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AI EngineeringTeX

NNSight Remote Interpretability

by Orchestra-Research

NNSight Remote Interpretability is an AI Engineering skill for Claude Code, published by Orchestra-Research in AI-Research-SKILLs.

11.6K stars838 forkson Orchestra-Research/AI-Research-SKILLsAdded 2026/07/19+1% in starsRepository updated 2026/06/16
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Install in seconds
Install NNSight Remote Interpretability
Copy NNSight Remote Interpretability into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/main/04-mechanistic-interpretability/nnsight ~/.claude/skills/nnsight

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/Orchestra-Research/AI-Research-SKILLs.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
04-mechanistic-interpretability/nnsight/SKILL.md in Orchestra-Research/AI-Research-SKILLs
Installs to
~/.claude/skills/nnsight
Collection
One of 50 skills cataloged from this repository
Category
AI Engineering — 3670 skills

What NNSight Remote Interpretability does

Provides guidance for interpreting and manipulating neural network internals using nnsight. Ideal for running interpretability experiments on models too large for local GPUs via remote NDIF execution, or for working with any PyTorch architecture.

NNSight Remote Interpretability is cataloged under AI Engineering on DirSkills. NNSight Remote Interpretability comes from a repository tagged ai, ai-research, claude, claude-code and claude-skills.

Documentation

README

nnsight: Transparent Access to Neural Network Internals

nnsight (/ɛn.saɪt/) enables researchers to interpret and manipulate the internals of any PyTorch model, with the unique capability of running the same code locally on small models or remotely on massive models (70B+) via NDIF.

GitHub: ndif-team/nnsight (730+ stars) Paper: NNsight and NDIF: Democratizing Access to Foundation Model Internals (ICLR 2025)

Key Value Proposition

Write once, run anywhere: The same interpretability code works on GPT-2 locally or Llama-3.1-405B remotely. Just toggle remote=True.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about NNSight Remote Interpretability

  • What else does Orchestra-Research publish alongside NNSight Remote Interpretability?

    NNSight Remote Interpretability is one of 50 skills that DirSkills catalogs from Orchestra-Research/AI-Research-SKILLs, the repository it ships in. Its siblings there include AWQ Quantization, Autoresearch and Axolotl. Each one is a separate skill with its own page in this directory, installs the same way NNSight Remote Interpretability does, and is maintained by Orchestra-Research in that same repository. The rest of the collection is listed on the Orchestra-Research/AI-Research-SKILLs page.

  • How does NNSight Remote Interpretability compare to other AI Engineering skills?

    NNSight Remote Interpretability ranks #354 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of NNSight Remote Interpretability against them. Open each page to compare what they document and how they install.

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