Cedar-OS provides TypeScript types and Zod schemas for agent responses, enabling type-safe handling of LLM outputs, structured responses, streaming events, and frontend tool execution.

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Basic LLM Responses

The core response type contains the agent’s text response along with usage and metadata information: TypeScript Type: 
interface LLMResponse {
	content: string;
	usage?: {
		promptTokens: number;
		completionTokens: number;
		totalTokens: number;
	};
	metadata?: Record<string, unknown>;
	// The object field contains structured output when using JSON Schema or Zod
	object?: StructuredResponseType | StructuredResponseType[];
}
Corresponding Zod Schema: 
import { LLMResponseSchema } from 'cedar-os';

// Basic response schema (no structured output)
const BasicResponseSchema = LLMResponseSchema();

// With custom structured output schema
const TaskResponseSchema = LLMResponseSchema(
	z.object({
		taskId: z.string(),
		title: z.string(),
		completed: z.boolean(),
	})
);

// Usage example
const response = TaskResponseSchema.parse(agentResponse);
const taskId = response.object?.taskId; // ✅ Fully typed

​
Structured Responses

For agents that return structured data, Cedar provides flexible typing for custom response objects: TypeScript Types: 
// Base structure for all response objects
interface BaseStructuredResponseType {
	type: string;
	content?: string;
}

// Create custom response types
type CustomStructuredResponseType<
	T extends string,
	P extends object = Record<string, never>
> = BaseStructuredResponseType & { type: T } & P;

// Example: Task creation response
type CreateTaskResponse = CustomStructuredResponseType<
	'create_task',
	{
		taskId: string;
		title: string;
		assignee?: string;
	}
>;
Corresponding Zod Schemas: 
import {
	StructuredResponseSchema,
	BaseStructuredResponseSchema,
} from 'cedar-os';

// Generic structured response schema
const AnyStructuredResponse = BaseStructuredResponseSchema;

// Specific response type schema
const CreateTaskResponseSchema = StructuredResponseSchema('create_task').and(
	z.object({
		taskId: z.string(),
		title: z.string(),
		assignee: z.string().optional(),
	})
);

// Usage with LLMResponse
const TaskResponseSchema = LLMResponseSchema(CreateTaskResponseSchema);

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Built-in Response Types

Cedar provides several built-in response types with corresponding TypeScript types and Zod schemas:

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FrontendToolResponse

For executing registered frontend tools: TypeScript Type: 
type FrontendToolResponse = CustomStructuredResponseType<
	'frontendTool',
	{
		toolName: string;
		args?: unknown;
	}
>;

// Example usage
type SendEmailToolResponse = CustomStructuredResponseType<
	'frontendTool',
	{
		toolName: 'sendEmail';
		args: {
			to: string;
			subject: string;
			body: string;
		};
	}
>;
Corresponding Zod Schema: 
import { FrontendToolResponseSchema } from 'cedar-os';

// Basic frontend tool response validation
const response = FrontendToolResponseSchema.parse({
	type: 'frontendTool',
	toolName: 'sendEmail',
	args: {
		to: 'user@example.com',
		subject: 'Hello',
		body: 'This is a test email',
	},
});

// Create specific tool response schemas
const SendEmailToolSchema = FrontendToolResponseSchema.and(
	z.object({
		toolName: z.literal('sendEmail'),
		args: z.object({
			to: z.string().email(),
			subject: z.string(),
			body: z.string(),
		}),
	})
);

​
SetStateResponse

For executing state setter functions: TypeScript Type: 
type SetStateResponse = CustomStructuredResponseType<
	'setState',
	{
		stateKey: string;
		setterKey: string;
		args?: unknown; // Single object parameter (v0.1.11+)
	}
>;

// Example usage
type AddTodoResponse = CustomStructuredResponseType<
	'setState',
	{
		stateKey: 'todos';
		setterKey: 'addTodo';
		args: {
			text: string;
			priority: 'low' | 'medium' | 'high';
		};
	}
>;
Corresponding Zod Schema: 
import { SetStateResponseSchema } from 'cedar-os';

// Basic setState response validation
const response = SetStateResponseSchema.parse({
	type: 'setState',
	stateKey: 'todos',
	setterKey: 'addTodo',
	args: {
		text: 'Learn Cedar-OS',
		priority: 'high',
	},
});

// Create specific setter response schemas
const AddTodoResponseSchema = SetStateResponseSchema.and(
	z.object({
		stateKey: z.literal('todos'),
		setterKey: z.literal('addTodo'),
		args: z.object({
			text: z.string(),
			priority: z.enum(['low', 'medium', 'high']),
		}),
	})
);

​
MessageResponse

For adding custom messages to chat: TypeScript Type: 
type MessageResponse = CustomStructuredResponseType<
	'message',
	{
		role?: 'user' | 'assistant' | 'bot';
		content: string;
	}
>;
Corresponding Zod Schema: 
import { BackendMessageResponseSchema } from 'cedar-os';

const messageResponse = BackendMessageResponseSchema.parse({
	type: 'message',
	role: 'assistant',
	content: 'Task completed successfully!',
});

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Streaming Responses

For real-time streaming, Cedar provides event-based typing: TypeScript Type: 
type StreamEvent =
	| { type: 'chunk'; content: string }
	| {
			type: 'object';
			object: StructuredResponseType | StructuredResponseType[];
	  }
	| { type: 'done'; completedItems: (string | object)[] }
	| { type: 'error'; error: unknown };
Corresponding Zod Schema: 
import { StreamEventSchema } from 'cedar-os';

// Validate streaming events
function handleStreamEvent(event: unknown) {
	const validatedEvent = StreamEventSchema.parse(event);

	switch (validatedEvent.type) {
		case 'chunk':
			console.log('Content:', validatedEvent.content); // ✅ string
			break;
		case 'object':
			console.log('Structured:', validatedEvent.object); // ✅ StructuredResponseType
			break;
		case 'done':
			console.log('Completed:', validatedEvent.completedItems); // ✅ (string | object)[]
			break;
		case 'error':
			console.error('Error:', validatedEvent.error); // ✅ unknown
			break;
	}
}

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Voice Responses

For voice-enabled agents, Cedar extends the base response with audio-specific fields: TypeScript Type: 
interface VoiceLLMResponse extends LLMResponse {
	transcription?: string;
	audioData?: string; // Base64 encoded audio
	audioUrl?: string;
	audioFormat?: string;
}
Corresponding Zod Schema: 
import { VoiceLLMResponseSchema } from 'cedar-os';

// Basic voice response schema
const BasicVoiceResponseSchema = VoiceLLMResponseSchema();

// Voice response with structured output
const VoiceTaskResponseSchema = VoiceLLMResponseSchema(
	z.object({
		action: z.enum(['create', 'update', 'delete']),
		target: z.string(),
	})
);

// Usage example
const voiceResponse = VoiceTaskResponseSchema.parse(agentResponse);
const transcription = voiceResponse.transcription; // ✅ string | undefined
const action = voiceResponse.object?.action; // ✅ 'create' | 'update' | 'delete' | undefined

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Next Steps

Now that you understand response typing, learn about: