agent-skills/skills/agent-supervisor/SKILL.md

name, version, description, inputs, steps, outputs, tags, metadata

name	version	description	inputs	steps	outputs	tags	metadata
agent-supervisor	1.0.0	Demonstrate a supervisor-worker architecture for intelligent task delegation and real-time decision-making.	name description OPENAI_API_KEY OpenAI API key for language models. name description TAVILY_API_KEY Tavily API key for search functionality.	step action details 1 Load environment variables. Set the OPENAI_API_KEY and TAVILY_API_KEY environment variables. step action details 2 Configure LangChain tools. Initialize TavilySearchResults and PythonREPLTool. step action details 3 Define agent nodes. Create functions for the Researcher and Coder agents that process state through their respective tasks. step action details 4 Set up supervisor agent. Create a supervisor agent function that decides which worker should act next based on user input. step action details 5 Build state graph. Construct the state graph with nodes for each agent and edges connecting them to the supervisor node. step action details 6 Add conditional edges. Define conditions for transitioning between agents based on their responses. step action details 7 Compile graph. Compile the state graph into a runnable workflow. step action details 8 Run example queries. Stream through the workflow with example inputs to demonstrate its functionality.	name description Example 1: Code Hello World A demonstration of coding a simple hello world program. name description Example 2: Research Report A demonstration of researching and writing a brief report on pikas.		source_repo extracted_at confidence https://github.com/extrawest/multi_agent_workflow_demo_in_langgraph.git 0.9

agent-supervisor

Demonstrate a supervisor-worker architecture for intelligent task delegation and real-time decision-making.

Steps

1. {'step': 1, 'action': 'Load environment variables.', 'details': 'Set the OPENAI_API_KEY and TAVILY_API_KEY environment variables.'}
2. {'step': 2, 'action': 'Configure LangChain tools.', 'details': 'Initialize TavilySearchResults and PythonREPLTool.'}
3. {'step': 3, 'action': 'Define agent nodes.', 'details': 'Create functions for the Researcher and Coder agents that process state through their respective tasks.'}
4. {'step': 4, 'action': 'Set up supervisor agent.', 'details': 'Create a supervisor agent function that decides which worker should act next based on user input.'}
5. {'step': 5, 'action': 'Build state graph.', 'details': 'Construct the state graph with nodes for each agent and edges connecting them to the supervisor node.'}
6. {'step': 6, 'action': 'Add conditional edges.', 'details': 'Define conditions for transitioning between agents based on their responses.'}
7. {'step': 7, 'action': 'Compile graph.', 'details': 'Compile the state graph into a runnable workflow.'}
8. {'step': 8, 'action': 'Run example queries.', 'details': 'Stream through the workflow with example inputs to demonstrate its functionality.'}

Inputs

• {'name': 'OPENAI_API_KEY', 'description': 'OpenAI API key for language models.'}
• {'name': 'TAVILY_API_KEY', 'description': 'Tavily API key for search functionality.'}

Outputs

• {'name': 'Example 1: Code Hello World', 'description': 'A demonstration of coding a simple hello world program.'}
• {'name': 'Example 2: Research Report', 'description': 'A demonstration of researching and writing a brief report on pikas.'}

Failure Modes

• {'mode': 'Invalid API keys', 'description': 'The workflow may fail if the provided API keys are invalid or expired.'}
• {'mode': 'Insufficient permissions', 'description': 'The workflow may fail if the user does not have sufficient permissions to use the Tavily search functionality.'}

Source

Extracted from: https://github.com/extrawest/multi_agent_workflow_demo_in_langgraph.git Confidence: 0.9