Preregistering Analysis

This enforces the discipline of locking your hypotheses, analysis plan, and decision rules before you touch outcome data. The idea is simple: if you decided what test to run after seeing the results, you can't tell whether the data shaped your conclusions. It gives you a template for writing predictions, walks you through verifying they're actually falsifiable, and commits everything to git with a timestamp before you execute. The "looked at it? it's exploratory now" rule has no exceptions, which will feel rigid until you've watched a few analyses that seemed obviously confirmatory turn out to hinge entirely on choices made after peeking. Think of it as test-driven development for science: write the test before the code so you know the test tests something real.

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last updated: Jun 1, 2026

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Install

$ npx -y skills add k-dense-ai/science-superpowers --skill preregistering-analysis --agent claude-code

Installs into .claude/skills of the current project.

Files

Pre-Registering the Analysis

Overview

Write down the hypotheses, the exact analysis, the directional predictions, and the decision rules — and freeze them — before you look at the outcomes. Then run exactly that.

Core principle: If you decided the analysis after seeing the data, you cannot tell whether the data shaped the answer. A prediction is only evidence if it was made before the result.

Violating the letter of this rule is violating the spirit of this rule.

This is the pre-registration discipline — the science analog of test-driven development. In TDD you write the test before the code so you know the test tests something. Here you write the prediction before the result so you know the result confirms something.

The Iron Law

NO CONFIRMATORY CLAIM WITHOUT A PRE-REGISTERED PREDICTION FIRST

Looked at the outcomes before locking the analysis? That analysis is now exploratory. You cannot relabel it confirmatory. To make a confirmatory claim, pre-register and test on data you have not yet used.

SKILL.md on GitHub