of my Android app, 'RecipeMaster'."

Tips & gotchas

The effectiveness of this skill depends on providing accurate information about your application and target market. Results should be considered alongside other marketing efforts and may require experimentation to achieve optimal results.