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Deprecation notice: The Default and ReAct styles are going to be removed in a future release. Only ReAct Core (react_core) remains. Migrate your agents to ReAct Core as soon as possible. See the agent style migration guide for instructions.
Agent styles define how the agent reasons through problems and how it behaves when collaborating with other agents. You can choose from three styles:
Note:
If you use GPT-OSS-120B or GPT-5.4 as your agent’s model, the agent ignores all styles and uses ReAct Core automatically.

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ReAct Core style

Choose ReAct Core (react_core) for complex tasks and multi-agent workflows. It uses the model’s built-in function calling and is optimized for accurate collaboration, keeping collaborators focused on the task at hand. Use this style for:
  • Multi-agent workflows with collaborator agents
  • Complex reasoning tasks
  • Any scenario where collaborator accuracy matters
Note: react_core is the canonical identifier in the ADK and the UI, displayed as ReAct Core. ReAct Core (react_core) was previously named ReAct Intrinsic (react_intrinsic).In the ADK, react_intrinsic is accepted as an alias for react_core and behaves identically. In the REST API, react_intrinsic is the accepted value.

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Default style (Deprecated)

Choose Default (default) for simple tasks. This style uses a streamlined, tool-centric reasoning mode. The LLM decides which tool to use, how to use it, and when to respond. It works best for linear logic, such as retrieving a report or checking a ticket, because the agent orchestrates tool calls dynamically. Use this style for:
  • Single-step or lightly sequential tasks
  • Scenarios that need flexibility
  • Tasks that involve multiple tools without strict sequencing

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ReAct style (Deprecated)

Choose ReAct (react) for complex or ambiguous problems where each outcome influences the next step. This style uses an iterative loop: Think → Act → Observe. It supports reasoning, validation, and interactive confirmation. Inspired by the ReAct methodology, it surfaces the agent’s chain of thought. A ReAct agent breaks tasks into smaller steps, reasons through each, takes action, and adjusts based on what it learns. It might ask you for confirmation before continuing. Use this style for:
  • Exploratory or research-intensive tasks
  • Scenarios requiring iterative validation
  • Tasks with unclear or evolving requirements
  • Situations where transparent reasoning matters