# MLOps setup (/ml--mlops-pipeline)

/ml--mlops-pipeline is a Claude Code skill in the AI & Agents section. Gives an ML project reproducible training, experiment tracking, a model registry and CI, sized to the team instead of a full platform.

- Web version: https://skills.sgomez.dev/en/s/ml--mlops-pipeline
- Section: [AI & Agents](https://skills.sgomez.dev/en/ai.md)
- Author: Santiago Gómez de la Torre
- License: MIT
- Source: https://github.com/sgomez-dev/claude-skills/blob/main/skills/ml/mlops-pipeline.md
- Updated 10 Jul 2026

## How to ask for it

- `/ml--mlops-pipeline set up a model registry for my team`
- `/ml--mlops-pipeline add experiment tracking to my project`
- `/ml--mlops-pipeline configure CI to validate models before deploy`

## Install

macOS · Linux:

```
curl -fsSL https://raw.githubusercontent.com/sgomez-dev/claude-skills/main/install.sh | bash
```

Windows:

```
irm https://raw.githubusercontent.com/sgomez-dev/claude-skills/main/install.ps1 | iex
```

Claude Code plugin:

```
/plugin marketplace add sgomez-dev/claude-skills
/plugin install ml-skills@claude-skills-collection
```

## Permissions

- Reads: `**/*.py`, `**/*.ipynb`, `**/*.yaml`, `**/*.toml`, `**/*.cfg`, `requirements.txt`, `Dockerfile`, `.github/**`, `Makefile`
- Writes: `**/*.py`, `**/*.yaml`, `**/*.toml`, `.github/**`, `Makefile`, `**/*.md`, `Dockerfile`
- Runs: `python`, `pip`
- Network: No
- Destructive: No

## Author's description

Set up MLOps — experiment tracking, model registry, CI for models, reproducibility

- [How we review this](https://skills.sgomez.dev/en/methodology.md)