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* add class-based skills * address formating issues * Remove generated filtered-unit.slnx and add to .gitignore The filtered solution file is generated dynamically by eng/scripts/New-FilteredSolution.ps1 during CI. Checking it in risks it becoming stale and out-of-sync with the real solution. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove generated filtered-unit.slnx and add to .gitignore The filtered solution file is generated dynamically by eng/scripts/New-FilteredSolution.ps1 during CI. Checking it in risks it becoming stale and out-of-sync with the real solution. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * consolidate DI samples into one * fix file encoding * suppress compatibility warning --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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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.mdfiles on disk viaAgentFileSkillsSource - The progressive disclosure pattern: advertise → load → read resources → run scripts
- Using the
AgentSkillsProviderconstructor 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 tablescripts/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
python3on your PATH
Setup
export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
Run
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**