# mlops-workflows

Integrates MLflow practices into your AI coding assistant. The skill guides experiment tracking, model registry management, and parameter logging.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 444 installs · ★ 62
- Author: manutej
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/manutej/luxor-claude-marketplace/tree/HEAD/plugins/luxor-data-engineering/skills/mlops-workflows/SKILL.md
- Updated: 2026-06-13
- HTML: https://affpapa.org/en/nevibecode/skills/mlops-workflows

## What it does

The skill provides step-by-step guidance for organizing machine learning lifecycles with MLflow. It directs the assistant to log run parameters and package pipelines with `MLproject` configs. During training, the agent infers model signatures and records metadata systematically.

Hyperparameter tuning uses nested runs. This structure separates parent search jobs from child trials when running `GridSearchCV`. Models are committed to the MLflow Registry, where deployment aliases like `production` mark release candidates.

Logging fails if an MLflow tracking server is not reachable at `http://localhost:5000` or configured locally. You need Python 3.8 or newer alongside MLflow 2.0+ and `scikit-learn` installed in your environment.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add manutej/luxor-claude-marketplace --skill mlops-workflows -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/mlops-workflows/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/mlops-workflows/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add manutej/luxor-claude-marketplace --skill mlops-workflows -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/mlops-workflows/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add manutej/luxor-claude-marketplace --skill mlops-workflows -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/mlops-workflows/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install manutej/luxor-claude-marketplace mlops-workflows
```

2. **Manually: put the files in place**
- File: `.github/skills/mlops-workflows/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add manutej/luxor-claude-marketplace --skill mlops-workflows -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/manutej/luxor-claude-marketplace --path plugins/luxor-data-engineering/skills/mlops-workflows
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/mlops-workflows/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add manutej/luxor-claude-marketplace --skill mlops-workflows -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/manutej/luxor-claude-marketplace/tree/HEAD/plugins/luxor-data-engineering/skills/mlops-workflows/SKILL.md

## When to use it
- track training metrics and model parameters in MLflow
- configure nested runs for hyperparameter search
- assign production aliases in the MLflow model registry
- enable automatic logging for scikit-learn models

## Example prompts
- Configure MLflow tracking for my random forest regressor training run.
- Set up nested MLflow runs to capture each step of hyperparameter tuning.
- Register the trained model in MLflow and tag it with the production alias.

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From the same set: [manutej/luxor-claude-marketplace](https://affpapa.org/en/nevibecode/by/manutej/luxor-claude-marketplace.md) — 65 cards

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NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md