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Ab Test Designer

Checked
pmprompt·vlatest·testing·MIT

Designs statistically sound A/B tests, specifying metrics, sample sizes, and hypotheses for data-driven optimization.

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 pmprompt/claude-plugin-product-management --skill ab-test-designer -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

pmprompt

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.

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  • No pipe-to-shell installers: passed

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

  • Pinned to a commit: passed

    Scanned pmprompt/claude-plugin-product-management at 3114dbe33f.

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

Commit
3114dbe33f
Manifest
skills/ab-test-designer/SKILL.md
Scanned
1 file, 75 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

The ab-test-designer skill enables AI agents to generate comprehensive A/B test plans, including hypotheses, metrics, and statistical parameters. It helps product teams validate features by structuring experiments with clear success criteria and sample size calculations.

When to use it

  • You need to design an experiment to compare two versions of a feature before development begins.
  • Your team requires a structured hypothesis statement linking specific changes to expected business outcomes.
  • You must define statistical significance levels, confidence intervals, or required sample sizes for your test.
  • You want to identify key performance indicators (KPIs) that will determine the winner of an A/B test.

Key capabilities

  • Generates structured A/B test hypotheses based on user behavior goals.
  • Defines primary and secondary metrics for measuring experiment success.
  • Calculates necessary sample sizes and duration estimates for valid statistical testing.
  • Outlines null and alternative hypotheses to frame experimental logic clearly.

Example prompts

  • "Create an A/B test plan for a new checkout button color, including the hypothesis, metrics, and required sample size."
  • "Design an experiment to test the impact of adding a live chat widget on user retention rates."
  • "Generate a structured A/B test proposal comparing two pricing page layouts with defined success criteria."

Tips & gotchas

Ensure you have access to historical conversion data or traffic estimates, as the skill relies on these inputs to calculate accurate sample sizes. Always validate generated statistical parameters with your data science team before launching live experiments.