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CLAUDE.md

AI-Research-SKILLs CLAUDE.md

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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

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CLAUDE.md

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The instructions Claude Code reads when this claude.md runs.

# CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

## Project Overview

**AI Research Skills Library** - A comprehensive open-source library of 98 AI research skills enabling AI agents to autonomously conduct AI research — from idea to paper. Each skill provides expert-level guidance (200-500 lines) with real code examples, troubleshooting guides, and production-ready workflows.

**Mission**: Enable AI agents to autonomously conduct AI research from hypothesis to experimental verification, covering the full lifecycle: literature survey, ideation, dataset preparation, training pipelines, model deployment, evaluation, and paper writing.

## Repository Architecture

### Directory Structure (98 Skills Across 23 Categories)

Skills are organized into numbered categories representing the AI research lifecycle:

- `0-autoresearch-skill/` - **Autonomous research orchestration** (1 skill: Autoresearch — central layer that manages the full lifecycle and routes to all other skills)
- `01-model-architecture/` - Model architectures (5 skills: TorchTitan, LitGPT, Mamba, RWKV, NanoGPT)
- `02-tokenization/` - Tokenizers (2 skills: HuggingFace Tokenizers, SentencePiece)
- `03-fine-tuning/` - Fine-tuning frameworks (4 skills: Axolotl, LLaMA-Factory, Unsloth, PEFT)
- `04-mechanistic-interpretability/` - Interpretability tools (4 sk
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