Skills

A skill is a package of structured files that teaches an AI coding agent how to work with a specific tool or framework. The skill below was generated by Great Docs from this project’s documentation. Install it in your agent and it will be able to run commands, edit configuration, write content, and troubleshoot problems without step-by-step guidance from you.

Any agent — install with npx:

npx skills add https://ambmodels.github.io/ambforecast/

Codex / OpenCode

Tell the agent:
Fetch the skill file at https://ambmodels.github.io/ambforecast/skill.md and follow the instructions.

Manual — download the skill file:

curl -O https://ambmodels.github.io/ambforecast/skill.md

Or browse the SKILL.md file.

SKILL.md

---
name: ambforecast
description: >
  Ambulance forecast. Use when writing Python code that uses the ambforecast package.
compatibility: Requires Python >=3.10.
---

# ambforecast

Ambulance forecast

## Installation

```bash
pip install ambforecast
```

## API overview

### Data preparation

Prepare and validate historic, holiday, and temperature data.

- `preprocessing.prepare_historic`
- `preprocessing.validate_historic`
- `preprocessing.prepare_holidays`
- `preprocessing.validate_holidays`
- `preprocessing.expand_holiday_windows`
- `preprocessing.prepare_temp`
- `preprocessing.interpolate_temp`
- `preprocessing.validate_temp`

### Data splitting

Create train/test splits and rolling forecast origin samples.

- `splits.train_test_split`
- `splits.rolling_forecast_origin`

### ARIMA

Configure and run ARIMA forecasts.

- `arima.ARIMAParams`
- `arima.arima`

### Prophet

Configure and run Prophet forecasts.

- `prophet.ProphetRegressor`
- `prophet.ProphetParams`
- `prophet.prophet`

### Naive benchmark

Configure and run Seasonal Naive forecasts.

- `naive.SNaiveParams`
- `naive.snaive`

### Running forecasts

Run individual, multi-area/metric, and cross-validation forecasts.

- `forecast.run_single_forecast`
- `forecast.run_forecasts`
- `forecast.run_cross_validation`

### Ensembles

Combine forecasts.

- `ensemble.ensemble`

### Forecast evaluation

Calculate forecast accuracy measures.

- `errors.forecast_errors`
- `errors.calculate_errors`

### Plotting

Visualise results.

- `plot.plot_forecast`
- `plot.plot_cross_validation`
- `plot.plot_observed_against_forecast`
- `plot.plot_holiday_coverage`
- `plot.plot_error_over_time`
- `plot.plot_error_boxplot`

## Resources

- [Full documentation](https://ambmodels.github.io/ambforecast/)
- [llms.txt](llms.txt) — Indexed API reference for LLMs
- [llms-full.txt](llms-full.txt) — Comprehensive documentation for LLMs