reproai
NewSummary
The reproai skill helps developers reproduce and debug AI-related issues by automating the setup of reproducible environments, capturing model outputs, and comparing results across different configurations.
- It streamlines the process of isolating bugs in machine learning pipelines and ensures consistent experimentation.
Install & Usage
mkdir -p .claude/skillsAdd the configuration to .claude/skills/reproai.md
/reproaiUse Cases
Usage Examples
/reproai reproduce training run --config configs/experiment.yaml --seed 42
Set up a minimal reproducible example for this error: 'RuntimeError: CUDA out of memory'
/reproai compare outputs --baseline v1.0 --candidate v2.0 --metric accuracy
Security Audits
Frequently Asked Questions
What is reproai?
The reproai skill helps developers reproduce and debug AI-related issues by automating the setup of reproducible environments, capturing model outputs, and comparing results across different configurations. It streamlines the process of isolating bugs in machine learning pipelines and ensures consistent experimentation.
How to install reproai?
To install reproai: create the skills directory (mkdir -p .claude/skills), then add the config to .claude/skills/reproai.md. Finally, /reproai in Claude Code.
What is reproai best for?
reproai is a other categorized under General. Created by leoyyang.
What can I use reproai for?
reproai is useful for: Reproduce a training run with specific hyperparameters to verify a reported bug.; Compare model outputs across different versions of a library to identify regressions.; Set up a minimal reproducible example for a data preprocessing issue.; Automate the collection of logs and metrics for a failing inference pipeline.; Replicate a deployment environment locally to test a production issue.; Generate a reproducible script for a research experiment to share with collaborators..