Does this skill support complex types like Enums and Unions?

Yes, it provides patterns for Enums, Literals, and Unions, which are highly effective for providing LLMs with clear, constrained choices for better output accuracy.

Are field descriptions mandatory in Atomic Agents schemas?

While Python doesn't require them, they are essential for AI agents because LLMs use these descriptions to understand the purpose and context of each field.

How do I add business logic validation to my agent's input?

You can use Pydantic's @field_validator for specific fields or @model_validator for logic involving multiple fields directly within your schema definition.

Why should I use BaseIOSchema instead of Pydantic's BaseModel?

BaseIOSchema is specifically designed for Atomic Agents, providing the necessary metadata and integration hooks that allow the framework to map models to LLMs and tools effectively.

Atomic Agents Schema Designer

Name: Atomic Agents Schema Designer
Author: BrainBlend-AI

byBrainBlend-AI

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5,524

Data Science & ML

Defines robust, type-safe data contracts and Pydantic-based schemas for AI agents using the Atomic Agents framework.

About

The Atomic Agents Schema Designer skill streamlines the creation of structured data models for complex AI agent interactions. By leveraging the specialized BaseIOSchema class, it ensures seamless integration between agents, tools, and external systems while providing a reliable framework for data validation, type constraints, and LLM-optimized documentation. This skill is essential for developers building agentic workflows where precise input and output definitions are required for LLM reliability, stability, and production-grade performance.

Key Features

Automatic implementation of BaseIOSchema for Atomic Agents integration
5,524 GitHub stars
Integrated Pydantic field and model validation patterns
Standardized templates for tool inputs, chat I/O, and complex nested models
Advanced field constraints including range, length, and literal types
LLM-optimized schema documentation using descriptions and docstrings

Use Cases

Designing complex nested data structures for automated data extraction and analysis
Creating strictly validated tool parameters to increase LLM reliability
Defining structured input and output contracts for multi-agent collaboration

About

Key Features

Automatic implementation of BaseIOSchema for Atomic Agents integration
5,524 GitHub stars
Integrated Pydantic field and model validation patterns
Standardized templates for tool inputs, chat I/O, and complex nested models
Advanced field constraints including range, length, and literal types
LLM-optimized schema documentation using descriptions and docstrings

Use Cases

Designing complex nested data structures for automated data extraction and analysis
Creating strictly validated tool parameters to increase LLM reliability
Defining structured input and output contracts for multi-agent collaboration