oracle-agent-spec

Portable AI agents are defined using a declarative JSON or YAML agent spec that abstracts framework-specific logic, enabling the exact same blueprint to deploy across Oracle ADK and LangGraph runtimes.

Yes, you can define AI agent workflows in YAML without framework-specific logic by using a declarative agent-spec format to configure LLMNodes, APINodes, and workflows for cross-runtime execution.

The best way to migrate an agent from a sandbox to production OCI is to define it using a framework-agnostic agent spec, validate cross-runtime compatibility, and compile the declarative blueprint for deployment with minimal rewrites.

Yes, the Open Agent Specification supports both JSON and YAML definitions for writing portable, versioned AI agent configurations that can be executed across different deployment runtimes without framework-specific logic.

You validate cross-runtime compatibility for declarative agent blueprints by loading the JSON or YAML agent spec and checking it against target runtimes like Oracle ADK and LangGraph to ensure seamless portability.

You need a versioned agent-spec format when you require reusable agent blueprints and multi-runtime compatibility to safely migrate declarative AI components across different execution environments without structural conflicts.