surveying-prior-work

Compile established methods and prior effect sizes to ground analysis planning.

282|26|Updated May 28, 2026
One-click install
npx skills add https://github.com/K-Dense-AI/science-superpowers --skill surveying-prior-work
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: surveying-prior-work
Source: https://github.com/K-Dense-AI/science-superpowers/tree/main/skills/surveying-prior-work
Command: npx skills add https://github.com/K-Dense-AI/science-superpowers --skill surveying-prior-work

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Before designing an analysis, researchers must ground the question and chosen methods in prior knowledge to avoid reinventing established methods, missing confounds, or presenting novelty without evidence.

Core Features & Use Cases

  • Grounding: Compile established methods, known confounds, and prior effect sizes to inform analysis planning.
  • Relationship to prior work: Assess whether a result is a replication, extension, or novel finding, and document sources.
  • Cite sources: Record precise references to support the design and final report.

Quick Start

Ask the AI to identify relevant prior work and appropriate standard methods before designing the analysis.

Frequently Asked Questions about surveying-prior-work

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ground my research question with established methods before analysis?

A literature review for experimental design compiles established methods, known confounds, and prior effect sizes to transparently relate your research question to prior work and prevent missing critical design flaws.

What is the best way to estimate prior effect sizes for power calculations?

Estimating prior effect sizes for power calculations requires surveying prior work to extract proven findings, ensuring your experimental design is transparently grounded in established methods and accurate literature.

How do I determine if my result is a replication, extension, or novel finding?

Determining if a result is a replication, extension, or novel finding requires assessing its transparent relationship to prior work and documenting exact sources to evaluate the novelty of your contribution.

Can I use literature review to identify known confounds for experimental design?

Yes, a literature review identifies known confounds by compiling established methods and prior findings, ensuring your experimental design proactively accounts for confounds during analysis planning.

Why does framing a research question require thorough literature grounding?

Framing a research question requires thorough literature grounding to avoid reinventing established methods, missing confounds, or presenting novelty without prior effect sizes.