Quick Agent Creation

Create a new Atomic Agents agent based on the user's description.

Process

1. Understand Requirements

If $ARGUMENTS is provided, parse the agent description. Otherwise, ask:

• What should this agent do?
• What input does it need?
• What output should it produce?

2. Load Knowledge

Use the Skill tool to load: atomic-agents
Use the Skill tool to load: atomic-schemas
Use the Skill tool to load: atomic-prompts

3. Identify Target Location

• Check if there's an existing project structure
• Look for agents/ directory or determine where to create the agent
• Identify existing schemas to potentially reuse

4. Design the Agent

Use the schema-designer agent for complex schemas:

Task(subagent_type="schema-designer", prompt="Design input and output schemas for an agent that: [description]. Use ultrathink.")

5. Create Files

Create the following:

schemas.py (or add to existing):

from atomic_agents.lib.base.base_io_schema import BaseIOSchema
from pydantic import Field

class [Agent]InputSchema(BaseIOSchema):
    """Input for [agent purpose]."""
    # fields...

class [Agent]OutputSchema(BaseIOSchema):
    """Output from [agent purpose]."""
    # fields...

[agent_name].py:

import instructor
import openai
from atomic_agents.agents.base_agent import AtomicAgent, AgentConfig
from atomic_agents.lib.components.system_prompt_generator import SystemPromptGenerator
from atomic_agents.lib.components.chat_history import ChatHistory

from .schemas import [Agent]InputSchema, [Agent]OutputSchema

# Initialize client
client = instructor.from_openai(openai.OpenAI())

# Configure agent
config = AgentConfig(
    client=client,
    model="gpt-4o-mini",
    history=ChatHistory(),
    system_prompt_generator=SystemPromptGenerator(
        background=[
            "You are an expert [role].",
            "Your purpose is to [purpose].",
        ],
        steps=[
            "1. [First step]",
            "2. [Second step]",
            "3. [Third step]",
        ],
        output_instructions=[
            "Provide [format instructions].",
            "Ensure [quality requirements].",
        ],
    ),
)

# Create agent
agent = AtomicAgent[InputSchema, OutputSchema](config=config)

6. Provide Usage Example

Show how to use the created agent:

from [module] import agent, [Agent]InputSchema

# Run the agent
input_data = [Agent]InputSchema(field="value")
output = agent.run(input_data)
print(output)

7. Quick Review

Perform a quick validation:

• Schemas inherit from BaseIOSchema
• All fields have descriptions
• SystemPromptGenerator has background, steps, output_instructions
• Client is wrapped with instructor
• Type parameters match schemas

Report any issues found.

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Output

Provide:

1. Created files with their paths
2. Usage example
3. Any suggestions for enhancement