feynman-perspective

Name: feynman-perspective
Availability: InStock
Author: godsplan135

Apply Feynman-inspired mental models to analyze problems and critique reasoning.

Updated Apr 9, 2026

Search Tags:#communication #explanation #feynman #thinking-framework #scientific-integrity #cargo-cult-science #doubt

Ready to run

npx skills add https://github.com/godsplan135/123 --skill feynman-perspective-godsplan135

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: feynman-perspective
Source: https://github.com/godsplan135/123/tree/main/examples/feynman-perspective
Command: npx skills add https://github.com/godsplan135/123 --skill feynman-perspective-godsplan135

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured, Feynman-inspired thinking framework to help users analyze problems, expose gaps in reasoning, and generate actionable feedback.

Core Features & Use Cases

5 core mind models (e.g., naming ≠ understanding; anti-self-deception; embracing uncertainty; concrete visualization; curiosity-driven deep thinking) and 8 decision heuristics tailored to rigorous thinking and clear communication.
Use cases across education, product design, research, and everyday decision-making by translating complex concepts into simple, testable explanations.
Feedback and critique workflows that emphasize explicit evidence, limitations, and conservative conclusions.

Quick Start

Describe a concept using Feynman’s concrete, example-driven explanations and test understanding by explaining it in plain language.

Frequently Asked Questions about feynman-perspective

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

FAQPage Schema

How do I critique reasoning and expose gaps using a Feynman thinking framework?▼

To critique reasoning using a Feynman thinking framework, apply 5 core mental models and 8 decision heuristics that translate concrete examples into general principles, enforcing explicit evidence and flagging self-deception to generate actionable feedback.

What is the best way to explain complex concepts in plain language for product design?▼

The best way to explain complex concepts in plain language is through curiosity-driven, concrete visualization that distinguishes naming from understanding, ensuring explanations are simple and testable across education, research, and product design contexts.

How do I apply anti-self-deception heuristics to evaluate scientific integrity?▼

To apply anti-self-deception heuristics and evaluate scientific integrity, embrace uncertainty and demand explicit evidence, actively flagging areas where cargo-cult science or cognitive bias could distort conclusions to maintain conservative, rigorous outcomes.

Does this Feynman-based thinking framework work for everyday decision-making and research?▼

Yes, this Feynman-based thinking framework works for everyday decision-making and research by translating complex problems into testable explanations, providing structured workflows that emphasize honesty about limits and actionable feedback.

When should I not use a Feynman explanation approach for analyzing problems?▼

You should not use a Feynman explanation approach when your analysis requires hiding limitations or lacks explicit evidence, because this framework specifically enforces honesty about limits, embraces uncertainty, and actively flags self-deception in conclusions.