ai-skill-interface

Create a mini-application named 'SkillMaster' using the Python package 'ai-skill-interface'. This application will serve as a platform where users can interact with various AI skills through a simple command-line interface. The primary goal of SkillMaster is to demonstrate how different AI skills can be integrated into a single application without the user needing to understand the underlying complexities of each skill's implementation.

### Core Features:
1. **Skill Registration**: Users should be able to register new skills within the application. Each skill must adhere to the abstract skill interface provided by 'ai-skill-interface', defining what the skill does but not how it accomplishes its task.
2. **Skill Execution**: Once registered, users can execute skills by providing necessary inputs. The application should handle the execution process, including passing inputs to the appropriate skill and displaying outputs.
3. **Skill Testing**: Implement a feature that allows developers to test their skills within the application environment. This includes running predefined test cases and validating the skill's output against expected results.
4. **Security Checks**: Integrate basic security checks to ensure that only authorized skills are executed. This could involve verifying digital signatures of uploaded skills or checking against a whitelist of approved skills.
5. **Documentation Generation**: Automatically generate documentation for each skill, detailing its purpose, input/output formats, and any other relevant information.

### Steps to Build the Application:
1. **Setup Environment**: Begin by setting up your Python development environment and installing the 'ai-skill-interface' package.
2. **Define Skill Interface**: Using the package, define an abstract skill interface that all skills in your application must implement. This interface should specify methods such as `execute`, `test`, and `validate`.
3. **Develop Sample Skills**: Create a few sample skills that demonstrate the variety of functionalities possible with 'ai-skill-interface'. For example, one skill could perform sentiment analysis on text, while another might solve mathematical equations.
4. **Build Command-Line Interface**: Develop a simple CLI that allows users to register, execute, and test skills. Ensure that the CLI guides users through the process of interacting with the application.
5. **Implement Security Measures**: Add functionality to validate skills before they are allowed to run. This could include signature verification or checks against a list of approved skills.
6. **Generate Documentation**: Automate the generation of documentation for each skill, ensuring that it is easily accessible from within the application.
7. **Testing and Validation**: Rigorously test the application and each skill to ensure reliability and correctness.
8. **Final Deployment**: Package the application for deployment, making it available for others to use and extend.

By following these steps, you'll create a versatile mini-application that showcases the power and flexibility of the 'ai-skill-interface' package.