# Contributing Guide

Thank you for your interest in contributing to `sktime-mcp`. This project aims to provide a robust MCP layer for the `sktime` ecosystem.

## Development Setup

1. **Fork and Clone**:
   ```bash
   git clone https://github.com/sktime/sktime-mcp.git
   cd sktime-mcp
   ```

2. **Environment**:
   We recommend using a virtual environment.
   ```bash
   python3 -m venv .venv
   source .venv/bin/activate
   ```

3. **Install Dependencies**:
   Install the package in editable mode with all development and optional dependencies.
   ```bash
   pip install -e ".[dev,all]"
   ```

4. **Pre-commit Hooks**:
   Enable pre-commit hooks to ensure code quality and formatting.
   ```bash
   pre-commit install
   ```

## Code Quality Standards

We use `ruff` for linting and formatting.

- **Check Linting**: `ruff check .`
- **Format Code**: `ruff format .`

Ensure all new code is properly type-hinted and includes docstrings following the NumPy format.

## Testing

The project uses `pytest`. All new features should be accompanied by unit or integration tests.

### Running Tests
```bash
pytest tests/
```

### Async Tests
Since the MCP server is heavily asynchronous, many tests use `pytest-asyncio`. Ensure your test environment is correctly configured.

## Project Structure

- `src/sktime_mcp/server.py`: The main entry point and tool dispatcher.
- `src/sktime_mcp/tools/`: Implementation of individual MCP tools, grouped by category.
- `src/sktime_mcp/runtime/`: State management, handle registry, and job execution.
- `src/sktime_mcp/data/`: Data loading and formatting logic.
- `src/sktime_mcp/composition/`: Pipeline validation and building.

## Pull Request Process

1. Create a new branch for your feature or bug fix.
2. Ensure all tests pass and linting is clean.
3. Update the documentation if you are adding or changing tools.
4. Submit a PR with a clear description of the changes and references to any related issues.