Takes your experiment blueprint JSON and scaffolds out a complete Python research codebase with data loaders, model stubs for your proposed method and baselines, training loops with checkpointing, evaluation harnesses, and config files for ablations. Saves you the tedious hour of setting up boilerplate when you want to go from research plan to runnable code. The generated skeleton is opinionated about structure (separate directories for data, models, training, evaluation) but that's the point. You'll still need to fill in the actual model logic and dataset specifics, but you get a working entry point and all the plumbing connected. Good for moving fast on new experiments without reinventing project structure every time.
npx -y skills add openraiser/nanoresearch --skill nanoresearch-experiment --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
mindrally/skills