A comprehensive skill package for AI research, ML engineering, and research orchestration
Around 98 skills for AI research and ML engineering, covering training, fine-tuning, evaluation, distributed training, inference optimization, and autoresearch orchestration. Long-form references compiled from official documentation and real GitHub issues teach agents practical pitfalls in ML libraries.
Researchers and engineers who train or fine-tune models or run ML experiments.
The README lists varying skill counts (98/87/83), raising consistency concerns; the apparent single contributor also raises maintenance concerns.
npx skills add Orchestra-Research/AI-Research-SKILLs