How does this help with developer and designer workflows?

It helps teams build interfaces that respect human cognitive limits, reducing user frustration and improving product adoption through science-based design.

Is the information based on current psychological research?

Yes, the skill includes foundational studies as well as modern caveats, such as updated research on working memory limits (Cowan, 2001) vs. Miller's Law.

Does this skill include specific researchers and citations?

Yes, it includes references to work from Nobel laureates like Daniel Kahneman and experts like Mihaly Csikszentmihalyi, including years and key publications.

What is the Psychology Foundations skill?

It is a specialized capability for Claude that provides research-backed psychological principles to explain why certain UX patterns work and how to apply them effectively.

Can I use this for design critiques?

Absolutely. Use this skill to evaluate whether a proposed interface aligns with principles like the Peak-End Rule, the Zeigarnik Effect, or Cognitive Load Theory.

Psychology Foundations for UX

Name: Psychology Foundations for UX
Author: bfmcneill

bybfmcneill

Design Tools

Explains the research-backed cognitive and behavioral science principles behind effective user experience design patterns.

About

This skill provides Claude with a deep foundation in the 'why' behind UX design, drawing from neuroscience, cognitive psychology, and behavioral economics. It equips the model with research-backed principles—such as the Peak-End Rule, Cognitive Load Theory, and Loss Aversion—to help designers and developers create more intuitive, satisfying, and scientifically sound user interfaces. By moving beyond surface-level heuristics, it ensures that digital experiences are grounded in proven human behavior and mental processing limits.

Key Features

0 GitHub stars
Access to peer-reviewed research summaries from pioneers like Kahneman, Tversky, and Sweller
Strategic insights on behavioral economics principles like Loss Aversion and Choice Overload
Detailed UX implications for cognitive biases and memory limitations
Evidence-based guidance on managing user cognitive load and anticipation
Quick reference for established 'Laws of UX' with academic evidence-level validation

Use Cases

Justifying design decisions to stakeholders using academic research and psychological data
Structuring complex information to align with human working memory constraints and the Serial Position Effect
Optimizing user flows to reduce friction and improve retention based on behavioral science

About

Key Features

0 GitHub stars
Access to peer-reviewed research summaries from pioneers like Kahneman, Tversky, and Sweller
Strategic insights on behavioral economics principles like Loss Aversion and Choice Overload
Detailed UX implications for cognitive biases and memory limitations
Evidence-based guidance on managing user cognitive load and anticipation
Quick reference for established 'Laws of UX' with academic evidence-level validation

Use Cases

Justifying design decisions to stakeholders using academic research and psychological data
Structuring complex information to align with human working memory constraints and the Serial Position Effect
Optimizing user flows to reduce friction and improve retention based on behavioral science