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experiment-design

Skill114 starsChanged 10 months agoMITView on GitHub

Design robust experiments to test product hypotheses. Define metrics, sample size, and success criteria.

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The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 22 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

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  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When you have a hypothesis and need to design an experiment to validate it.

    line 12
  2. Distinctive:

    When to check results?

    line 41
  3. Distinctive:

    Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

    line 62

“Common” is measured: kept by at least 6 in 10 of the 22 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

Experiment Design

Design robust experiments to test product hypotheses.

When to Use

When you have a hypothesis and need to design an experiment to validate it.

The Process

1. Factor Breakdown

Analyze your goal and system:

  • What factors could influence the outcome?
  • Which are controllable vs. environmental?
  • What are the key variables?

2. Experiment Structure

For each factor, define:

  • Hypothesis: What you expect to happen
  • Independent variable: What you're changing
  • Dependent variable: What you're measuring
  • Control group: Baseline comparison
  • Experimental group: Who gets the change
  • Measurement method: How you'll collect data
  • Confounding variables: What else could affect results

3. Sample Design

  • Who participates?
  • How many needed for statistical significance?
  • How will you recruit/select?

4. Timeline

  • How long to run?
  • When to check results?
  • What's the minimum detectable effect?

5. Stop/Scale Rules

  • What results mean "stop"?
  • What results mean "scale"?
  • What's inconclusive?

Output Format

For each experiment:

  • Hypothesis statement
  • Variables (independent, dependent)
  • Groups (control, experimental)
  • Sample size and selection
  • Measurement approach
  • Success criteria
  • Stop/scale rules

When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

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