surveying-prior-work
Use after framing a question and before designing an analysis, or when choosing a method, judging whether a result is novel, or needing a prior effect size for a power calculation
npx skills add K-Dense-AI/science-superpowers --skill surveying-prior-work --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Surveying Prior Work ## Overview Before designing an analysis, ground the question and your chosen methods in what is already known. Most questions have established methods, known confounds, and prior effect sizes. Reinventing a method badly — or rediscovering a known artifact and reporting it as a finding — wastes effort and erodes credibility. **Core principle:** Find out what is already known before you generate new claims. This is the science analog of reading the existing codebase before writing new code. It is a flexible skill — adapt depth to the stakes of the investigation. ## When to Use - After `framing-research-questions`, before `designing-the-analysis` - When selecting a statistical method or model and unsure what is standard - When a result looks novel — check whether it is a known effect or artifact first - When you need a plausible prior effect size to power the study - When you suspect confounds but don't know which are established in the field ## What to Ground Survey four things: 1. **Established methods** — what is the standard, accepted way to analyze this kind of question? What are its assumptions and failure modes? 2. **Known confounds and artifacts** — wha
- Overview
- When to Use
- What to Ground
- The Process
- Red Flags
- Handoff
What does the surveying-prior-work skill do?
Use after framing a question and before designing an analysis, or when choosing a method, judging whether a result is novel, or needing a prior effect size for a power calculation
How do I install it?
Run `npx skills add K-Dense-AI/science-superpowers --skill surveying-prior-work --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/science-superpowers, a repository with 287 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.