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Skills/Testing & QA
k-dense-ai avatar

Preregistering Analysis

k-dense-ai/science-superpowers

This enforces the discipline of locking your hypotheses, analysis plan, and decision rules before you touch outcome data.

GitHub stars
202
last updated
Jun 1, 2026
View on GitHubSave

Install

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

Installs into .claude/skills of the current project.

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What it does

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.

Files

Select a file.

Details

Repository
github.com/k-dense-ai/science-superpowers
Categories
Testing & QA, Data Science & ML, Productivity & Planning
First seen
Jun 11, 2026

More from k-dense-ai/science-superpowers

All 15
  • Receiving Critical Review
  • Reporting And Archiving Findings
  • Requesting Red Team Review
  • Setting Up Reproducible Analysis
  • Subagent Driven Analysis
  • Surveying Prior Work
  • Using Science Superpowers
  • Verifying Results Before Claiming
  • Writing Science Skills
  • Designing The Analysis
  • Dispatching Parallel Investigations
  • Executing Analysis
  • Framing Research Questions
  • Investigating Anomalous Results

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