内容摘录
AI Research Engineering Skills Library
**The most comprehensive open-source library of AI research engineering skills for AI agents**
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**85 Skills Powering AI Research in 2026**
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<summary><b>View All 21 Categories</b></summary>
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|:---:|:---:|:---:|
| **Model Architecture** (5) | **Fine-Tuning** (4) | **Post-Training** (8) |
| **Distributed Training** (6) | **Optimization** (6) | **Inference** (4) |
| **Tokenization** (2) | **Data Processing** (2) | **Evaluation** (3) |
| **Safety & Alignment** (4) | **Agents** (4) | **RAG** (5) |
| **Multimodal** (7) | **Prompt Engineering** (4) | **MLOps** (3) |
| **Observability** (2) | **Infrastructure** (3) | **Mech Interp** (4) |
| **Emerging Techniques** (6) | **ML Paper Writing** (1) | **Ideation** (2) |
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Table of Contents
Our Mission
Path Towards AI Research Agent
Available AI Research Engineering Skills
Demos
Skill Structure
Roadmap
Repository Structure
Use Cases
Contributing
Community
Our Mission
We provide the layer of **Engineering Ability** that **enable your coding agent to write and conduct AI research experiments**, including preparing datasets, executing training pipelines, deploying models, and building your AI agents.
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<img src="docs/skills.png" alt="AI Research Agent System" width="50%">
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<em>System diagram of an AI research agent</em>
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Path Towards AI Research Agent
Modern AI research requires mastering dozens of specialized tools and frameworks.
AI Researchers spend more time debugging infrastructure than testing hypotheses—slowing the pace of scientific discovery.
We provide a comprehensive library of expert-level research engineering skills that enable AI agents to autonomously implement and execute different stages of AI research experiments—from data preparation and model training to evaluation and deployment.
Specialized Expertise - Each skill provides deep, production-ready knowledge of a specific framework (Megatron-LM, vLLM, TRL, etc.)
End-to-End Coverage - 85 skills spanning the full AI research lifecycle, from model architecture to deployment
Research-Grade Quality - Documentation sourced from official repos, real GitHub issues, and battle-tested production workflows
Available AI Research Engineering Skills
**Quality over quantity**: Each skill provides comprehensive, expert-level guidance with real code examples, troubleshooting guides, and production-ready workflows.
📦 Quick Install (Recommended)
Install skills to **any coding agent** (Claude Code, OpenCode, Cursor, Codex, Gemini CLI, Qwen Code) with one command:
This launches an interactive installer that:
**Auto-detects** your installed coding agents
**Installs** skills to ~/.orchestra/skills/ with symlinks to each agent
**Offers** everything, quickstart bundle, by category, or individual skills
**Updates** installed skills with latest versions
**Uninstalls** all or selected skills
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<summary><b>CLI Commands</b></summary>
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<summary><b>Claude Code Marketplace (Alternative)</b></summary>
Install skill categories directly using the **Claude Code CLI**:
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All 21 Categories (85 Skills)
| Category | Skills | Included |
|----------|--------|----------|
| Model Architecture | 5 | LitGPT, Mamba, NanoGPT, RWKV, TorchTitan |
| Tokenization | 2 | HuggingFace Tokenizers, SentencePiece |
| Fine-Tuning | 4 | Axolotl, LLaMA-Factory, PEFT, Unsloth |
| Mech Interp | 4 | TransformerLens, SAELens, pyvene, nnsight |
| Data Processing | 2 | NeMo Curator, Ray Data |
| Post-Training | 8 | TRL, GRPO, OpenRLHF, SimPO, verl, slime, miles, torchforge |
| Safety | 4 | Constitutional AI, LlamaGuard, NeMo Guardrails, Prompt Guard |
| Distributed | 6 | DeepSpeed, FSDP, Accelerate, Megatron-Core, Lightning, Ray Train |
| Infrastructure | 3 | Modal, Lambda Labs, SkyPilot |
| Optimization | 6 | Flash Attention, bitsandbytes, GPTQ, AWQ, HQQ, GGUF |
| Evaluation | 3 | lm-eval-harness, BigCode, NeMo Evaluator |
| Inference | 4 | vLLM, TensorRT-LLM, llama.cpp, SGLang |
| MLOps | 3 | W&B, MLflow, TensorBoard |
| Agents | 4 | LangChain, LlamaIndex, CrewAI, AutoGPT |
| RAG | 5 | Chroma, FAISS, Pinecone, Qdrant, Sentence Transformers |
| Prompt Eng | 4 | DSPy, Instructor, Guidance, Outlines |
| Observability | 2 | LangSmith, Phoenix |
| Multimodal | 7 | CLIP, Whisper, LLaVA, BLIP-2, SAM, Stable Diffusion, AudioCraft |
| Emerging | 6 | MoE, Model Merging, Long Context, Speculative Decoding, Distillation, Pruning |
| ML Paper Writing | 1 | ML Paper Writing (LaTeX templates, citation verification) |
| Ideation | 2 | Research Brainstorming, Creative Thinking |
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<summary><b>View All 85 Skills in Details</b></summary>
🏗️ Model Architecture (5 skills)
**LitGPT** - Lightning AI's 20+ clean LLM implementations with production training recipes…