orchestra-research-ai-research-skills
๐ชMarketplaceOrchestra-Research/AI-Research-SKILLs
|Streamlines AI research workflows by providing curated Claude skills for data analysis, literature review, experiment design, and research paper generation.
Overview
AI Research Engineering Skills Library by Orchestra Research is the most comprehensive open-source collection of AI research engineering skills for AI coding agents. With 83 skills across 20 categories, it provides the engineering layer that enables coding agents to write and conduct AI research experiments, from dataset preparation and training pipelines to model deployment and agent building.
Key Features
- 83 Skills Across 20 Categories โ Covers model architecture, fine-tuning, post-training, distributed training, optimization, inference, RAG, multimodal, safety & alignment, MLOps, mechanistic interpretability, and more
- Research-to-Code Pipeline โ Bridges the gap between AI research hypotheses and executable experiment infrastructure
- Multi-Agent Compatible โ Works with Claude Code, Codex, and other AI agents via npm package or direct installation
- Structured Skill Format โ Each skill includes context, methodology, best practices, and agent-ready instructions for consistent quality
- Active Community โ Slack community and regular updates with new research categories
Who is this for?
AI researchers and ML engineers who spend more time debugging infrastructure than testing hypotheses. This library enables coding agents to handle the engineering work โ setting up training pipelines, configuring distributed training, deploying models โ so researchers can focus on the science.
Add this Marketplace
/plugin marketplace add orchestra-research/AI-research-SKILLsPlugins in this Marketplace
agents
data-processing
distributed-training
emerging-techniques
Emerging-techniques category of the AI Research Engineering Skills library โ 6 skills covering Mixture-of-Experts training, Model Merging (TIES/DARE/SLERP via mergekit), Long Context (RoPE/YaRN/ALiBi), Speculative Decoding, Knowledge Distillation, and Model Pruning.
evaluation
fine-tuning
inference-serving
infrastructure
mechanistic-interpretability
ml-paper-writing
AI research skill for writing publication-ready ML papers for top conferences (NeurIPS, ICML, ICLR, ACL, AAAI, COLM) with LaTeX templates and citation verification.
mlops
model-architecture
multimodal
A collection of 7 multimodal AI research skills covering CLIP, Whisper, LLaVA, BLIP-2, SAM, Stable Diffusion, and AudioCraft โ part of Orchestra Research's 83 AI research engineering skills for coding agents.
observability
optimization
post-training
prompt-engineering
Prompt-engineering category of the AI Research Engineering Skills library โ 4 skills covering DSPy (declarative prompt programming), Instructor (Pydantic-validated structured outputs), Guidance (regex/grammar-constrained generation), and Outlines (FSM-based structured text).
rag
safety-alignment
A collection of 4 AI safety and alignment research skills covering Constitutional AI, LlamaGuard safety classifier, NeMo programmable guardrails with Colang, and Meta's Prompt Guard injection detector โ part of Orchestra Research's AI research engineering skills.
tokenization
A tokenization skill from the AI Research Engineering Skills Library, which offers 83 skills across 20 categories covering model architecture, fine-tuning, inference, and other AI research areas.