Skill: guohongbin-git/mlops-collaboration-cn (version 1.0.0)

--- name: mlops-collaboration-cn version: 1.0.0 description: Prepare projects for sharing, collaboration, and community license: MIT --- # MLOps Collaboration 🤝 Make projects collaborative and community-ready. ## Features ### 1. README Template 📖 Professional documentation: ```bash cp references/README-template.md ../your-project/README.md # Edit with your project details ``` Includes: - Badges (PyPI, CI, License) - Quick start guide - Installation steps - Usage examples - Contributing guide ### 2. Required Files Checklist ✅ Community files: - `LICENSE` - MIT/Apache/GPL - `CODE_OF_CONDUCT.md` - Contributor Covenant - `CONTRIBUTING.md` - How to contribute - `CHANGELOG.md` - Version history ### 3. Dev Container 📦 VS Code Dev Container: ```json // .devcontainer/devcontainer.json { "image": "mcr.microsoft.com/devcontainers/python:3.11", "features": { "ghcr.io/astral-sh/uv:latest": {} } } ``` ## Quick Start ```bash # Copy README template cp references/README-template.md ./README.md # Create required files touch LICENSE CODE_OF_CONDUCT.md CONTRIBUTING.md CHANGELOG.md # Setup dev container mkdir -p .devcontainer # Add devcontainer.json # Protect main branch (GitHub UI) # Settings → Branches → Add rule ``` ## Release Checklist 1. Bump version in `pyproject.toml` 2. Update `CHANGELOG.md` 3. Git tag: `git tag v1.0.0` 4. Push: `git push --tags` 5. GitHub Release ## Semantic Versioning - `1.0.0` → `1.0.1` - Bug fix (PATCH) - `1.0.0` → `1.1.0` - New feature (MINOR) - `1.0.0` → `2.0.0` - Breaking change (MAJOR) ## Author Converted from [MLOps Coding Course](https://github.com/MLOps-Courses/mlops-coding-skills) ## Changelog ### v1.0.0 (2026-02-18) - Initial OpenClaw conversion - Added README template

path: package.json
content: {
  "name": "mlops-collaboration-cn",
  "version": "1.0.0",
  "description": "MLOps Collaboration - Prepare projects for sharing and community",
  "main": "SKILL.md",
  "keywords": [
    "mlops",
    "collaboration",
    "documentation",
    "readme",
    "contributing"
  ],
  "author": "money-maker-ai",
  "license": "MIT",
  "repository": {
    "type": "git",
    "url": "https://github.com/MLOps-Courses/mlops-coding-skills"
  }
}


path: references/README-template.md
content: # README template for MLOps projects

# [Project Name]

[![PyPI version](https://badge.fury.io/py/your-package.svg)](https://badge.fury.io/py/your-package)
[![Python](https://img.shields.io/pypi/pyversions/your-package.svg)](https://pypi.org/project/your-package/)
[![License](https://img.shields.io/github/license/your-username/your-repo.svg)](LICENSE)
[![CI](https://github.com/your-username/your-repo/workflows/CI/badge.svg)](https://github.com/your-username/your-repo/actions)

Brief description of what your project does.

## Features

- Feature 1
- Feature 2
- Feature 3

## Installation

```bash
pip install your-package
```

Or with uv:

```bash
uv add your-package
```

## Quick Start

```python
from your_package import Model

model = Model()
model.train(X_train, y_train)
predictions = model.predict(X_test)
```

## Usage

### Training

```bash
python -m your_package.application.train --config config.yaml
```

### Inference

```bash
python -m your_package.application.predict --input data.csv
```

## Configuration

Create `config.yaml`:

```yaml
model:
  n_estimators: 100
  max_depth: 10

training:
  batch_size: 32
  learning_rate: 0.001
```

## Development

### Setup

```bash
# Clone repo
git clone https://github.com/your-username/your-repo.git
cd your-repo

# Install dev dependencies
uv sync

# Run tests
uv run pytest

# Run linters
uv run ruff check src/
```

### Testing

```bash
uv run pytest tests/ -v --cov=src
```

## Project Structure

```
your-package/
├── src/your_package/
│   ├── io/          # Data I/O
│   ├── domain/      # Business logic
│   └── application/ # Training/inference
├── tests/
├── config.yaml
└── pyproject.toml
```

## Contributing

See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

## License

This project is licensed under the MIT License - see [LICENSE](LICENSE) for details.

## Acknowledgments

- Based on [MLOps Coding Course](https://github.com/MLOps-Courses/mlops-coding-skills)


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: clean | SkillSpector: clean (LOW)