nnsight-remote-interpretability
An AI agent skill from Orchestra-Research/AI-Research-SKILLs, scored 72 out of 100 by code.
Code score by group
It loses the most points in Description (9), the group that checks whether the description says what the skill does and when to use it.
What the author says it does
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- Orchestra-Research/AI-Research-SKILLs
- Folder
- 04-mechanistic-interpretability/nnsight
- License
- MIT
- GitHub stars
- 14,480
- SKILL.md lines
- 437
- Other files
- 3
Add nnsight-remote-interpretability to your agent
npx skills add Orchestra-Research/AI-Research-SKILLs --skill nnsight-remote-interpretability
The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
Labelled for
More skills from Orchestra-Research/AI-Research-SKILLs
-
pytorch-fsdp2
Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU…
Verified82B -
systems-paper-writing
Comprehensive guide for writing systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides paragraph-level structural blueprints, writing patterns, venue-specific ch…
Verified82B -
evolving-ai-agents
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing…
77B -
brainstorming-research-ideas
Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking…
76B -
academic-plotting
Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architect…
74B -
miles-rl-training
Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignme…
73B -
presenting-conference-talks
Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral talks, spotlight pr…
73B -
evaluating-llms-harness
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, o…
72B
All skills in Orchestra-Research/AI-Research-SKILLs
Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.