python-example

You define tools using Python SDK decorators by applying the @tool and @param metadata annotations to Python functions. This decorator-based approach generates structured tool definitions and configuration for AI agents within the Skill Engine SDK.

Decorator-based configuration works by using the @config annotation to persist and adjust runtime options directly in Python source code. This config-driven behavior loads settings from SKILL.md frontmatter, allowing dynamic status reporting and configuration retrieval during execution.

Yes, you need Python 3.x and the Skill Engine Python SDK to build and test Python-based skills. The environment uses decorator-based metadata for tools, config, and status methods, loading behavior from SKILL.md frontmatter and Python source.

The best way to start prototyping is to run the python-example skill commands like 'skill run python-example:greet --name "Alice"'. This educational template demonstrates tool definitions, configuration, and status reporting to accelerate learning and testing.

Yes, you can retrieve the current skill configuration and available tools through status and discovery methods. The Python SDK uses decorators to expose these runtime options, allowing you to query the skill's active configuration and registered tool definitions.

Using decorators for Python SDK tools keeps tool definitions, configuration, and status reporting directly within the Python source code. This approach streamlines educational tutorials and rapid prototyping by loading behavior directly from SKILL.md frontmatter and functions.