How does this differ from standard code generation?

Unlike standard generation, this skill focuses on the 'why' behind the code, using checkpoint questions and a methodical scaffolding process to ensure the user understands the implementation.

How does it help with model debugging?

The skill includes a 'Debugging Gauntlet' which provides systematic tests for overfitting single batches, checking gradient flow, and verifying initialization against the paper's specs.

Can I use this for any type of research paper?

Yes, it includes specific strategies for Transformers, Reinforcement Learning, Generative Models (like VAEs or GANs), and Computer Vision architectures.

What is the Implement Paper From Scratch skill?

It is a specialized capability for Claude Code that provides a structured, pedagogical framework for building complex algorithms directly from research papers.

Does this skill rely on high-level AI libraries?

No, it encourages the use of minimal dependencies like NumPy and fundamental PyTorch to ensure the developer understands every step of the implementation.

Implement Paper From Scratch

Name: Implement Paper From Scratch
Author: GhostScientist

byGhostScientist

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데이터 과학 및 ML

Guides developers through the methodical, step-by-step implementation of research papers to ensure deep understanding and reproducible results.

This skill transforms Claude into a research engineering mentor that facilitates the manual reproduction of scientific papers from first principles. Instead of providing simple code generation, it follows a rigorous four-phase process—pre-implementation analysis, scaffolded implementation, debugging, and verification—to build models from the ground up using fundamental libraries like NumPy and PyTorch. By emphasizing understanding through interactive checkpoint questions and a 'debugging gauntlet,' it helps users move beyond high-level wrappers to master the underlying mechanics of cutting-edge algorithms in fields like Computer Vision, NLP, and Reinforcement Learning.

주요 기능

01Comprehensive debugging gauntlet for troubleshooting gradients, shapes, and initialization

02Domain-specific guidance for Transformers, RL, Generative Models, and CV

03Phase-based workflow covering analysis, scaffolding, debugging, and evaluation

04Interactive checkpoint questions to verify theoretical and practical comprehension

051 GitHub stars

06Minimalist implementation approach using NumPy and PyTorch fundamentals

사용 사례

01Deepening understanding of complex architectures through manual implementation

02Reproducing state-of-the-art results from a research paper for a custom project

03Developing and debugging custom loss functions or non-standard model layers

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ghostscientist/skills implement-paper-from-scratch

For use in Claude.ai and ChatGPT

Download Skill