Documentation Index
Fetch the complete documentation index at: https://agentstack.beeai.dev/llms.txt
Use this file to discover all available pages before exploring further.
User messages need metadata that fulfills agent service demands and includes user responses to forms, approvals, and canvas requests. This guide shows how to build properly structured A2A messages with the correct metadata attached.
See Agent Requirements for the fulfillment and UI metadata helpers used in this flow.
Build a message builder
buildMessageBuilder returns a function that resolves agent demands and builds a user message with metadata.
import { buildMessageBuilder } from "agentstack-sdk";
const buildMessage = buildMessageBuilder(agentCard);
const message = await buildMessage(
"context-id",
{
llm: async (demands) => ({
llm_fulfillments: {
default: {
identifier: "llm_proxy",
api_base: "{platform_url}/api/v1/openai/",
api_key: contextToken.token,
api_model: "gpt-4o",
},
},
}),
},
{
messageId: "message-id",
parts: [{ kind: "text", text: "Hello" }],
},
);
Add user responses
Use resolveUserMetadata when the user responds to forms, approvals, or canvas requests.
import { resolveUserMetadata } from "agentstack-sdk";
const metadata = await resolveUserMetadata({
form: { name: "Ada" },
approvalResponse: { decision: "approve" },
});