oa-library-templates

To create an AI agent template in JSON format, you must follow a standardized framework defining mandatory and optional fields, model selection, and tool usage rules. This ensures your agent is correctly structured, categorized, and optimized for performance and cost.

Choosing a Claude model for an agent template involves using a specific decision tree based on task complexity. For example, select haiku for simple summaries and sonnet for more complex analysis, ensuring the agent is optimized for performance and cost.

To categorize agent templates in a library, you apply predefined category management guidelines. You assign the agent to existing categories like code-dev or follow specific rules to create new ones, ensuring library discoverability and consistency.

Required fields for a JSON agent template include specific mandatory structures defined by the framework to ensure consistency. The template structure details these mandatory fields alongside optional ones, guiding correct agent design and library integration.

Yes, the framework supports tool usage in agent design by detailing available tools and their application. It provides specific guidance on how to integrate tools within the JSON template to ensure the agent functions correctly.