How does it handle spaced repetition?

It integrates with org-fc and org-drill, adding custom visual indicators based on retention intervals and color-coded data streams for memory management.

What is the Gwern-Emacs skill?

It is a specialized Claude Code skill that implements Gwern Branwen's empirical rationality and scaling principles directly within the Emacs ecosystem.

Can I use it for scientific research?

Yes, it includes specific org-capture templates and SQLite logging functions designed for n=1 self-experimentation, protocol tracking, and statistical analysis.

What is the 'Bitter Lesson' integration?

It automates model selection by choosing the most compute-heavy models for complex tasks and smaller models for simple ones, following the principle that general methods leveraging compute outperform specialized heuristics.

Gwern Emacs Rationality

Name: Gwern Emacs Rationality
Author: plurigrid

byplurigrid

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Productivity & Workflow

Integrates empirical rationality and scaling hypothesis principles into Emacs for advanced research and self-experimentation.

This skill synthesizes Gwern Branwen's philosophy of empirical rationality with modern Emacs workflows to create a high-leverage environment for research and self-improvement. It provides specialized tools for spaced repetition via org-fc, structured self-experimentation protocols using org-capture and SQLite, and automated scaling heuristics for AI model selection based on the 'Bitter Lesson.' By leveraging xenodium's Emacs philosophy, it transforms the editor into an augmented Tool AI assistant capable of tracking compute budgets, performing N-gram analysis, and managing deterministic color-coded data streams for better cognitive mapping.

Key Features

01Scaling-aware AI model selection based on task complexity

02Integrated Tool AI agents for augmented decision-making and meta-analysis

03Structured Self-Experimentation (n=1) templates with SQLite data logging

04Deterministic concept coloring via Gay.jl integration for visual organization

05Automated Spaced Repetition (SR) workflows with visual retention cues

068 GitHub stars

Use Cases

01Managing long-term knowledge retention through customized spaced repetition systems

02Optimizing LLM usage and compute costs using empirical scaling heuristics

03Conducting and analyzing personal scientific experiments with rigorous data tracking

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi gwern-emacs

For use in Claude.ai and ChatGPT

Download Skill