# File-Based Agent Skills Sample

This sample demonstrates how to use **file-based Agent Skills** with a `ChatClientAgent`.

## What it demonstrates

- Discovering skills from `SKILL.md` files on disk via `AgentFileSkillsSource`
- The progressive disclosure pattern: advertise → load → read resources → run scripts
- Using the `AgentSkillsProvider` constructor with a skill directory path and script runner
- Running file-based scripts (Python) via a subprocess-based executor

## Skills Included

### unit-converter

Converts between common units (miles↔km, pounds↔kg) using a multiplication factor.

- `references/conversion-table.md` — Conversion factor table
- `scripts/convert.py` — Python script that performs the conversion

## Running the Sample

### Prerequisites

- .NET 10.0 SDK
- Azure OpenAI endpoint with a deployed model
- Python 3 installed and available as `python3` on your PATH

### Setup

```bash
export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
```

### Run

```bash
dotnet run
```

### Expected Output

```
Converting units with file-based skills
------------------------------------------------------------
Agent: Here are your conversions:

1. **26.2 miles → 42.16 km** (a marathon distance)
2. **75 kg → 165.35 lbs**
```