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Makeup of a Standard Agent

In order to create a Standard Agent, you define the following:
  • Models: defines an LLM provider (currently supports OpenRouter and OpenAI) and model and fallbacks.
  • Tools: a typescript function that can be called by an agent. This is where most business integration logic lives.
  • Prompts: a prompt defines what the LLM will receive on any given turn of a conversation, including the system message, the available tools, the message history, and more.
  • Agents: an agent defines the structure and behavior of a conversation, including the type of conversation (AI-Human or Dual-AI), the initial prompt to use, limits on the number of turns, and what ends one side’s turns and yields the conversation to the other side.
Structurally an agent has a single prompt, a prompt can have many tools (which can be TypeScript functions, prompts, or agents) and a model, and a model can have multiple fallback models.

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Threads

To actually run an agent, you create a new thread specifying which agent you want to use. In other words you can think of a thread as an instance of an agent. Each thread is backed by a single Cloudflare DurableObject instance (defined in your wrangler.jsonc file as DurableThread). Each thread has its own SQLite database that stores the message history of that thread, the execution state of the agent, and detailed logs of the agent’s execution. To create a thread, you can use the ’+ New Thread’ button in the AgentBuilder UI, or you can submit an HTTP request: 
curl -X POST "https://example.com/api/threads" \
  -H "Content-Type: application/json" \
  -d '{
    "agent_id": "weather_agent",
    "tags": ["type:weather", "user:jane"]
  }'
If successful the response will be a JSON object containing the threadId: 
{
  "threadId": "123e4567-e89b-12d3-a456-426614174000",
  "agent_id": "weather_agent",
  "message": "Thread created successfully"
}
A thread’s id is a cryptographically unique identifier for a given conversation. Keeping track of this id in your client code is important as it allows you to communicate directly with the thread’s DurableObject instance.
Depending on your use case this id may need to be treated as an authentication token. Anyone with the threadId has full access to the thread’s data.

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Parent/Child Threads (Subagents)

When a prompt delegates to a dual_ai subagent, AgentBuilder creates a child thread linked to its parent:
  • child thread has isolated SQLite/messages/filesystem
  • parent tracks child state in a resumable registry
  • communication uses queued messages and lifecycle tools
  • attachments are copied across filesystems and rewritten to destination-local paths
This lets one orchestrator thread safely compose many worker/reviewer child threads. Once a thread is created, you can send new messages to the thread via HTTP request: 
curl -X POST "https://example.com/api/threads/123e4567-e89b-12d3-a456-426614174000/message" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "What is the weather in Paris today?",
    "role": "user"
  }'

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Messages

Both user provided content and model responses are called “messages” and are stored in the DurableThread database. The message history can be retrieved at via HTTP request: 
curl -X GET "https://example.com/api/threads/123e4567-e89b-12d3-a456-426614174000/messages" \
  -H "Content-Type: application/json"
Additionally live message data can be streamed via WebSocket, however the simplest way to connect to the WebSocket and use live message data is to implement the @standardagents/react package.

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Next Steps

React Package

Build UIs with @standardagents/react

API Reference

Read the API reference