Build a Modular Skill-Based Agent System for LLMs with Dynamic Tool Routing in Python

It looks like you've provided a comprehensive code snippet for an advanced AI agent system, which includes several components such as skill-based agents, dynamic skill loading and unloading, composite skills, and more. Here's a breakdown of the key parts and functionalities:

Key Components

1. Skill Classes:

   • Each skill is defined by inheriting from Skill class.
   • Skills have metadata (name, description, category, etc.) and a schema that defines their input parameters.
   • The execute method contains the logic for what the skill does.

2. SkillRegistry:

   • Manages a collection of skills.
   • Provides methods to register, get, list, and introspect skills.

3. SkillLoader:

   • Facilitates dynamic loading and unloading of skills.
   • Uses SkillRegistry for managing the lifecycle of skills.

4. SkillIntrospectorSkill:

   • A meta-skill that allows querying the skill registry to discover available skills or get details about a specific skill.

5. Composite Skills (e.g., ResearchReportSkill):

   • Combine multiple simpler skills to perform more complex tasks.
   • Example: `Research

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