Verifying Results Before Claiming
This is the pre-commit hook for your brain before you report any finding. It enforces one iron law: run the analysis fresh, read the actual output, then make the claim. No "it was significant earlier," no "the script ran fine," no trusting what a subagent reported. You identify what command proves your claim, execute it from raw data with a fixed seed, read the estimate and interval, check assumptions, and only then state the result with evidence attached. The source is uncompromising about this, calling out common rationalizations like conflating training accuracy with model quality or reporting p-values without effect sizes. If you work with data and have ever caught yourself saying "it should work" before actually checking, this skill is the corrective.
- GitHub stars
- 202
- last updated
- Jun 1, 2026
Install
$ npx -y skills add k-dense-ai/science-superpowers --skill verifying-results-before-claiming --agent claude-codeInstalls into .claude/skills of the current project.
Files
Verifying Results Before Claiming
Overview
Claiming a finding without fresh verification is dishonesty, not efficiency.
Core principle: Evidence before claims, always.
Violating the letter of this rule is violating the spirit of this rule.
The Iron Law
NO CLAIMS WITHOUT FRESH REPRODUCED EVIDENCE
If you haven't run the analysis in this state and read its actual output, you cannot claim its result. "It was significant earlier" is not evidence now.
The Gate Function
BEFORE claiming any result or expressing satisfaction:
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- Repository
- github.com/k-dense-ai/science-superpowers
- Category
- Git & Pull Requests
- First seen
- Jun 11, 2026
More from k-dense-ai/science-superpowers
All 15- Writing Science Skills
- Designing The Analysis
- Dispatching Parallel Investigations
- Executing Analysis
- Framing Research Questions
- Investigating Anomalous Results
- Preregistering Analysis
- Receiving Critical Review
- Reporting And Archiving Findings
- Requesting Red Team Review
- Setting Up Reproducible Analysis
- Subagent Driven Analysis
- Surveying Prior Work
- Using Science Superpowers
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