ml-paper-writing
๐ฏSkillfrom zechenzhangagi/ai-research-skills
|ml-paper-writing skill from zechenzhangagi/ai-research-skills
Part of
zechenzhangagi/ai-research-skills(83 items)
Installation
/plugin marketplace add zechenzhangAGI/AI-research-SKILLs/plugin install fine-tuning@ai-research-skills # Axolotl, LLaMA-Factory, PEFT, Unsloth/plugin install post-training@ai-research-skills # TRL, GRPO, OpenRLHF, SimPO/plugin install inference-serving@ai-research-skills # vLLM, TensorRT-LLM, llama.cpp, SGLang/plugin install distributed-training@ai-research-skills+ 1 more commands
Skill Details
Overview
# AI Research Engineering Skills Library
> The most comprehensive open-source library of AI research engineering skills for AI agents
[](https://opensource.org/licenses/MIT)
[](https://www.orchestra-research.com/perspectives/ai-research-skills)
[](https://www.orchestra-research.com/perspectives/LLM-with-Orchestra)
**77 Skills Powering AI Research in 2026**
| | | | |:---:|:---:|:---:| | Model Architecture (5) | Fine-Tuning (4) | Post-Training (4) | | Distributed Training (5) | Optimization (6) | Inference (4) | | Tokenization (2) | Data Processing (2) | Evaluation (3) | | Safety & Alignment (3) | 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) | |
---
Table of Contents
- [Our Mission](#our-mission)
- [Path Towards AI Research Agent](#path-towards-ai-research-agent)
- [Available AI Research Engineering Skills](#available-ai-research-engineering-skills)
- [Demo](#demo)
- [Skill Structure](#skill-structure)
- [Roadmap](#roadmap)
- [Repository Structure](#repository-structure)
- [Use Cases](#use-cases)
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.
System diagram of an AI research agent
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 hypothesesโslowing 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 experimentsโfrom 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 - 77 skills spanning model architecture, tokenization, fine-tuning, mechanistic interpretability, data processing, post-training, distributed training, optimization, evaluation, inference, infrastructure, agents, RAG, multimodal, prompt engineering, MLOps, observability, emerging techniques, and ML paper writing
- 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.
๐ฆ Install from Claude Code Marketplace
Install skill categories directly using the Claude Code CLI:
```bash
# Add the marketplace
/plugin marketplace add zechenzhangAGI/AI-research-SKILLs
# Install by category (20 categories available)
/plugin install fine-tuning@ai-research-skills # Axolotl, LLaMA-Factory, PEFT, Unsloth
/plugin install post-training@ai-research-skills # TRL, GRPO, OpenRLHF, SimPO
/plugin install inference-serving@ai-research-skills # vLLM, TensorRT-LLM, llama.cpp, SGLang
/plugin install distributed-training@ai-research-skills
/plugin install optimization@ai-research-skills
```
All 20 Categories:
| Category | Install Command | S
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