plugins/mlintern/.codex-plugin/plugin.json

{
  "name": "ml-intern",
  "version": "0.1.0",
  "description": "Hugging Face ML Intern for Codex — research ML papers, inspect models and datasets, run training and evaluation jobs, and ship ML artifacts.",
  "author": {
    "name": "Hugging Face",
    "email": "agents@huggingface.co",
    "url": "https://github.com/huggingface"
  },
  "homepage": "https://huggingface.co/docs/hub/agents-skills",
  "repository": "https://github.com/razvan/ml-intern-codex-plugin",
  "license": "Apache-2.0",
  "keywords": ["huggingface", "ml", "machine-learning", "training", "fine-tuning", "evaluation", "datasets", "models"],
  "skills": "./skills/",
  "interface": {
    "displayName": "ML Intern",
    "shortDescription": "Hugging Face ML engineering agent for Codex",
    "longDescription": "ML Intern is an autonomous ML engineering agent for the Hugging Face ecosystem. It researches papers, validates datasets and models, writes training/evaluation code, runs HF Jobs, and ships ML artifacts with zero avoidable errors.",
    "developerName": "Hugging Face",
    "category": "Coding",
    "capabilities": ["Interactive", "Read", "Write"],
    "websiteURL": "https://huggingface.co",
    "defaultPrompt": [
      "Fine-tune a language model on a custom dataset using Hugging Face Jobs",
      "Find the best open-source embedding model and benchmark it",
      "Research papers on preference optimization and implement DPO training"
    ],
    "brandColor": "#FF6B00"
  }
}