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Eduard van Valkenburg
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* updated automation tasks and commands, with alias for the time being * Restore aggregate test exclusions Preserve the legacy all-tests scope for test --all by excluding lab and devui from the default aggregate sweep, while still allowing explicit package selection. Also ignore hidden/generated test directories such as .mypy_cache during aggregate discovery. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated versions in pre-commit --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Code-Defined Agent Skills
This sample demonstrates how to create Agent Skills in Python code, without needing SKILL.md files on disk. A unit-converter skill shows three approaches:
What's Demonstrated
- Static Resources — Pass inline content via the
resourcesparameter when constructing aSkill - Dynamic Resources — Attach callable functions via the
@skill.resourcedecorator that return content computed at runtime - Dynamic Scripts — Attach callable scripts via the
@skill.scriptdecorator (unit conversion via a single factor parameter)
All three can be combined with file-based skills in a single SkillsProvider.
Project Structure
code_defined_skill/
├── code_defined_skill.py
└── README.md
Running the Sample
Prerequisites
- An Azure AI Foundry project with a deployed model (e.g.
gpt-4o-mini)
Environment Variables
Set the required environment variables in a .env file (see python/.env.example):
AZURE_AI_PROJECT_ENDPOINT: Your Azure AI Foundry project endpointAZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: The name of your model deployment (defaults togpt-4o-mini)
Authentication
This sample uses AzureCliCredential for authentication. Run az login in your terminal before running the sample.
Run
cd python
uv run samples/02-agents/skills/code_defined_skill/code_defined_skill.py