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Experiment Design

Checked
product-on-purpose·v1.0.0·marketing·Apache-2.0

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->

Install on your platform

Showing OpenClaw.

  1. 1

    Run this in your terminal

    terminal
    $ 

What we know about this skill

Publisher

product-on-purpose

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 product-on-purpose/pm-skills at 1cef1a9eae.

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

Scanned
7 files, 676 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 facilitates the design of experiments to validate product hypotheses and inform decision-making. It helps structure experiment plans, including defining clear objectives, identifying key metrics (both primary and secondary), outlining participant segments, and detailing success criteria. The tool aims to ensure experiments are rigorously designed for reliable results and actionable insights.

When to use it

  • Prioritizing Features: Use this skill when deciding between multiple feature ideas by running A/B tests to measure user engagement or conversion rates.
  • Validating Pricing Models: Design experiments to test different pricing tiers and understand their impact on revenue and customer acquisition.
  • Optimizing Onboarding Flows: Create an experiment to compare two onboarding flows, measuring completion rates and time-to-value as key metrics.
  • Testing New UI/UX Designs: Run controlled tests to evaluate the usability and effectiveness of redesigned user interfaces.

Key capabilities

  • Objective definition
  • Metric identification (primary & secondary)
  • Participant segmentation
  • Success criteria outlining

Example prompts

  • "Design an experiment to test whether a new call-to-action button increases click-through rates on our landing page."
  • "I want to validate the hypothesis that offering free shipping will increase order volume. Create an experimental plan for this."
  • "Help me structure an A/B test comparing two different user onboarding flows, focusing on time-to-value as a primary metric."

Tips & gotchas

The quality of the experiment design heavily relies on clearly defined hypotheses and measurable objectives. Ensure your team has a solid understanding of experimental methodology before using this skill to avoid misleading results.