| name | basic-agent |
| description | Provides a foundational template for building AI agents using the ReAct pattern. Use for: quick prototyping of new agent ideas, understanding core agentic loops, and as a starting point for custom agent development. |
Basic Agent Skill
This skill provides a basic agent template, demonstrating the ReAct (Reasoning and Acting) pattern. It is designed to be a simple, yet effective, starting point for developing AI agents.
Key Features
- ReAct Loop: Implements the fundamental Thought-Action-Observation cycle, enabling the agent to reason about its actions and learn from observations.
- Tool Integration: Offers a straightforward interface for incorporating custom tools, allowing the agent to interact with external systems or perform specific tasks.
- Context Management: Includes basic mechanisms for managing conversation history and maintaining context throughout interactions.
Usage Instructions
To utilize this basic agent skill, follow these steps:
- Define Tools: Create Python functions that the agent can call to perform actions. These functions should be self-contained and clearly defined.
- Initialize LLM: Configure your preferred Large Language Model (LLM) to serve as the agent's reasoning engine.
- Run Agent: Instantiate the
BasicAgent class with your LLM and tools, then invoke its run method with a user prompt to start the agent loop.
Example Implementation Sketch
class BasicAgent:
def __init__(self, llm, tools):
self.llm = llm
self.tools = tools
self.history = []
def run(self, prompt):
pass
Resources
