
Using Science Superpowers
This is the bootstrap that makes the whole skill system work. It loads first in any conversation and enforces a simple rule: if there's even a 1% chance a skill applies to what you're doing, invoke it before responding. No clarifying questions first, no quick peeks at the data, no rationalizing that this one thing is too simple. It includes a flowchart showing when to invoke skills and a table of red flag thoughts that mean you're about to skip the discipline. The instruction priority is clear: your explicit instructions override everything, then skills, then default behavior. Worth reading the red flags table, it's basically a field guide to how analyses go wrong.
- GitHub stars
- 202
- last updated
- Jun 1, 2026
Install
$ npx -y skills add k-dense-ai/science-superpowers --skill using-science-superpowers --agent claude-codeInstalls into .claude/skills of the current project.
Files
IF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.
This is not negotiable. This is not optional. You cannot rationalize your way out of this.
Instruction Priority
Science Superpowers skills override default system prompt behavior, but your human partner's instructions always take precedence:
- Your human partner's explicit instructions (CLAUDE.md, GEMINI.md, AGENTS.md, direct requests) — highest priority
- Science Superpowers skills — override default system behavior where they conflict
- Default system prompt — lowest priority
If CLAUDE.md, GEMINI.md, or AGENTS.md says "skip pre-registration" and a skill says "always pre-register," follow your human partner's instructions. They are in control.
How to Access Skills
Sponsors
Details
- Repository
- github.com/k-dense-ai/science-superpowers
- First seen
- Jun 11, 2026
More from k-dense-ai/science-superpowers
All 15- Verifying Results Before Claiming
- 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