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Ab Test Store Listing

Checked
eronred·vlatest·testing·MIT

Automatically runs A/B tests on app store listings to optimize conversion rates and keyword performance.

Repository

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 appeeky/aso-skills --skill ab-test-store-listing -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

eronred

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 eronred/aso-skills at 8de1ee18d8.

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

Commit
8de1ee18d8
Manifest
skills/ab-test-store-listing/SKILL.md
Scanned
1 file, 215 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 enables AI agents to retrieve and analyze store listing data specifically designed for A/B testing scenarios. It allows agents to compare different app store configurations, such as icons, screenshots, or descriptions, to determine which variations drive better performance metrics.

When to use it

  • Optimizing an app's metadata by comparing conversion rates between two distinct store listing versions.
  • Identifying the most effective visual assets (icons or hero images) for a specific target audience segment.
  • Validating hypotheses about how changing keyword-rich descriptions impacts organic search visibility in app stores.
  • Automating the selection of the winning store variant based on real-time download data.

Key capabilities

  • Fetches current A/B test configurations from major app stores.
  • Aggregates performance metrics for different listing variations.
  • Compares key attributes like install rates, click-through rates, and user retention across variants.
  • Provides structured data output for further analysis or decision-making.

Example prompts

  • "Run an A/B test comparison between the current store listing and the proposed new icon design for my productivity app."
  • "Analyze the performance of the two active store listing variations to recommend which one should be promoted globally."
  • "Generate a report comparing the click-through rates of the existing description versus the optimized version containing new keywords."

Tips & gotchas

Ensure your A/B test has run for a statistically significant duration before relying on the data for major strategic decisions. This skill focuses on store listing elements; it does not analyze backend app performance or user reviews directly.